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"2023-08-25T08:35:14Z"

"2023-08-25T08:36:15Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6177). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005847 / 0.011353 (-0.005506) | 0.003488 / 0.011008 (-0.007521) | 0.079545 / 0.038508 (0.041037) | 0.055114 / 0.023109 (0.032005) | 0.312694 / 0.275898 (0.036796) | 0.338808 / 0.323480 (0.015329) | 0.004573 / 0.007986 (-0.003413) | 0.002818 / 0.004328 (-0.001510) | 0.062102 / 0.004250 (0.057852) | 0.044072 / 0.037052 (0.007019) | 0.317682 / 0.258489 (0.059192) | 0.354139 / 0.293841 (0.060298) | 0.026905 / 0.128546 (-0.101641) | 0.007990 / 0.075646 (-0.067656) | 0.260071 / 0.419271 (-0.159201) | 0.043658 / 0.043533 (0.000125) | 0.313828 / 0.255139 (0.058689) | 0.339678 / 0.283200 (0.056478) | 0.020076 / 0.141683 (-0.121607) | 1.446321 / 1.452155 (-0.005834) | 1.527046 / 1.492716 (0.034330) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.197801 / 0.018006 (0.179795) | 0.432874 / 0.000490 (0.432385) | 0.004093 / 0.000200 (0.003893) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023505 / 0.037411 (-0.013906) | 0.072377 / 0.014526 (0.057852) | 0.081058 / 0.176557 (-0.095498) | 0.141628 / 0.737135 (-0.595507) | 0.081622 / 0.296338 (-0.214716) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.395005 / 0.215209 (0.179795) | 3.949006 / 2.077655 (1.871352) | 1.934028 / 1.504120 (0.429908) | 1.756065 / 1.541195 (0.214871) | 1.778719 / 1.468490 (0.310229) | 0.501279 / 4.584777 (-4.083498) | 3.032120 / 3.745712 (-0.713592) | 2.859751 / 5.269862 (-2.410110) | 1.885924 / 4.565676 (-2.679753) | 0.057236 / 0.424275 (-0.367039) | 0.006704 / 0.007607 (-0.000903) | 0.465794 / 0.226044 (0.239750) | 4.648622 / 2.268929 (2.379694) | 2.345649 / 55.444624 (-53.098975) | 1.981122 / 6.876477 (-4.895355) | 2.148235 / 2.142072 (0.006163) | 0.591466 / 4.805227 (-4.213761) | 0.125262 / 6.500664 (-6.375402) | 0.061305 / 0.075469 (-0.014164) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243932 / 1.841788 (-0.597856) | 17.912110 / 8.074308 (9.837802) | 13.662097 / 10.191392 (3.470705) | 0.148051 / 0.680424 (-0.532373) | 0.016778 / 0.534201 (-0.517423) | 0.340342 / 0.579283 (-0.238941) | 0.351720 / 0.434364 (-0.082644) | 0.377837 / 0.540337 (-0.162501) | 0.521163 / 1.386936 (-0.865774) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006011 / 0.011353 (-0.005342) | 0.003549 / 0.011008 (-0.007459) | 0.063579 / 0.038508 (0.025071) | 0.056196 / 0.023109 (0.033087) | 0.448879 / 0.275898 (0.172981) | 0.491542 / 0.323480 (0.168062) | 0.004597 / 0.007986 (-0.003389) | 0.002790 / 0.004328 (-0.001539) | 0.063257 / 0.004250 (0.059006) | 0.045653 / 0.037052 (0.008600) | 0.459714 / 0.258489 (0.201225) | 0.491371 / 0.293841 (0.197530) | 0.028124 / 0.128546 (-0.100422) | 0.008016 / 0.075646 (-0.067630) | 0.069418 / 0.419271 (-0.349853) | 0.040393 / 0.043533 (-0.003140) | 0.450978 / 0.255139 (0.195839) | 0.472075 / 0.283200 (0.188875) | 0.020006 / 0.141683 (-0.121677) | 1.451946 / 1.452155 (-0.000209) | 1.513557 / 1.492716 (0.020840) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225416 / 0.018006 (0.207410) | 0.412287 / 0.000490 (0.411797) | 0.004075 / 0.000200 (0.003875) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025949 / 0.037411 (-0.011463) | 0.080633 / 0.014526 (0.066108) | 0.089960 / 0.176557 (-0.086597) | 0.144530 / 0.737135 (-0.592606) | 0.091427 / 0.296338 (-0.204911) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462311 / 0.215209 (0.247102) | 4.605063 / 2.077655 (2.527408) | 2.541083 / 1.504120 (1.036963) | 2.356341 / 1.541195 (0.815147) | 2.389824 / 1.468490 (0.921334) | 0.507397 / 4.584777 (-4.077380) | 3.079023 / 3.745712 (-0.666689) | 2.792025 / 5.269862 (-2.477837) | 1.846931 / 4.565676 (-2.718746) | 0.058422 / 0.424275 (-0.365853) | 0.006409 / 0.007607 (-0.001199) | 0.530648 / 0.226044 (0.304604) | 5.321030 / 2.268929 (3.052101) | 2.978335 / 55.444624 (-52.466289) | 2.641188 / 6.876477 (-4.235288) | 2.780450 / 2.142072 (0.638378) | 0.593864 / 4.805227 (-4.211363) | 0.125394 / 6.500664 (-6.375270) | 0.061432 / 0.075469 (-0.014037) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337142 / 1.841788 (-0.504646) | 18.841575 / 8.074308 (10.767267) | 14.678622 / 10.191392 (4.487230) | 0.144491 / 0.680424 (-0.535933) | 0.018145 / 0.534201 (-0.516056) | 0.339376 / 0.579283 (-0.239907) | 0.339129 / 0.434364 (-0.095235) | 0.394842 / 0.540337 (-0.145495) | 0.547924 / 1.386936 (-0.839012) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#57af0ab30796df59d28bf933e756ffbe5f34db1e \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006478 / 0.011353 (-0.004875) | 0.003845 / 0.011008 (-0.007163) | 0.084179 / 0.038508 (0.045671) | 0.071327 / 0.023109 (0.048217) | 0.315206 / 0.275898 (0.039308) | 0.353477 / 0.323480 (0.029997) | 0.005267 / 0.007986 (-0.002719) | 0.003282 / 0.004328 (-0.001046) | 0.064062 / 0.004250 (0.059811) | 0.051940 / 0.037052 (0.014888) | 0.332004 / 0.258489 (0.073515) | 0.363199 / 0.293841 (0.069358) | 0.030546 / 0.128546 (-0.098000) | 0.008453 / 0.075646 (-0.067193) | 0.287636 / 0.419271 (-0.131636) | 0.051999 / 0.043533 (0.008466) | 0.325220 / 0.255139 (0.070081) | 0.355324 / 0.283200 (0.072125) | 0.023417 / 0.141683 (-0.118266) | 1.473370 / 1.452155 (0.021215) | 1.596903 / 1.492716 (0.104186) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212645 / 0.018006 (0.194638) | 0.463766 / 0.000490 (0.463276) | 0.002834 / 0.000200 (0.002634) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028424 / 0.037411 (-0.008987) | 0.082188 / 0.014526 (0.067662) | 0.777186 / 0.176557 (0.600629) | 0.218290 / 0.737135 (-0.518845) | 0.099098 / 0.296338 (-0.197240) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387138 / 0.215209 (0.171929) | 3.845655 / 2.077655 (1.768000) | 1.929812 / 1.504120 (0.425692) | 1.718263 / 1.541195 (0.177069) | 1.760933 / 1.468490 (0.292443) | 0.475171 / 4.584777 (-4.109606) | 3.523366 / 3.745712 (-0.222346) | 3.167322 / 5.269862 (-2.102540) | 1.975164 / 4.565676 (-2.590513) | 0.056106 / 0.424275 (-0.368169) | 0.007448 / 0.007607 (-0.000159) | 0.459824 / 0.226044 (0.233779) | 4.590566 / 2.268929 (2.321638) | 2.377968 / 55.444624 (-53.066656) | 2.034052 / 6.876477 (-4.842425) | 2.224976 / 2.142072 (0.082904) | 0.575901 / 4.805227 (-4.229326) | 0.131546 / 6.500664 (-6.369118) | 0.059266 / 0.075469 (-0.016203) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.254783 / 1.841788 (-0.587005) | 19.497795 / 8.074308 (11.423487) | 13.937672 / 10.191392 (3.746280) | 0.164092 / 0.680424 (-0.516332) | 0.017915 / 0.534201 (-0.516286) | 0.391430 / 0.579283 (-0.187853) | 0.403681 / 0.434364 (-0.030683) | 0.457711 / 0.540337 (-0.082626) | 0.620395 / 1.386936 (-0.766541) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006793 / 0.011353 (-0.004560) | 0.004101 / 0.011008 (-0.006907) | 0.064780 / 0.038508 (0.026272) | 0.071087 / 0.023109 (0.047977) | 0.401963 / 0.275898 (0.126065) | 0.433085 / 0.323480 (0.109605) | 0.005348 / 0.007986 (-0.002638) | 0.003289 / 0.004328 (-0.001039) | 0.065209 / 0.004250 (0.060958) | 0.054202 / 0.037052 (0.017150) | 0.405629 / 0.258489 (0.147140) | 0.440326 / 0.293841 (0.146485) | 0.032283 / 0.128546 (-0.096263) | 0.008510 / 0.075646 (-0.067137) | 0.071144 / 0.419271 (-0.348127) | 0.047414 / 0.043533 (0.003881) | 0.402065 / 0.255139 (0.146926) | 0.421217 / 0.283200 (0.138017) | 0.021924 / 0.141683 (-0.119759) | 1.490067 / 1.452155 (0.037913) | 1.539134 / 1.492716 (0.046417) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280072 / 0.018006 (0.262066) | 0.456130 / 0.000490 (0.455641) | 0.020926 / 0.000200 (0.020726) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032040 / 0.037411 (-0.005371) | 0.092343 / 0.014526 (0.077817) | 0.104866 / 0.176557 (-0.071690) | 0.156631 / 0.737135 (-0.580505) | 0.107203 / 0.296338 (-0.189136) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426268 / 0.215209 (0.211059) | 4.255539 / 2.077655 (2.177884) | 2.285077 / 1.504120 (0.780957) | 2.114277 / 1.541195 (0.573083) | 2.159242 / 1.468490 (0.690752) | 0.489421 / 4.584777 (-4.095356) | 3.630797 / 3.745712 (-0.114915) | 3.205238 / 5.269862 (-2.064624) | 1.985846 / 4.565676 (-2.579830) | 0.057436 / 0.424275 (-0.366839) | 0.007154 / 0.007607 (-0.000454) | 0.507294 / 0.226044 (0.281250) | 5.050105 / 2.268929 (2.781176) | 2.750474 / 55.444624 (-52.694151) | 2.404116 / 6.876477 (-4.472360) | 2.576483 / 2.142072 (0.434411) | 0.584909 / 4.805227 (-4.220318) | 0.130695 / 6.500664 (-6.369969) | 0.059743 / 0.075469 (-0.015726) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352702 / 1.841788 (-0.489086) | 19.687944 / 8.074308 (11.613636) | 14.991847 / 10.191392 (4.800455) | 0.185164 / 0.680424 (-0.495260) | 0.020314 / 0.534201 (-0.513887) | 0.395162 / 0.579283 (-0.184121) | 0.408917 / 0.434364 (-0.025447) | 0.467049 / 0.540337 (-0.073288) | 0.649209 / 1.386936 (-0.737727) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#885518608ceab83b7ed8ceba7a0b72bc68096026 \"CML watermark\")\n" ]

"2023-08-24T16:16:09Z"

"2023-08-24T16:25:25Z"

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[ "Hi! Can you share the error this reproducer throws in your environment? `streaming=True` streams the dataset as it's iterated over without creating a memory-map file.", "The trace of the error. Streaming works but is slower.\r\n```\r\nRoot Cause (first observed failure):\r\n[0]:\r\n time : 2023-08-24_06:06:01\r\n host : compute-126.cm.cluster\r\n rank : 0 (local_rank: 0)\r\n exitcode : 1 (pid: 48442)\r\n error_file: /tmp/torchelastic_4fqzcuuz/none_rx2470jl/attempt_0/0/error.json\r\n traceback : Traceback (most recent call last):\r\n File \"/users/yli7/.conda/envs/pytorch2.0/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 346, in wrapper\r\n return f(*args, **kwargs)\r\n File \"Pretrain.py\", line 214, in main\r\n pair_dataset, c4_dataset = create_dataset('pretrain', config)\r\n File \"/dcs05/qiao/data/william/project/DaVinci/dataset/__init__.py\", line 109, in create_dataset\r\n c4_dataset = load_dataset(\"c4\", \"en\", split=\"train\").to_iterable_dataset(num_shards=1024).map(pre_caption_huggingface)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/load.py\", line 1810, in load_dataset\r\n ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1145, in as_dataset\r\n datasets = map_nested(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py\", line 436, in map_nested\r\n return function(data_struct)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1175, in _build_single_dataset\r\n ds = self._as_dataset(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1246, in _as_dataset\r\n dataset_kwargs = ArrowReader(cache_dir, self.info).read(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 244, in read\r\n return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 265, in read_files\r\n pa_table = self._read_files(files, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 200, in _read_files\r\n pa_table: Table = self._get_table_from_filename(f_dict, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 336, in _get_table_from_filename\r\n table = ArrowReader.read_table(filename, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 357, in read_table\r\n return table_cls.from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 1059, in from_file\r\n table = _memory_mapped_arrow_table_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 65, in _memory_mapped_arrow_table_from_file\r\n opened_stream = _memory_mapped_record_batch_reader_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 50, in _memory_mapped_record_batch_reader_from_file\r\n memory_mapped_stream = pa.memory_map(filename)\r\n File \"pyarrow/io.pxi\", line 1009, in pyarrow.lib.memory_map\r\n File \"pyarrow/io.pxi\", line 956, in pyarrow.lib.MemoryMappedFile._open\r\n File \"pyarrow/error.pxi\", line 144, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 115, in pyarrow.lib.check_status\r\n OSError: Memory mapping file failed: Cannot allocate memory\r\n```" ]

"2023-08-24T05:33:45Z"

"2023-08-24T17:32:00Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006095 / 0.011353 (-0.005258) | 0.003580 / 0.011008 (-0.007429) | 0.080146 / 0.038508 (0.041638) | 0.063445 / 0.023109 (0.040336) | 0.321930 / 0.275898 (0.046032) | 0.397933 / 0.323480 (0.074453) | 0.003455 / 0.007986 (-0.004531) | 0.002856 / 0.004328 (-0.001472) | 0.062938 / 0.004250 (0.058687) | 0.048896 / 0.037052 (0.011843) | 0.333070 / 0.258489 (0.074581) | 0.404485 / 0.293841 (0.110644) | 0.027156 / 0.128546 (-0.101390) | 0.007974 / 0.075646 (-0.067672) | 0.261505 / 0.419271 (-0.157766) | 0.045328 / 0.043533 (0.001795) | 0.311203 / 0.255139 (0.056064) | 0.390006 / 0.283200 (0.106806) | 0.023650 / 0.141683 (-0.118033) | 1.468856 / 1.452155 (0.016701) | 1.503867 / 1.492716 (0.011151) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202110 / 0.018006 (0.184103) | 0.436433 / 0.000490 (0.435944) | 0.002278 / 0.000200 (0.002078) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024575 / 0.037411 (-0.012836) | 0.073005 / 0.014526 (0.058479) | 0.083609 / 0.176557 (-0.092947) | 0.144881 / 0.737135 (-0.592254) | 0.083495 / 0.296338 (-0.212844) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398911 / 0.215209 (0.183702) | 3.994035 / 2.077655 (1.916381) | 2.056768 / 1.504120 (0.552649) | 1.913242 / 1.541195 (0.372047) | 1.932934 / 1.468490 (0.464444) | 0.498953 / 4.584777 (-4.085824) | 3.031107 / 3.745712 (-0.714605) | 2.817165 / 5.269862 (-2.452696) | 1.858886 / 4.565676 (-2.706790) | 0.056977 / 0.424275 (-0.367299) | 0.006634 / 0.007607 (-0.000973) | 0.472580 / 0.226044 (0.246536) | 4.738301 / 2.268929 (2.469372) | 2.373938 / 55.444624 (-53.070686) | 2.021057 / 6.876477 (-4.855420) | 2.195419 / 2.142072 (0.053346) | 0.585182 / 4.805227 (-4.220045) | 0.124260 / 6.500664 (-6.376405) | 0.060250 / 0.075469 (-0.015219) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.227350 / 1.841788 (-0.614438) | 18.496525 / 8.074308 (10.422216) | 13.946658 / 10.191392 (3.755266) | 0.140024 / 0.680424 (-0.540399) | 0.017077 / 0.534201 (-0.517124) | 0.334415 / 0.579283 (-0.244868) | 0.351118 / 0.434364 (-0.083246) | 0.379556 / 0.540337 (-0.160782) | 0.525064 / 1.386936 (-0.861872) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006176 / 0.011353 (-0.005177) | 0.003648 / 0.011008 (-0.007360) | 0.063461 / 0.038508 (0.024953) | 0.062770 / 0.023109 (0.039660) | 0.448786 / 0.275898 (0.172888) | 0.486490 / 0.323480 (0.163010) | 0.005527 / 0.007986 (-0.002458) | 0.002860 / 0.004328 (-0.001469) | 0.063803 / 0.004250 (0.059553) | 0.049657 / 0.037052 (0.012604) | 0.449625 / 0.258489 (0.191136) | 0.489378 / 0.293841 (0.195537) | 0.028406 / 0.128546 (-0.100140) | 0.008062 / 0.075646 (-0.067584) | 0.068417 / 0.419271 (-0.350854) | 0.040854 / 0.043533 (-0.002678) | 0.461670 / 0.255139 (0.206531) | 0.481622 / 0.283200 (0.198423) | 0.021018 / 0.141683 (-0.120665) | 1.450328 / 1.452155 (-0.001826) | 1.501283 / 1.492716 (0.008567) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269824 / 0.018006 (0.251817) | 0.412296 / 0.000490 (0.411807) | 0.039582 / 0.000200 (0.039382) | 0.000266 / 0.000054 (0.000211) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026436 / 0.037411 (-0.010976) | 0.080633 / 0.014526 (0.066107) | 0.089786 / 0.176557 (-0.086770) | 0.145020 / 0.737135 (-0.592115) | 0.092327 / 0.296338 (-0.204012) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.464349 / 0.215209 (0.249140) | 4.630631 / 2.077655 (2.552976) | 2.560527 / 1.504120 (1.056407) | 2.374195 / 1.541195 (0.833000) | 2.424774 / 1.468490 (0.956284) | 0.510428 / 4.584777 (-4.074349) | 3.099805 / 3.745712 (-0.645907) | 2.781096 / 5.269862 (-2.488765) | 1.854276 / 4.565676 (-2.711400) | 0.058102 / 0.424275 (-0.366173) | 0.006365 / 0.007607 (-0.001242) | 0.534082 / 0.226044 (0.308038) | 5.355003 / 2.268929 (3.086074) | 3.012546 / 55.444624 (-52.432078) | 2.665222 / 6.876477 (-4.211255) | 2.821014 / 2.142072 (0.678942) | 0.597733 / 4.805227 (-4.207494) | 0.125433 / 6.500664 (-6.375231) | 0.060802 / 0.075469 (-0.014667) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345699 / 1.841788 (-0.496088) | 18.836083 / 8.074308 (10.761774) | 14.895458 / 10.191392 (4.704066) | 0.146843 / 0.680424 (-0.533581) | 0.018082 / 0.534201 (-0.516119) | 0.335729 / 0.579283 (-0.243554) | 0.351013 / 0.434364 (-0.083351) | 0.388435 / 0.540337 (-0.151902) | 0.543826 / 1.386936 (-0.843110) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d0c7e8c4808a1fb6ee7234b4caa25aa9fcfdc88f \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006593 / 0.011353 (-0.004760) | 0.004089 / 0.011008 (-0.006919) | 0.084753 / 0.038508 (0.046245) | 0.079899 / 0.023109 (0.056790) | 0.311528 / 0.275898 (0.035630) | 0.349722 / 0.323480 (0.026243) | 0.004288 / 0.007986 (-0.003698) | 0.004552 / 0.004328 (0.000224) | 0.065896 / 0.004250 (0.061646) | 0.053813 / 0.037052 (0.016760) | 0.316958 / 0.258489 (0.058469) | 0.367011 / 0.293841 (0.073170) | 0.031082 / 0.128546 (-0.097464) | 0.008684 / 0.075646 (-0.066963) | 0.288003 / 0.419271 (-0.131268) | 0.052560 / 0.043533 (0.009027) | 0.305589 / 0.255139 (0.050450) | 0.349656 / 0.283200 (0.066457) | 0.023857 / 0.141683 (-0.117826) | 1.462360 / 1.452155 (0.010205) | 1.568170 / 1.492716 (0.075454) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.272342 / 0.018006 (0.254336) | 0.585108 / 0.000490 (0.584618) | 0.003427 / 0.000200 (0.003227) | 0.000078 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030347 / 0.037411 (-0.007064) | 0.086325 / 0.014526 (0.071799) | 0.100958 / 0.176557 (-0.075598) | 0.156534 / 0.737135 (-0.580601) | 0.102506 / 0.296338 (-0.193832) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.406625 / 0.215209 (0.191416) | 4.065957 / 2.077655 (1.988302) | 2.075867 / 1.504120 (0.571747) | 1.914390 / 1.541195 (0.373196) | 2.013321 / 1.468490 (0.544831) | 0.486832 / 4.584777 (-4.097945) | 3.545940 / 3.745712 (-0.199772) | 3.323226 / 5.269862 (-1.946635) | 2.067742 / 4.565676 (-2.497934) | 0.057884 / 0.424275 (-0.366391) | 0.007751 / 0.007607 (0.000144) | 0.484923 / 0.226044 (0.258878) | 4.844885 / 2.268929 (2.575956) | 2.569828 / 55.444624 (-52.874796) | 2.224058 / 6.876477 (-4.652419) | 2.485587 / 2.142072 (0.343515) | 0.584311 / 4.805227 (-4.220916) | 0.134984 / 6.500664 (-6.365680) | 0.062164 / 0.075469 (-0.013305) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.247182 / 1.841788 (-0.594605) | 20.107500 / 8.074308 (12.033192) | 14.194444 / 10.191392 (4.003052) | 0.147134 / 0.680424 (-0.533290) | 0.018062 / 0.534201 (-0.516138) | 0.392029 / 0.579283 (-0.187254) | 0.402991 / 0.434364 (-0.031373) | 0.457600 / 0.540337 (-0.082737) | 0.632553 / 1.386936 (-0.754383) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006920 / 0.011353 (-0.004433) | 0.004257 / 0.011008 (-0.006751) | 0.065233 / 0.038508 (0.026725) | 0.078151 / 0.023109 (0.055042) | 0.389141 / 0.275898 (0.113243) | 0.431518 / 0.323480 (0.108038) | 0.005752 / 0.007986 (-0.002234) | 0.003584 / 0.004328 (-0.000745) | 0.065173 / 0.004250 (0.060922) | 0.059113 / 0.037052 (0.022060) | 0.398225 / 0.258489 (0.139736) | 0.430980 / 0.293841 (0.137139) | 0.032802 / 0.128546 (-0.095744) | 0.008702 / 0.075646 (-0.066945) | 0.071345 / 0.419271 (-0.347926) | 0.048269 / 0.043533 (0.004736) | 0.389264 / 0.255139 (0.134125) | 0.416008 / 0.283200 (0.132809) | 0.024845 / 0.141683 (-0.116838) | 1.499100 / 1.452155 (0.046945) | 1.576397 / 1.492716 (0.083681) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296674 / 0.018006 (0.278668) | 0.540108 / 0.000490 (0.539619) | 0.004293 / 0.000200 (0.004093) | 0.000151 / 0.000054 (0.000096) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034108 / 0.037411 (-0.003303) | 0.092747 / 0.014526 (0.078221) | 0.112203 / 0.176557 (-0.064354) | 0.162728 / 0.737135 (-0.574407) | 0.109955 / 0.296338 (-0.186383) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.432006 / 0.215209 (0.216797) | 4.297591 / 2.077655 (2.219937) | 2.379645 / 1.504120 (0.875525) | 2.218680 / 1.541195 (0.677485) | 2.314608 / 1.468490 (0.846117) | 0.495562 / 4.584777 (-4.089215) | 3.589787 / 3.745712 (-0.155925) | 3.349593 / 5.269862 (-1.920268) | 2.119893 / 4.565676 (-2.445783) | 0.057976 / 0.424275 (-0.366299) | 0.007612 / 0.007607 (0.000005) | 0.509422 / 0.226044 (0.283378) | 5.101444 / 2.268929 (2.832515) | 2.794532 / 55.444624 (-52.650092) | 2.459033 / 6.876477 (-4.417444) | 2.714424 / 2.142072 (0.572352) | 0.588444 / 4.805227 (-4.216784) | 0.135763 / 6.500664 (-6.364901) | 0.062593 / 0.075469 (-0.012876) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.361415 / 1.841788 (-0.480372) | 20.940684 / 8.074308 (12.866376) | 15.161364 / 10.191392 (4.969972) | 0.154243 / 0.680424 (-0.526181) | 0.020305 / 0.534201 (-0.513896) | 0.397438 / 0.579283 (-0.181845) | 0.415047 / 0.434364 (-0.019317) | 0.473250 / 0.540337 (-0.067088) | 0.740681 / 1.386936 (-0.646255) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6e84937af4f24194bf61f09244ebef6528fb7c4c \"CML watermark\")\n" ]

"2023-08-23T15:45:53Z"

"2023-08-24T12:37:41Z"

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"2023-08-23T14:11:20Z"

"2023-08-23T14:45:42Z"

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[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]

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[ "Hi! The streaming mode also retries requests - `datasets.config.STREAMING_READ_MAX_RETRIES` (20 sec by default) controls the number of retries and `datasets.config.STREAMING_READ_RETRY_INTERVAL` (5 sec) the sleep time between retries.\r\n\r\n> At step 1800 I got a 504 HTTP status code error from Huggingface hub for my pytorch dataloader\r\n\r\nA minor Hub outage that we experienced yesterday could be the cause." ]

"2023-08-23T13:15:38Z"

"2023-08-24T14:29:27Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6171). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009315 / 0.011353 (-0.002038) | 0.004931 / 0.011008 (-0.006077) | 0.100534 / 0.038508 (0.062026) | 0.089270 / 0.023109 (0.066161) | 0.394995 / 0.275898 (0.119097) | 0.440244 / 0.323480 (0.116764) | 0.006026 / 0.007986 (-0.001959) | 0.004252 / 0.004328 (-0.000077) | 0.078828 / 0.004250 (0.074577) | 0.066770 / 0.037052 (0.029718) | 0.411152 / 0.258489 (0.152663) | 0.445616 / 0.293841 (0.151775) | 0.048344 / 0.128546 (-0.080203) | 0.013700 / 0.075646 (-0.061946) | 0.361205 / 0.419271 (-0.058066) | 0.072085 / 0.043533 (0.028552) | 0.399173 / 0.255139 (0.144034) | 0.439334 / 0.283200 (0.156134) | 0.035815 / 0.141683 (-0.105868) | 1.779023 / 1.452155 (0.326868) | 1.865099 / 1.492716 (0.372383) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.275978 / 0.018006 (0.257972) | 0.588850 / 0.000490 (0.588360) | 0.004953 / 0.000200 (0.004754) | 0.000109 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031329 / 0.037411 (-0.006082) | 0.095435 / 0.014526 (0.080910) | 0.111182 / 0.176557 (-0.065375) | 0.177692 / 0.737135 (-0.559444) | 0.113345 / 0.296338 (-0.182993) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.577882 / 0.215209 (0.362673) | 5.865872 / 2.077655 (3.788217) | 2.664218 / 1.504120 (1.160098) | 2.383354 / 1.541195 (0.842159) | 2.336821 / 1.468490 (0.868331) | 0.834585 / 4.584777 (-3.750192) | 5.418720 / 3.745712 (1.673008) | 4.551790 / 5.269862 (-0.718072) | 2.921874 / 4.565676 (-1.643803) | 0.095738 / 0.424275 (-0.328537) | 0.009625 / 0.007607 (0.002018) | 0.688317 / 0.226044 (0.462273) | 6.831826 / 2.268929 (4.562897) | 3.482607 / 55.444624 (-51.962017) | 2.633482 / 6.876477 (-4.242995) | 2.878786 / 2.142072 (0.736714) | 0.971615 / 4.805227 (-3.833613) | 0.208661 / 6.500664 (-6.292003) | 0.080271 / 0.075469 (0.004802) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.661193 / 1.841788 (-0.180594) | 24.223041 / 8.074308 (16.148733) | 21.621791 / 10.191392 (11.430399) | 0.243809 / 0.680424 (-0.436614) | 0.031630 / 0.534201 (-0.502571) | 0.501408 / 0.579283 (-0.077875) | 0.600002 / 0.434364 (0.165638) | 0.572066 / 0.540337 (0.031728) | 0.791992 / 1.386936 (-0.594944) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009410 / 0.011353 (-0.001943) | 0.005255 / 0.011008 (-0.005753) | 0.079202 / 0.038508 (0.040693) | 0.078973 / 0.023109 (0.055863) | 0.557416 / 0.275898 (0.281518) | 0.560417 / 0.323480 (0.236937) | 0.007066 / 0.007986 (-0.000920) | 0.004560 / 0.004328 (0.000232) | 0.080359 / 0.004250 (0.076109) | 0.060071 / 0.037052 (0.023019) | 0.538441 / 0.258489 (0.279952) | 0.592486 / 0.293841 (0.298645) | 0.053221 / 0.128546 (-0.075325) | 0.014056 / 0.075646 (-0.061591) | 0.094084 / 0.419271 (-0.325188) | 0.066721 / 0.043533 (0.023188) | 0.521873 / 0.255139 (0.266734) | 0.579637 / 0.283200 (0.296437) | 0.041476 / 0.141683 (-0.100206) | 1.829681 / 1.452155 (0.377527) | 1.948418 / 1.492716 (0.455702) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.347594 / 0.018006 (0.329588) | 0.606906 / 0.000490 (0.606417) | 0.035413 / 0.000200 (0.035213) | 0.000371 / 0.000054 (0.000317) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031987 / 0.037411 (-0.005425) | 0.096985 / 0.014526 (0.082459) | 0.109275 / 0.176557 (-0.067282) | 0.175340 / 0.737135 (-0.561795) | 0.110763 / 0.296338 (-0.185575) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.634823 / 0.215209 (0.419614) | 6.527172 / 2.077655 (4.449517) | 3.135709 / 1.504120 (1.631589) | 2.634357 / 1.541195 (1.093162) | 2.670583 / 1.468490 (1.202093) | 0.888686 / 4.584777 (-3.696091) | 5.382289 / 3.745712 (1.636577) | 4.701189 / 5.269862 (-0.568673) | 3.161290 / 4.565676 (-1.404386) | 0.112414 / 0.424275 (-0.311861) | 0.009443 / 0.007607 (0.001836) | 0.774703 / 0.226044 (0.548658) | 7.905334 / 2.268929 (5.636405) | 3.689548 / 55.444624 (-51.755076) | 3.087263 / 6.876477 (-3.789214) | 3.366568 / 2.142072 (1.224496) | 1.185951 / 4.805227 (-3.619277) | 0.248638 / 6.500664 (-6.252026) | 0.104598 / 0.075469 (0.029129) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.820667 / 1.841788 (-0.021120) | 24.536703 / 8.074308 (16.462395) | 23.083964 / 10.191392 (12.892572) | 0.252897 / 0.680424 (-0.427527) | 0.032954 / 0.534201 (-0.501247) | 0.482467 / 0.579283 (-0.096816) | 0.602247 / 0.434364 (0.167883) | 0.600563 / 0.540337 (0.060225) | 0.824013 / 1.386936 (-0.562923) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c07a54ed4d570c5842d7bbe467025805be16ef51 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009242 / 0.011353 (-0.002111) | 0.005244 / 0.011008 (-0.005764) | 0.112678 / 0.038508 (0.074170) | 0.089176 / 0.023109 (0.066067) | 0.405823 / 0.275898 (0.129925) | 0.465703 / 0.323480 (0.142223) | 0.005227 / 0.007986 (-0.002758) | 0.004296 / 0.004328 (-0.000032) | 0.082961 / 0.004250 (0.078711) | 0.063144 / 0.037052 (0.026092) | 0.422369 / 0.258489 (0.163880) | 0.478185 / 0.293841 (0.184344) | 0.049770 / 0.128546 (-0.078776) | 0.016561 / 0.075646 (-0.059086) | 0.380172 / 0.419271 (-0.039100) | 0.068698 / 0.043533 (0.025165) | 0.397773 / 0.255139 (0.142634) | 0.461284 / 0.283200 (0.178084) | 0.036907 / 0.141683 (-0.104775) | 1.828017 / 1.452155 (0.375862) | 2.028385 / 1.492716 (0.535669) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.291245 / 0.018006 (0.273239) | 0.605519 / 0.000490 (0.605030) | 0.003790 / 0.000200 (0.003590) | 0.000094 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029269 / 0.037411 (-0.008142) | 0.087014 / 0.014526 (0.072488) | 0.116984 / 0.176557 (-0.059573) | 0.170644 / 0.737135 (-0.566491) | 0.109011 / 0.296338 (-0.187328) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.603045 / 0.215209 (0.387836) | 6.125308 / 2.077655 (4.047653) | 2.637127 / 1.504120 (1.133007) | 2.468636 / 1.541195 (0.927441) | 2.383773 / 1.468490 (0.915283) | 0.838139 / 4.584777 (-3.746638) | 5.355777 / 3.745712 (1.610065) | 4.753015 / 5.269862 (-0.516846) | 3.097486 / 4.565676 (-1.468191) | 0.094749 / 0.424275 (-0.329526) | 0.009040 / 0.007607 (0.001433) | 0.699987 / 0.226044 (0.473942) | 7.111671 / 2.268929 (4.842742) | 3.297798 / 55.444624 (-52.146827) | 2.614578 / 6.876477 (-4.261898) | 2.927717 / 2.142072 (0.785645) | 1.037292 / 4.805227 (-3.767935) | 0.218025 / 6.500664 (-6.282639) | 0.086306 / 0.075469 (0.010836) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.645146 / 1.841788 (-0.196642) | 24.191875 / 8.074308 (16.117567) | 21.844371 / 10.191392 (11.652979) | 0.245369 / 0.680424 (-0.435055) | 0.031776 / 0.534201 (-0.502425) | 0.465634 / 0.579283 (-0.113649) | 0.565498 / 0.434364 (0.131134) | 0.497409 / 0.540337 (-0.042929) | 0.748048 / 1.386936 (-0.638889) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009239 / 0.011353 (-0.002114) | 0.005345 / 0.011008 (-0.005663) | 0.072732 / 0.038508 (0.034224) | 0.099880 / 0.023109 (0.076770) | 0.466933 / 0.275898 (0.191035) | 0.471730 / 0.323480 (0.148250) | 0.006164 / 0.007986 (-0.001821) | 0.004486 / 0.004328 (0.000158) | 0.075475 / 0.004250 (0.071224) | 0.068291 / 0.037052 (0.031238) | 0.465925 / 0.258489 (0.207436) | 0.469198 / 0.293841 (0.175357) | 0.047304 / 0.128546 (-0.081242) | 0.013368 / 0.075646 (-0.062278) | 0.083563 / 0.419271 (-0.335708) | 0.063204 / 0.043533 (0.019671) | 0.457422 / 0.255139 (0.202283) | 0.478793 / 0.283200 (0.195593) | 0.036120 / 0.141683 (-0.105563) | 1.841209 / 1.452155 (0.389054) | 1.955984 / 1.492716 (0.463267) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.369160 / 0.018006 (0.351154) | 0.607140 / 0.000490 (0.606650) | 0.047253 / 0.000200 (0.047054) | 0.000475 / 0.000054 (0.000420) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.040226 / 0.037411 (0.002815) | 0.107361 / 0.014526 (0.092835) | 0.122424 / 0.176557 (-0.054133) | 0.186447 / 0.737135 (-0.550688) | 0.127060 / 0.296338 (-0.169279) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.706737 / 0.215209 (0.491528) | 6.791287 / 2.077655 (4.713632) | 3.194471 / 1.504120 (1.690352) | 2.928145 / 1.541195 (1.386950) | 2.829078 / 1.468490 (1.360588) | 0.929797 / 4.584777 (-3.654980) | 5.484638 / 3.745712 (1.738926) | 4.841570 / 5.269862 (-0.428292) | 2.995247 / 4.565676 (-1.570430) | 0.104709 / 0.424275 (-0.319566) | 0.009543 / 0.007607 (0.001936) | 0.817605 / 0.226044 (0.591561) | 7.879234 / 2.268929 (5.610305) | 3.838073 / 55.444624 (-51.606551) | 3.189728 / 6.876477 (-3.686749) | 3.483775 / 2.142072 (1.341703) | 1.092823 / 4.805227 (-3.712404) | 0.227660 / 6.500664 (-6.273004) | 0.082452 / 0.075469 (0.006983) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.750413 / 1.841788 (-0.091374) | 27.078082 / 8.074308 (19.003774) | 23.968038 / 10.191392 (13.776646) | 0.248065 / 0.680424 (-0.432359) | 0.029961 / 0.534201 (-0.504240) | 0.508630 / 0.579283 (-0.070653) | 0.608707 / 0.434364 (0.174343) | 0.611062 / 0.540337 (0.070725) | 0.830797 / 1.386936 (-0.556139) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9d793220dd8cbaa099a3928c2132c94c9f7453bc \"CML watermark\")\n" ]

"2023-08-23T09:21:11Z"

"2023-08-23T09:32:59Z"

"2023-08-23T09:21:19Z"

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"2023-08-23T07:08:17Z"

"2023-08-23T07:09:48Z"

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[ "Unfortunately, I cannot reproduce this behavior on my machine or Colab - the reproducer returns `['main_data', 'additional_data']` as expected.", "Thank you for looking into this, Mario. Is this on [my repository](https://huggingface.co/datasets/tsor13/test), or on another one that you have reproduced? Would you mind pointing me to it if so?", "Whoa, in colab I received the correct behavior using my dataset. It must have something to do with my local copy of `datasets` (which again just failed).\r\n\r\nI've tried uninstalling/reinstnalling to no avail", "hi @tsor13 , I haven't been able to reproduce your issue on `tsor13/test` dataset locally either. reinstalling doesn't help?" ]

"2023-08-23T00:13:22Z"

"2023-08-23T15:35:31Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6168). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009350 / 0.011353 (-0.002003) | 0.005658 / 0.011008 (-0.005350) | 0.123173 / 0.038508 (0.084664) | 0.096354 / 0.023109 (0.073244) | 0.464398 / 0.275898 (0.188500) | 0.544455 / 0.323480 (0.220975) | 0.007337 / 0.007986 (-0.000648) | 0.004424 / 0.004328 (0.000096) | 0.089715 / 0.004250 (0.085465) | 0.072462 / 0.037052 (0.035410) | 0.460601 / 0.258489 (0.202112) | 0.544384 / 0.293841 (0.250543) | 0.052994 / 0.128546 (-0.075552) | 0.014459 / 0.075646 (-0.061187) | 0.464368 / 0.419271 (0.045096) | 0.072889 / 0.043533 (0.029356) | 0.471387 / 0.255139 (0.216248) | 0.560982 / 0.283200 (0.277783) | 0.041398 / 0.141683 (-0.100285) | 1.964688 / 1.452155 (0.512533) | 2.240727 / 1.492716 (0.748011) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.308524 / 0.018006 (0.290518) | 0.669306 / 0.000490 (0.668816) | 0.006644 / 0.000200 (0.006444) | 0.000108 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037395 / 0.037411 (-0.000016) | 0.111303 / 0.014526 (0.096777) | 0.158988 / 0.176557 (-0.017569) | 0.236155 / 0.737135 (-0.500980) | 0.134775 / 0.296338 (-0.161564) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.648830 / 0.215209 (0.433621) | 6.614794 / 2.077655 (4.537139) | 2.867526 / 1.504120 (1.363407) | 2.472967 / 1.541195 (0.931772) | 2.488419 / 1.468490 (1.019929) | 0.915785 / 4.584777 (-3.668992) | 6.010754 / 3.745712 (2.265042) | 5.468873 / 5.269862 (0.199011) | 3.446535 / 4.565676 (-1.119141) | 0.118592 / 0.424275 (-0.305684) | 0.012005 / 0.007607 (0.004398) | 0.808467 / 0.226044 (0.582423) | 8.152122 / 2.268929 (5.883193) | 3.751282 / 55.444624 (-51.693342) | 3.009569 / 6.876477 (-3.866908) | 3.282613 / 2.142072 (1.140540) | 1.152727 / 4.805227 (-3.652500) | 0.240224 / 6.500664 (-6.260440) | 0.097871 / 0.075469 (0.022402) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.824944 / 1.841788 (-0.016843) | 27.840842 / 8.074308 (19.766533) | 24.368669 / 10.191392 (14.177277) | 0.260621 / 0.680424 (-0.419803) | 0.033730 / 0.534201 (-0.500471) | 0.552494 / 0.579283 (-0.026789) | 0.666921 / 0.434364 (0.232557) | 0.648812 / 0.540337 (0.108475) | 0.912602 / 1.386936 (-0.474334) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011688 / 0.011353 (0.000335) | 0.005794 / 0.011008 (-0.005215) | 0.093466 / 0.038508 (0.054958) | 0.102583 / 0.023109 (0.079474) | 0.593572 / 0.275898 (0.317674) | 0.614351 / 0.323480 (0.290871) | 0.007006 / 0.007986 (-0.000980) | 0.005557 / 0.004328 (0.001229) | 0.087779 / 0.004250 (0.083529) | 0.072639 / 0.037052 (0.035586) | 0.577464 / 0.258489 (0.318975) | 0.628240 / 0.293841 (0.334399) | 0.053876 / 0.128546 (-0.074670) | 0.015383 / 0.075646 (-0.060263) | 0.110633 / 0.419271 (-0.308639) | 0.067467 / 0.043533 (0.023934) | 0.613457 / 0.255139 (0.358318) | 0.604939 / 0.283200 (0.321739) | 0.041738 / 0.141683 (-0.099945) | 1.967167 / 1.452155 (0.515012) | 2.121009 / 1.492716 (0.628293) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.449937 / 0.018006 (0.431930) | 0.694410 / 0.000490 (0.693921) | 0.064051 / 0.000200 (0.063851) | 0.000810 / 0.000054 (0.000756) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.045138 / 0.037411 (0.007727) | 0.116831 / 0.014526 (0.102306) | 0.131906 / 0.176557 (-0.044651) | 0.202421 / 0.737135 (-0.534714) | 0.132568 / 0.296338 (-0.163770) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.698046 / 0.215209 (0.482837) | 7.112591 / 2.077655 (5.034936) | 3.332679 / 1.504120 (1.828559) | 2.946384 / 1.541195 (1.405189) | 3.074484 / 1.468490 (1.605994) | 0.970917 / 4.584777 (-3.613859) | 6.143506 / 3.745712 (2.397794) | 5.572496 / 5.269862 (0.302634) | 3.602673 / 4.565676 (-0.963004) | 0.115068 / 0.424275 (-0.309207) | 0.009971 / 0.007607 (0.002364) | 0.891090 / 0.226044 (0.665046) | 8.761788 / 2.268929 (6.492859) | 4.362685 / 55.444624 (-51.081939) | 3.612893 / 6.876477 (-3.263583) | 3.797948 / 2.142072 (1.655876) | 1.202890 / 4.805227 (-3.602337) | 0.238120 / 6.500664 (-6.262544) | 0.095612 / 0.075469 (0.020143) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.958880 / 1.841788 (0.117092) | 28.216454 / 8.074308 (20.142146) | 25.361424 / 10.191392 (15.170032) | 0.308203 / 0.680424 (-0.372221) | 0.032903 / 0.534201 (-0.501298) | 0.539714 / 0.579283 (-0.039569) | 0.688278 / 0.434364 (0.253914) | 0.644818 / 0.540337 (0.104481) | 0.905694 / 1.386936 (-0.481242) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a5289345e5b23548fee680a0bbc047c0b9a5ee8c \"CML watermark\")\n" ]

"2023-08-22T17:02:54Z"

"2023-08-22T17:14:15Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007342 / 0.011353 (-0.004011) | 0.004586 / 0.011008 (-0.006422) | 0.100430 / 0.038508 (0.061922) | 0.081053 / 0.023109 (0.057944) | 0.368130 / 0.275898 (0.092232) | 0.402852 / 0.323480 (0.079372) | 0.004504 / 0.007986 (-0.003482) | 0.003824 / 0.004328 (-0.000505) | 0.075326 / 0.004250 (0.071076) | 0.063329 / 0.037052 (0.026277) | 0.372837 / 0.258489 (0.114348) | 0.437857 / 0.293841 (0.144017) | 0.035512 / 0.128546 (-0.093034) | 0.009756 / 0.075646 (-0.065890) | 0.341035 / 0.419271 (-0.078236) | 0.060503 / 0.043533 (0.016970) | 0.362555 / 0.255139 (0.107416) | 0.409216 / 0.283200 (0.126017) | 0.030093 / 0.141683 (-0.111590) | 1.751550 / 1.452155 (0.299395) | 1.848676 / 1.492716 (0.355959) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229448 / 0.018006 (0.211442) | 0.500300 / 0.000490 (0.499811) | 0.005195 / 0.000200 (0.004995) | 0.000092 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031753 / 0.037411 (-0.005658) | 0.096075 / 0.014526 (0.081549) | 0.111476 / 0.176557 (-0.065081) | 0.179236 / 0.737135 (-0.557899) | 0.113599 / 0.296338 (-0.182739) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.472817 / 0.215209 (0.257608) | 4.715029 / 2.077655 (2.637374) | 2.417934 / 1.504120 (0.913814) | 2.235014 / 1.541195 (0.693819) | 2.323588 / 1.468490 (0.855098) | 0.553751 / 4.584777 (-4.031026) | 4.153467 / 3.745712 (0.407755) | 3.858836 / 5.269862 (-1.411025) | 2.377499 / 4.565676 (-2.188178) | 0.066528 / 0.424275 (-0.357747) | 0.008979 / 0.007607 (0.001372) | 0.561076 / 0.226044 (0.335032) | 5.609817 / 2.268929 (3.340888) | 3.011098 / 55.444624 (-52.433526) | 2.594162 / 6.876477 (-4.282314) | 2.863597 / 2.142072 (0.721525) | 0.681135 / 4.805227 (-4.124092) | 0.158863 / 6.500664 (-6.341801) | 0.072551 / 0.075469 (-0.002918) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.492230 / 1.841788 (-0.349558) | 23.028828 / 8.074308 (14.954519) | 16.663265 / 10.191392 (6.471873) | 0.173146 / 0.680424 (-0.507278) | 0.021635 / 0.534201 (-0.512566) | 0.478919 / 0.579283 (-0.100364) | 0.472908 / 0.434364 (0.038544) | 0.547248 / 0.540337 (0.006910) | 0.770288 / 1.386936 (-0.616648) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007728 / 0.011353 (-0.003625) | 0.004477 / 0.011008 (-0.006531) | 0.074858 / 0.038508 (0.036350) | 0.084266 / 0.023109 (0.061157) | 0.420280 / 0.275898 (0.144382) | 0.466835 / 0.323480 (0.143356) | 0.005980 / 0.007986 (-0.002006) | 0.003600 / 0.004328 (-0.000729) | 0.074941 / 0.004250 (0.070691) | 0.066414 / 0.037052 (0.029361) | 0.425949 / 0.258489 (0.167460) | 0.473236 / 0.293841 (0.179395) | 0.037213 / 0.128546 (-0.091333) | 0.009743 / 0.075646 (-0.065903) | 0.083758 / 0.419271 (-0.335513) | 0.057916 / 0.043533 (0.014383) | 0.423031 / 0.255139 (0.167892) | 0.451107 / 0.283200 (0.167907) | 0.028577 / 0.141683 (-0.113106) | 1.810509 / 1.452155 (0.358354) | 1.875579 / 1.492716 (0.382863) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296052 / 0.018006 (0.278046) | 0.496618 / 0.000490 (0.496128) | 0.028667 / 0.000200 (0.028467) | 0.000140 / 0.000054 (0.000086) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036694 / 0.037411 (-0.000717) | 0.110873 / 0.014526 (0.096347) | 0.126550 / 0.176557 (-0.050007) | 0.182924 / 0.737135 (-0.554212) | 0.123793 / 0.296338 (-0.172545) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.509881 / 0.215209 (0.294672) | 5.067402 / 2.077655 (2.989747) | 2.696028 / 1.504120 (1.191908) | 2.489861 / 1.541195 (0.948666) | 2.563400 / 1.468490 (1.094910) | 0.571184 / 4.584777 (-4.013593) | 4.154231 / 3.745712 (0.408519) | 3.891004 / 5.269862 (-1.378858) | 2.435290 / 4.565676 (-2.130387) | 0.065825 / 0.424275 (-0.358450) | 0.008460 / 0.007607 (0.000853) | 0.597579 / 0.226044 (0.371534) | 5.914954 / 2.268929 (3.646025) | 3.219305 / 55.444624 (-52.225319) | 2.843548 / 6.876477 (-4.032929) | 3.070300 / 2.142072 (0.928228) | 0.686018 / 4.805227 (-4.119209) | 0.160077 / 6.500664 (-6.340587) | 0.074058 / 0.075469 (-0.001411) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.598748 / 1.841788 (-0.243039) | 23.475685 / 8.074308 (15.401377) | 17.257831 / 10.191392 (7.066439) | 0.176539 / 0.680424 (-0.503885) | 0.021969 / 0.534201 (-0.512232) | 0.473565 / 0.579283 (-0.105718) | 0.465471 / 0.434364 (0.031107) | 0.567107 / 0.540337 (0.026769) | 0.783757 / 1.386936 (-0.603179) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2f6bb450b4a3065a7d5fc50ea67711082749a337 \"CML watermark\")\n", "Note that the https://github.com/huggingface/datasets-server/ explicitly relies on the fact that a split cannot contain a hyphen. cc @lhoestq ", "We can't enable this that easily unfortunately because it could make arrow file names ambiguous in the cache.\r\n\r\ne.g. dataset_name-train-0000-of-0008.arrow", "Oh, this would indeed make the caching for the multi-proc case ambiguous. Implementing this is only worth it if we get more requests, so I'm closing this PR for now." ]

"2023-08-22T13:30:59Z"

"2023-08-22T15:39:24Z"

"2023-08-22T15:38:53Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009036 / 0.011353 (-0.002317) | 0.004564 / 0.011008 (-0.006444) | 0.114958 / 0.038508 (0.076449) | 0.087329 / 0.023109 (0.064220) | 0.440111 / 0.275898 (0.164213) | 0.486056 / 0.323480 (0.162576) | 0.006580 / 0.007986 (-0.001406) | 0.004257 / 0.004328 (-0.000072) | 0.093458 / 0.004250 (0.089208) | 0.063380 / 0.037052 (0.026328) | 0.469455 / 0.258489 (0.210966) | 0.521630 / 0.293841 (0.227790) | 0.053496 / 0.128546 (-0.075050) | 0.013466 / 0.075646 (-0.062181) | 0.361629 / 0.419271 (-0.057642) | 0.068095 / 0.043533 (0.024562) | 0.472440 / 0.255139 (0.217301) | 0.508682 / 0.283200 (0.225483) | 0.034648 / 0.141683 (-0.107035) | 1.820117 / 1.452155 (0.367962) | 1.933448 / 1.492716 (0.440732) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.276543 / 0.018006 (0.258537) | 0.563380 / 0.000490 (0.562890) | 0.005345 / 0.000200 (0.005146) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029230 / 0.037411 (-0.008181) | 0.095613 / 0.014526 (0.081087) | 0.106178 / 0.176557 (-0.070378) | 0.181095 / 0.737135 (-0.556040) | 0.107789 / 0.296338 (-0.188550) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.612051 / 0.215209 (0.396842) | 6.065008 / 2.077655 (3.987353) | 2.720911 / 1.504120 (1.216791) | 2.495218 / 1.541195 (0.954023) | 2.423351 / 1.468490 (0.954860) | 0.835571 / 4.584777 (-3.749205) | 5.438230 / 3.745712 (1.692518) | 4.550301 / 5.269862 (-0.719561) | 2.919889 / 4.565676 (-1.645788) | 0.097748 / 0.424275 (-0.326527) | 0.009285 / 0.007607 (0.001678) | 0.741968 / 0.226044 (0.515923) | 7.285394 / 2.268929 (5.016466) | 3.433634 / 55.444624 (-52.010991) | 2.680823 / 6.876477 (-4.195654) | 2.931149 / 2.142072 (0.789076) | 1.012852 / 4.805227 (-3.792375) | 0.224899 / 6.500664 (-6.275765) | 0.089411 / 0.075469 (0.013942) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.622759 / 1.841788 (-0.219029) | 23.690030 / 8.074308 (15.615721) | 21.034451 / 10.191392 (10.843059) | 0.241504 / 0.680424 (-0.438920) | 0.030109 / 0.534201 (-0.504092) | 0.472536 / 0.579283 (-0.106747) | 0.631396 / 0.434364 (0.197032) | 0.598997 / 0.540337 (0.058659) | 0.798680 / 1.386936 (-0.588256) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008696 / 0.011353 (-0.002657) | 0.005032 / 0.011008 (-0.005977) | 0.087369 / 0.038508 (0.048861) | 0.078105 / 0.023109 (0.054996) | 0.464861 / 0.275898 (0.188963) | 0.509620 / 0.323480 (0.186140) | 0.006399 / 0.007986 (-0.001587) | 0.004276 / 0.004328 (-0.000052) | 0.081643 / 0.004250 (0.077393) | 0.062560 / 0.037052 (0.025508) | 0.495377 / 0.258489 (0.236888) | 0.484885 / 0.293841 (0.191044) | 0.054354 / 0.128546 (-0.074193) | 0.013851 / 0.075646 (-0.061795) | 0.089531 / 0.419271 (-0.329740) | 0.068732 / 0.043533 (0.025199) | 0.455842 / 0.255139 (0.200703) | 0.528775 / 0.283200 (0.245575) | 0.039646 / 0.141683 (-0.102037) | 1.733600 / 1.452155 (0.281445) | 1.879074 / 1.492716 (0.386358) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.369616 / 0.018006 (0.351610) | 0.607426 / 0.000490 (0.606936) | 0.055540 / 0.000200 (0.055341) | 0.000543 / 0.000054 (0.000488) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036026 / 0.037411 (-0.001385) | 0.103968 / 0.014526 (0.089442) | 0.114852 / 0.176557 (-0.061705) | 0.187313 / 0.737135 (-0.549822) | 0.116839 / 0.296338 (-0.179500) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.614018 / 0.215209 (0.398809) | 6.139914 / 2.077655 (4.062259) | 2.826246 / 1.504120 (1.322126) | 2.524133 / 1.541195 (0.982938) | 2.606981 / 1.468490 (1.138491) | 0.844604 / 4.584777 (-3.740173) | 5.537178 / 3.745712 (1.791465) | 4.594624 / 5.269862 (-0.675237) | 3.032145 / 4.565676 (-1.533532) | 0.094771 / 0.424275 (-0.329504) | 0.008132 / 0.007607 (0.000525) | 0.714287 / 0.226044 (0.488242) | 7.296733 / 2.268929 (5.027804) | 3.698066 / 55.444624 (-51.746558) | 2.862781 / 6.876477 (-4.013696) | 3.114502 / 2.142072 (0.972429) | 0.986612 / 4.805227 (-3.818616) | 0.214438 / 6.500664 (-6.286226) | 0.076201 / 0.075469 (0.000732) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.747728 / 1.841788 (-0.094060) | 24.159845 / 8.074308 (16.085537) | 23.553485 / 10.191392 (13.362093) | 0.248387 / 0.680424 (-0.432037) | 0.029850 / 0.534201 (-0.504351) | 0.526416 / 0.579283 (-0.052867) | 0.625681 / 0.434364 (0.191317) | 0.619690 / 0.540337 (0.079352) | 0.827485 / 1.386936 (-0.559451) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#75639f9064dab9549add79fd5ee7de2a4429992c \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006728 / 0.011353 (-0.004625) | 0.003960 / 0.011008 (-0.007048) | 0.085569 / 0.038508 (0.047061) | 0.077463 / 0.023109 (0.054354) | 0.343112 / 0.275898 (0.067214) | 0.379128 / 0.323480 (0.055648) | 0.004087 / 0.007986 (-0.003899) | 0.003357 / 0.004328 (-0.000972) | 0.065570 / 0.004250 (0.061320) | 0.056259 / 0.037052 (0.019207) | 0.368595 / 0.258489 (0.110106) | 0.402672 / 0.293841 (0.108831) | 0.030946 / 0.128546 (-0.097600) | 0.008509 / 0.075646 (-0.067137) | 0.288552 / 0.419271 (-0.130719) | 0.052134 / 0.043533 (0.008601) | 0.344653 / 0.255139 (0.089514) | 0.374199 / 0.283200 (0.090999) | 0.026251 / 0.141683 (-0.115432) | 1.488258 / 1.452155 (0.036103) | 1.567119 / 1.492716 (0.074402) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218740 / 0.018006 (0.200734) | 0.465483 / 0.000490 (0.464994) | 0.003959 / 0.000200 (0.003759) | 0.000083 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029860 / 0.037411 (-0.007551) | 0.087968 / 0.014526 (0.073442) | 0.098257 / 0.176557 (-0.078299) | 0.155478 / 0.737135 (-0.581657) | 0.100696 / 0.296338 (-0.195642) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384642 / 0.215209 (0.169432) | 3.821692 / 2.077655 (1.744038) | 1.838012 / 1.504120 (0.333892) | 1.677554 / 1.541195 (0.136360) | 1.764284 / 1.468490 (0.295794) | 0.487512 / 4.584777 (-4.097265) | 3.614572 / 3.745712 (-0.131141) | 3.300740 / 5.269862 (-1.969122) | 2.079044 / 4.565676 (-2.486632) | 0.057392 / 0.424275 (-0.366883) | 0.007642 / 0.007607 (0.000035) | 0.456161 / 0.226044 (0.230117) | 4.554124 / 2.268929 (2.285196) | 2.319288 / 55.444624 (-53.125336) | 1.972024 / 6.876477 (-4.904452) | 2.210598 / 2.142072 (0.068526) | 0.588442 / 4.805227 (-4.216785) | 0.134474 / 6.500664 (-6.366191) | 0.062682 / 0.075469 (-0.012787) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243548 / 1.841788 (-0.598239) | 20.267230 / 8.074308 (12.192922) | 14.872096 / 10.191392 (4.680704) | 0.165164 / 0.680424 (-0.515260) | 0.018985 / 0.534201 (-0.515216) | 0.394526 / 0.579283 (-0.184757) | 0.413918 / 0.434364 (-0.020446) | 0.467130 / 0.540337 (-0.073208) | 0.627055 / 1.386936 (-0.759881) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006940 / 0.011353 (-0.004412) | 0.004203 / 0.011008 (-0.006805) | 0.065828 / 0.038508 (0.027320) | 0.076604 / 0.023109 (0.053495) | 0.401781 / 0.275898 (0.125883) | 0.434838 / 0.323480 (0.111358) | 0.005626 / 0.007986 (-0.002359) | 0.003409 / 0.004328 (-0.000920) | 0.064702 / 0.004250 (0.060452) | 0.057525 / 0.037052 (0.020473) | 0.405032 / 0.258489 (0.146543) | 0.440906 / 0.293841 (0.147065) | 0.032713 / 0.128546 (-0.095833) | 0.008723 / 0.075646 (-0.066923) | 0.071448 / 0.419271 (-0.347823) | 0.048186 / 0.043533 (0.004653) | 0.403950 / 0.255139 (0.148811) | 0.419506 / 0.283200 (0.136307) | 0.023532 / 0.141683 (-0.118150) | 1.496435 / 1.452155 (0.044280) | 1.567236 / 1.492716 (0.074519) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229194 / 0.018006 (0.211188) | 0.451363 / 0.000490 (0.450873) | 0.003651 / 0.000200 (0.003451) | 0.000108 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033674 / 0.037411 (-0.003737) | 0.097521 / 0.014526 (0.082995) | 0.108806 / 0.176557 (-0.067751) | 0.161002 / 0.737135 (-0.576133) | 0.108594 / 0.296338 (-0.187745) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436638 / 0.215209 (0.221429) | 4.348844 / 2.077655 (2.271189) | 2.341737 / 1.504120 (0.837617) | 2.195850 / 1.541195 (0.654656) | 2.332147 / 1.468490 (0.863657) | 0.496180 / 4.584777 (-4.088597) | 3.680987 / 3.745712 (-0.064725) | 3.332203 / 5.269862 (-1.937659) | 2.099541 / 4.565676 (-2.466136) | 0.058629 / 0.424275 (-0.365646) | 0.007363 / 0.007607 (-0.000245) | 0.517658 / 0.226044 (0.291614) | 5.175321 / 2.268929 (2.906392) | 2.858660 / 55.444624 (-52.585964) | 2.540557 / 6.876477 (-4.335920) | 2.755360 / 2.142072 (0.613288) | 0.595488 / 4.805227 (-4.209739) | 0.134265 / 6.500664 (-6.366399) | 0.062033 / 0.075469 (-0.013436) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.389950 / 1.841788 (-0.451838) | 20.800274 / 8.074308 (12.725966) | 15.314531 / 10.191392 (5.123139) | 0.166822 / 0.680424 (-0.513602) | 0.021099 / 0.534201 (-0.513102) | 0.400388 / 0.579283 (-0.178895) | 0.419981 / 0.434364 (-0.014383) | 0.474259 / 0.540337 (-0.066078) | 0.731678 / 1.386936 (-0.655258) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4566827557acbeba0d4cb66449bb70367e341b05 \"CML watermark\")\n" ]

"2023-08-22T11:27:41Z"

"2023-08-23T14:01:25Z"

"2023-08-23T13:52:36Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6165). All of your documentation changes will be reflected on that endpoint.", "@lhoestq \r\nA test is failing, but I don't think it is due to my changes", "Good catch ! Could you add a test to make sure transformed IterableDataset objects are still picklable ?\r\n\r\nSomething like `test_pickle_after_many_transforms` in in `test_iterable_dataset.py` that does a bunch or rename, map, take on a dataset and checks that the dataset can be pickled at the end and the reloaded dataset returns the same elements", "@lhoestq \r\nI added the test and fixed one last method" ]

"2023-08-22T10:07:23Z"

"2023-08-25T09:22:49Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006874 / 0.011353 (-0.004479) | 0.004276 / 0.011008 (-0.006732) | 0.085198 / 0.038508 (0.046690) | 0.084281 / 0.023109 (0.061171) | 0.344767 / 0.275898 (0.068869) | 0.377798 / 0.323480 (0.054318) | 0.005656 / 0.007986 (-0.002330) | 0.003601 / 0.004328 (-0.000727) | 0.065486 / 0.004250 (0.061235) | 0.056191 / 0.037052 (0.019139) | 0.351412 / 0.258489 (0.092923) | 0.398591 / 0.293841 (0.104750) | 0.031662 / 0.128546 (-0.096884) | 0.008901 / 0.075646 (-0.066745) | 0.290423 / 0.419271 (-0.128849) | 0.053793 / 0.043533 (0.010260) | 0.347968 / 0.255139 (0.092829) | 0.376978 / 0.283200 (0.093778) | 0.026745 / 0.141683 (-0.114938) | 1.514119 / 1.452155 (0.061964) | 1.580920 / 1.492716 (0.088203) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.273648 / 0.018006 (0.255642) | 0.575176 / 0.000490 (0.574686) | 0.003557 / 0.000200 (0.003357) | 0.000093 / 0.000054 (0.000038) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031714 / 0.037411 (-0.005697) | 0.089166 / 0.014526 (0.074640) | 0.101525 / 0.176557 (-0.075032) | 0.161855 / 0.737135 (-0.575281) | 0.101391 / 0.296338 (-0.194947) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.380947 / 0.215209 (0.165738) | 3.800527 / 2.077655 (1.722873) | 1.820789 / 1.504120 (0.316669) | 1.657327 / 1.541195 (0.116132) | 1.776242 / 1.468490 (0.307752) | 0.486954 / 4.584777 (-4.097823) | 3.688340 / 3.745712 (-0.057372) | 3.354453 / 5.269862 (-1.915409) | 2.119995 / 4.565676 (-2.445682) | 0.057446 / 0.424275 (-0.366829) | 0.007752 / 0.007607 (0.000145) | 0.461907 / 0.226044 (0.235862) | 4.617870 / 2.268929 (2.348942) | 2.337025 / 55.444624 (-53.107599) | 1.964770 / 6.876477 (-4.911707) | 2.252066 / 2.142072 (0.109993) | 0.591585 / 4.805227 (-4.213642) | 0.134655 / 6.500664 (-6.366009) | 0.060646 / 0.075469 (-0.014823) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.263271 / 1.841788 (-0.578517) | 20.822286 / 8.074308 (12.747978) | 14.710256 / 10.191392 (4.518864) | 0.167285 / 0.680424 (-0.513139) | 0.018302 / 0.534201 (-0.515899) | 0.401023 / 0.579283 (-0.178260) | 0.428956 / 0.434364 (-0.005407) | 0.466120 / 0.540337 (-0.074218) | 0.637868 / 1.386936 (-0.749069) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007174 / 0.011353 (-0.004179) | 0.004418 / 0.011008 (-0.006590) | 0.065731 / 0.038508 (0.027223) | 0.090457 / 0.023109 (0.067348) | 0.387306 / 0.275898 (0.111408) | 0.427178 / 0.323480 (0.103698) | 0.005699 / 0.007986 (-0.002286) | 0.003662 / 0.004328 (-0.000666) | 0.066190 / 0.004250 (0.061940) | 0.062860 / 0.037052 (0.025808) | 0.388855 / 0.258489 (0.130366) | 0.427853 / 0.293841 (0.134012) | 0.032770 / 0.128546 (-0.095776) | 0.008780 / 0.075646 (-0.066866) | 0.071156 / 0.419271 (-0.348116) | 0.050174 / 0.043533 (0.006641) | 0.385254 / 0.255139 (0.130115) | 0.405069 / 0.283200 (0.121869) | 0.025561 / 0.141683 (-0.116122) | 1.506907 / 1.452155 (0.054752) | 1.543270 / 1.492716 (0.050554) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.304651 / 0.018006 (0.286645) | 0.577269 / 0.000490 (0.576780) | 0.004479 / 0.000200 (0.004279) | 0.000127 / 0.000054 (0.000073) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034070 / 0.037411 (-0.003341) | 0.097664 / 0.014526 (0.083138) | 0.106969 / 0.176557 (-0.069588) | 0.163093 / 0.737135 (-0.574043) | 0.109384 / 0.296338 (-0.186955) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.414823 / 0.215209 (0.199614) | 4.148390 / 2.077655 (2.070735) | 2.114038 / 1.504120 (0.609918) | 1.959316 / 1.541195 (0.418121) | 2.098138 / 1.468490 (0.629648) | 0.486338 / 4.584777 (-4.098439) | 3.642850 / 3.745712 (-0.102863) | 3.458311 / 5.269862 (-1.811551) | 2.185662 / 4.565676 (-2.380014) | 0.057555 / 0.424275 (-0.366720) | 0.007522 / 0.007607 (-0.000085) | 0.497975 / 0.226044 (0.271931) | 4.971528 / 2.268929 (2.702600) | 2.614087 / 55.444624 (-52.830537) | 2.288406 / 6.876477 (-4.588070) | 2.564067 / 2.142072 (0.421995) | 0.582248 / 4.805227 (-4.222979) | 0.134931 / 6.500664 (-6.365733) | 0.062689 / 0.075469 (-0.012780) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.343331 / 1.841788 (-0.498457) | 21.398950 / 8.074308 (13.324642) | 14.620971 / 10.191392 (4.429579) | 0.169779 / 0.680424 (-0.510644) | 0.018683 / 0.534201 (-0.515518) | 0.396152 / 0.579283 (-0.183131) | 0.409596 / 0.434364 (-0.024768) | 0.482875 / 0.540337 (-0.057463) | 0.659977 / 1.386936 (-0.726959) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1fd2234b8c802d47db5a5aa939148f98c9c49350 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006662 / 0.011353 (-0.004691) | 0.003959 / 0.011008 (-0.007049) | 0.084447 / 0.038508 (0.045939) | 0.070267 / 0.023109 (0.047158) | 0.310301 / 0.275898 (0.034403) | 0.339866 / 0.323480 (0.016386) | 0.004008 / 0.007986 (-0.003977) | 0.003270 / 0.004328 (-0.001058) | 0.064997 / 0.004250 (0.060746) | 0.053151 / 0.037052 (0.016099) | 0.327867 / 0.258489 (0.069378) | 0.368560 / 0.293841 (0.074719) | 0.031436 / 0.128546 (-0.097111) | 0.008547 / 0.075646 (-0.067099) | 0.288513 / 0.419271 (-0.130758) | 0.051833 / 0.043533 (0.008300) | 0.312660 / 0.255139 (0.057521) | 0.347180 / 0.283200 (0.063980) | 0.024982 / 0.141683 (-0.116701) | 1.472487 / 1.452155 (0.020333) | 1.550138 / 1.492716 (0.057422) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208443 / 0.018006 (0.190437) | 0.451927 / 0.000490 (0.451437) | 0.004452 / 0.000200 (0.004252) | 0.000082 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029164 / 0.037411 (-0.008247) | 0.085801 / 0.014526 (0.071275) | 0.096229 / 0.176557 (-0.080327) | 0.153063 / 0.737135 (-0.584072) | 0.097712 / 0.296338 (-0.198626) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383969 / 0.215209 (0.168760) | 3.829216 / 2.077655 (1.751561) | 1.854466 / 1.504120 (0.350346) | 1.684149 / 1.541195 (0.142954) | 1.759422 / 1.468490 (0.290932) | 0.480229 / 4.584777 (-4.104548) | 3.653363 / 3.745712 (-0.092349) | 3.264456 / 5.269862 (-2.005406) | 2.020579 / 4.565676 (-2.545097) | 0.056920 / 0.424275 (-0.367355) | 0.007625 / 0.007607 (0.000018) | 0.458559 / 0.226044 (0.232515) | 4.580288 / 2.268929 (2.311359) | 2.353783 / 55.444624 (-53.090841) | 1.967223 / 6.876477 (-4.909253) | 2.182707 / 2.142072 (0.040634) | 0.631341 / 4.805227 (-4.173886) | 0.141656 / 6.500664 (-6.359008) | 0.059918 / 0.075469 (-0.015551) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.279635 / 1.841788 (-0.562153) | 19.725763 / 8.074308 (11.651455) | 14.477946 / 10.191392 (4.286554) | 0.164360 / 0.680424 (-0.516064) | 0.018286 / 0.534201 (-0.515915) | 0.394935 / 0.579283 (-0.184348) | 0.419638 / 0.434364 (-0.014726) | 0.460366 / 0.540337 (-0.079972) | 0.636876 / 1.386936 (-0.750060) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006568 / 0.011353 (-0.004785) | 0.004270 / 0.011008 (-0.006738) | 0.065522 / 0.038508 (0.027014) | 0.071597 / 0.023109 (0.048487) | 0.394929 / 0.275898 (0.119031) | 0.427548 / 0.323480 (0.104068) | 0.005320 / 0.007986 (-0.002665) | 0.003366 / 0.004328 (-0.000962) | 0.065780 / 0.004250 (0.061530) | 0.055390 / 0.037052 (0.018338) | 0.397950 / 0.258489 (0.139461) | 0.435800 / 0.293841 (0.141959) | 0.031816 / 0.128546 (-0.096730) | 0.008555 / 0.075646 (-0.067091) | 0.072110 / 0.419271 (-0.347161) | 0.049077 / 0.043533 (0.005544) | 0.390065 / 0.255139 (0.134926) | 0.410294 / 0.283200 (0.127094) | 0.023389 / 0.141683 (-0.118294) | 1.491491 / 1.452155 (0.039336) | 1.551057 / 1.492716 (0.058341) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243869 / 0.018006 (0.225862) | 0.451961 / 0.000490 (0.451471) | 0.019834 / 0.000200 (0.019634) | 0.000114 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031031 / 0.037411 (-0.006380) | 0.088189 / 0.014526 (0.073663) | 0.101743 / 0.176557 (-0.074814) | 0.155236 / 0.737135 (-0.581899) | 0.101245 / 0.296338 (-0.195094) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.422178 / 0.215209 (0.206969) | 4.199989 / 2.077655 (2.122334) | 2.228816 / 1.504120 (0.724696) | 2.057172 / 1.541195 (0.515978) | 2.162651 / 1.468490 (0.694161) | 0.491186 / 4.584777 (-4.093591) | 3.666221 / 3.745712 (-0.079491) | 3.289531 / 5.269862 (-1.980331) | 2.050027 / 4.565676 (-2.515650) | 0.057464 / 0.424275 (-0.366811) | 0.007379 / 0.007607 (-0.000228) | 0.506532 / 0.226044 (0.280487) | 5.066385 / 2.268929 (2.797456) | 2.694405 / 55.444624 (-52.750219) | 2.372200 / 6.876477 (-4.504277) | 2.562724 / 2.142072 (0.420652) | 0.615474 / 4.805227 (-4.189753) | 0.148284 / 6.500664 (-6.352380) | 0.061380 / 0.075469 (-0.014089) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.332649 / 1.841788 (-0.509139) | 20.591063 / 8.074308 (12.516755) | 14.105253 / 10.191392 (3.913861) | 0.151886 / 0.680424 (-0.528537) | 0.018200 / 0.534201 (-0.516001) | 0.395278 / 0.579283 (-0.184005) | 0.407113 / 0.434364 (-0.027251) | 0.473168 / 0.540337 (-0.067170) | 0.660766 / 1.386936 (-0.726170) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8b8e6ee067eb74e7965ca2a6768f15f9398cb7c8 \"CML watermark\")\n" ]

"2023-08-21T14:57:54Z"

"2023-08-21T16:27:05Z"

"2023-08-21T16:18:26Z"

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[ "Answered on the forum [here](https://discuss.huggingface.co/t/error-type-arrowinvalid-details-failed-to-parse-string-254-254-as-a-scalar-of-type-int32/51323)." ]

"2023-08-19T11:34:40Z"

"2023-08-21T13:28:16Z"

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[ "Hi ! Feel free to open a discussion at https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T/discussions to ask the file to be fixed (or directly open a PR with the fixed file)\r\n\r\n`datasets` expects all the examples to have the same fields", "@lhoestq I think the problem is caused by the fact that hugging face datasets writes a copy of data to the local cache using pyarrow. And the data scheme is inferred from the first few data blocks as can be seen [here](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_writer.py#L570). Maybe setting `streaming=True` can workaround this problem. Would you agree with my statement? ", "> @lhoestq I think the problem is caused by the fact that hugging face datasets writes a copy of data to the local cache using pyarrow. And the data scheme is inferred from the first few data blocks as can be seen [here](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_writer.py#L570).\r\n\r\nCorrect. Therefore any example that doesn't follow the inferred schema will make the code fail.\r\n\r\n> Maybe setting streaming=True can workaround this problem. Would you agree with my statement?\r\n\r\nYou'll meet the same problem but later - when streaming and arriving at the problematic example", "@lhoestq I just run below test with streaming=True and is not failing at the problematic example\r\n```python\r\nds = load_dataset('json', data_files='/path_to_local_RedPajamaData/filtered_27f05c041a1c401783f90b9415e40e4b.sampled.jsonl', streaming=True)\r\ncount = 0\r\nfor i in ds['train']:\r\n count += 1\r\n print(count)\r\n```\r\n\r\nand completes the 262241 samples successfully. It does error our when streaming is not used " ]

"2023-08-18T07:19:39Z"

"2023-08-18T17:00:35Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006736 / 0.011353 (-0.004617) | 0.004099 / 0.011008 (-0.006909) | 0.084339 / 0.038508 (0.045831) | 0.073715 / 0.023109 (0.050605) | 0.311962 / 0.275898 (0.036064) | 0.356108 / 0.323480 (0.032628) | 0.005321 / 0.007986 (-0.002665) | 0.003390 / 0.004328 (-0.000939) | 0.064622 / 0.004250 (0.060372) | 0.053978 / 0.037052 (0.016926) | 0.328967 / 0.258489 (0.070478) | 0.370506 / 0.293841 (0.076665) | 0.031123 / 0.128546 (-0.097423) | 0.008465 / 0.075646 (-0.067181) | 0.288136 / 0.419271 (-0.131136) | 0.052909 / 0.043533 (0.009376) | 0.325189 / 0.255139 (0.070050) | 0.360112 / 0.283200 (0.076912) | 0.023389 / 0.141683 (-0.118294) | 1.492899 / 1.452155 (0.040744) | 1.586449 / 1.492716 (0.093733) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.219708 / 0.018006 (0.201702) | 0.469550 / 0.000490 (0.469060) | 0.002776 / 0.000200 (0.002576) | 0.000084 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028985 / 0.037411 (-0.008427) | 0.083487 / 0.014526 (0.068961) | 0.096938 / 0.176557 (-0.079619) | 0.152886 / 0.737135 (-0.584249) | 0.096242 / 0.296338 (-0.200096) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.381959 / 0.215209 (0.166750) | 3.800033 / 2.077655 (1.722378) | 1.831903 / 1.504120 (0.327783) | 1.663207 / 1.541195 (0.122012) | 1.747282 / 1.468490 (0.278792) | 0.481671 / 4.584777 (-4.103106) | 3.653725 / 3.745712 (-0.091987) | 3.253058 / 5.269862 (-2.016804) | 2.022014 / 4.565676 (-2.543663) | 0.056651 / 0.424275 (-0.367624) | 0.007640 / 0.007607 (0.000033) | 0.461795 / 0.226044 (0.235750) | 4.625535 / 2.268929 (2.356606) | 2.356341 / 55.444624 (-53.088283) | 1.977437 / 6.876477 (-4.899040) | 2.179672 / 2.142072 (0.037599) | 0.582875 / 4.805227 (-4.222353) | 0.132964 / 6.500664 (-6.367700) | 0.060398 / 0.075469 (-0.015071) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.309567 / 1.841788 (-0.532220) | 19.856306 / 8.074308 (11.781997) | 14.074350 / 10.191392 (3.882958) | 0.149615 / 0.680424 (-0.530809) | 0.018487 / 0.534201 (-0.515714) | 0.393995 / 0.579283 (-0.185288) | 0.409057 / 0.434364 (-0.025307) | 0.459551 / 0.540337 (-0.080787) | 0.644594 / 1.386936 (-0.742342) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006824 / 0.011353 (-0.004529) | 0.004099 / 0.011008 (-0.006909) | 0.064415 / 0.038508 (0.025907) | 0.077983 / 0.023109 (0.054874) | 0.359351 / 0.275898 (0.083453) | 0.395168 / 0.323480 (0.071688) | 0.005384 / 0.007986 (-0.002602) | 0.003298 / 0.004328 (-0.001030) | 0.065041 / 0.004250 (0.060791) | 0.056717 / 0.037052 (0.019664) | 0.366882 / 0.258489 (0.108393) | 0.401337 / 0.293841 (0.107496) | 0.032273 / 0.128546 (-0.096273) | 0.008666 / 0.075646 (-0.066981) | 0.071442 / 0.419271 (-0.347829) | 0.049999 / 0.043533 (0.006466) | 0.365001 / 0.255139 (0.109862) | 0.379579 / 0.283200 (0.096379) | 0.023357 / 0.141683 (-0.118326) | 1.476839 / 1.452155 (0.024684) | 1.541703 / 1.492716 (0.048987) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.239014 / 0.018006 (0.221008) | 0.460678 / 0.000490 (0.460188) | 0.003368 / 0.000200 (0.003168) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030981 / 0.037411 (-0.006430) | 0.088287 / 0.014526 (0.073761) | 0.102459 / 0.176557 (-0.074098) | 0.154695 / 0.737135 (-0.582441) | 0.103479 / 0.296338 (-0.192860) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.416084 / 0.215209 (0.200874) | 4.128365 / 2.077655 (2.050710) | 2.113053 / 1.504120 (0.608934) | 1.948993 / 1.541195 (0.407798) | 2.035609 / 1.468490 (0.567119) | 0.481705 / 4.584777 (-4.103072) | 3.630366 / 3.745712 (-0.115346) | 3.340837 / 5.269862 (-1.929024) | 2.052573 / 4.565676 (-2.513104) | 0.056805 / 0.424275 (-0.367470) | 0.007294 / 0.007607 (-0.000313) | 0.489597 / 0.226044 (0.263553) | 4.892728 / 2.268929 (2.623799) | 2.564692 / 55.444624 (-52.879932) | 2.251964 / 6.876477 (-4.624513) | 2.457912 / 2.142072 (0.315839) | 0.588433 / 4.805227 (-4.216794) | 0.133588 / 6.500664 (-6.367076) | 0.062298 / 0.075469 (-0.013171) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.328566 / 1.841788 (-0.513222) | 20.145568 / 8.074308 (12.071260) | 14.231306 / 10.191392 (4.039914) | 0.168356 / 0.680424 (-0.512067) | 0.018333 / 0.534201 (-0.515868) | 0.390901 / 0.579283 (-0.188382) | 0.415005 / 0.434364 (-0.019359) | 0.477282 / 0.540337 (-0.063055) | 0.652085 / 1.386936 (-0.734851) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#341a41880a70b29f030caa0d36f1e297535ba5f9 \"CML watermark\")\n", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6161). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006388 / 0.011353 (-0.004965) | 0.003917 / 0.011008 (-0.007092) | 0.087397 / 0.038508 (0.048889) | 0.068522 / 0.023109 (0.045412) | 0.313299 / 0.275898 (0.037401) | 0.342884 / 0.323480 (0.019405) | 0.005216 / 0.007986 (-0.002770) | 0.003293 / 0.004328 (-0.001035) | 0.067474 / 0.004250 (0.063224) | 0.051122 / 0.037052 (0.014070) | 0.326443 / 0.258489 (0.067954) | 0.355744 / 0.293841 (0.061903) | 0.031130 / 0.128546 (-0.097416) | 0.008617 / 0.075646 (-0.067029) | 0.291201 / 0.419271 (-0.128070) | 0.052050 / 0.043533 (0.008517) | 0.312135 / 0.255139 (0.056996) | 0.347233 / 0.283200 (0.064034) | 0.023775 / 0.141683 (-0.117907) | 1.478807 / 1.452155 (0.026652) | 1.581239 / 1.492716 (0.088522) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208252 / 0.018006 (0.190246) | 0.466314 / 0.000490 (0.465824) | 0.004439 / 0.000200 (0.004239) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027918 / 0.037411 (-0.009494) | 0.082410 / 0.014526 (0.067884) | 0.094231 / 0.176557 (-0.082326) | 0.150189 / 0.737135 (-0.586946) | 0.095404 / 0.296338 (-0.200935) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382026 / 0.215209 (0.166817) | 3.822213 / 2.077655 (1.744559) | 1.833716 / 1.504120 (0.329596) | 1.666250 / 1.541195 (0.125055) | 1.703350 / 1.468490 (0.234860) | 0.477918 / 4.584777 (-4.106859) | 3.629304 / 3.745712 (-0.116408) | 3.199672 / 5.269862 (-2.070190) | 1.977855 / 4.565676 (-2.587821) | 0.056275 / 0.424275 (-0.368000) | 0.007538 / 0.007607 (-0.000070) | 0.455995 / 0.226044 (0.229950) | 4.559234 / 2.268929 (2.290305) | 2.333819 / 55.444624 (-53.110805) | 2.006851 / 6.876477 (-4.869625) | 2.150683 / 2.142072 (0.008611) | 0.576786 / 4.805227 (-4.228441) | 0.132352 / 6.500664 (-6.368312) | 0.059359 / 0.075469 (-0.016110) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.261525 / 1.841788 (-0.580262) | 19.174957 / 8.074308 (11.100649) | 14.286796 / 10.191392 (4.095404) | 0.144610 / 0.680424 (-0.535813) | 0.018213 / 0.534201 (-0.515988) | 0.390404 / 0.579283 (-0.188879) | 0.404678 / 0.434364 (-0.029686) | 0.455636 / 0.540337 (-0.084701) | 0.620801 / 1.386936 (-0.766135) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006383 / 0.011353 (-0.004970) | 0.003852 / 0.011008 (-0.007156) | 0.064116 / 0.038508 (0.025607) | 0.068920 / 0.023109 (0.045810) | 0.359439 / 0.275898 (0.083541) | 0.388904 / 0.323480 (0.065425) | 0.005192 / 0.007986 (-0.002794) | 0.003233 / 0.004328 (-0.001095) | 0.064589 / 0.004250 (0.060339) | 0.054496 / 0.037052 (0.017444) | 0.368699 / 0.258489 (0.110210) | 0.400420 / 0.293841 (0.106579) | 0.030869 / 0.128546 (-0.097677) | 0.008424 / 0.075646 (-0.067222) | 0.071015 / 0.419271 (-0.348257) | 0.048333 / 0.043533 (0.004801) | 0.360652 / 0.255139 (0.105513) | 0.393534 / 0.283200 (0.110334) | 0.022685 / 0.141683 (-0.118998) | 1.495565 / 1.452155 (0.043410) | 1.537947 / 1.492716 (0.045230) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.232911 / 0.018006 (0.214905) | 0.454191 / 0.000490 (0.453702) | 0.005711 / 0.000200 (0.005511) | 0.000117 / 0.000054 (0.000062) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029486 / 0.037411 (-0.007925) | 0.087249 / 0.014526 (0.072724) | 0.100104 / 0.176557 (-0.076453) | 0.151556 / 0.737135 (-0.585580) | 0.100853 / 0.296338 (-0.195485) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.415134 / 0.215209 (0.199925) | 4.139068 / 2.077655 (2.061413) | 2.121079 / 1.504120 (0.616959) | 1.945616 / 1.541195 (0.404421) | 1.988188 / 1.468490 (0.519698) | 0.483994 / 4.584777 (-4.100783) | 3.640366 / 3.745712 (-0.105347) | 3.218896 / 5.269862 (-2.050966) | 2.015527 / 4.565676 (-2.550149) | 0.056946 / 0.424275 (-0.367329) | 0.007262 / 0.007607 (-0.000345) | 0.486075 / 0.226044 (0.260031) | 4.864191 / 2.268929 (2.595262) | 2.590853 / 55.444624 (-52.853772) | 2.315359 / 6.876477 (-4.561118) | 2.418733 / 2.142072 (0.276661) | 0.582378 / 4.805227 (-4.222849) | 0.134097 / 6.500664 (-6.366568) | 0.060797 / 0.075469 (-0.014672) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337021 / 1.841788 (-0.504766) | 19.468907 / 8.074308 (11.394599) | 14.348874 / 10.191392 (4.157482) | 0.170408 / 0.680424 (-0.510016) | 0.018414 / 0.534201 (-0.515787) | 0.394551 / 0.579283 (-0.184732) | 0.404750 / 0.434364 (-0.029613) | 0.471972 / 0.540337 (-0.068365) | 0.650607 / 1.386936 (-0.736329) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ab4d978e2d5c246dc91e2fed041b06a38190be3b \"CML watermark\")\n", "The CI errors are unrelated to the changes" ]

"2023-08-17T22:40:37Z"

"2023-08-18T13:47:59Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008368 / 0.011353 (-0.002985) | 0.004754 / 0.011008 (-0.006254) | 0.096646 / 0.038508 (0.058138) | 0.088980 / 0.023109 (0.065871) | 0.374532 / 0.275898 (0.098633) | 0.404840 / 0.323480 (0.081360) | 0.006026 / 0.007986 (-0.001960) | 0.005716 / 0.004328 (0.001387) | 0.076297 / 0.004250 (0.072047) | 0.072335 / 0.037052 (0.035283) | 0.379435 / 0.258489 (0.120946) | 0.423449 / 0.293841 (0.129608) | 0.041344 / 0.128546 (-0.087202) | 0.009758 / 0.075646 (-0.065889) | 0.341550 / 0.419271 (-0.077721) | 0.068559 / 0.043533 (0.025026) | 0.368313 / 0.255139 (0.113174) | 0.415147 / 0.283200 (0.131947) | 0.028692 / 0.141683 (-0.112990) | 1.816198 / 1.452155 (0.364044) | 1.983351 / 1.492716 (0.490635) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222712 / 0.018006 (0.204706) | 0.517850 / 0.000490 (0.517360) | 0.004436 / 0.000200 (0.004236) | 0.000094 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033168 / 0.037411 (-0.004243) | 0.101353 / 0.014526 (0.086827) | 0.113235 / 0.176557 (-0.063322) | 0.180308 / 0.737135 (-0.556827) | 0.114604 / 0.296338 (-0.181734) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.454415 / 0.215209 (0.239206) | 4.500355 / 2.077655 (2.422701) | 2.188223 / 1.504120 (0.684103) | 1.974256 / 1.541195 (0.433061) | 2.067331 / 1.468490 (0.598841) | 0.572982 / 4.584777 (-4.011795) | 4.239160 / 3.745712 (0.493448) | 3.836812 / 5.269862 (-1.433049) | 2.367022 / 4.565676 (-2.198655) | 0.066886 / 0.424275 (-0.357389) | 0.009111 / 0.007607 (0.001504) | 0.539881 / 0.226044 (0.313837) | 5.362247 / 2.268929 (3.093319) | 2.784044 / 55.444624 (-52.660580) | 2.320975 / 6.876477 (-4.555502) | 2.543108 / 2.142072 (0.401036) | 0.685751 / 4.805227 (-4.119477) | 0.156840 / 6.500664 (-6.343824) | 0.071764 / 0.075469 (-0.003705) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.549830 / 1.841788 (-0.291958) | 22.799622 / 8.074308 (14.725314) | 16.750692 / 10.191392 (6.559300) | 0.196192 / 0.680424 (-0.484232) | 0.024518 / 0.534201 (-0.509683) | 0.479302 / 0.579283 (-0.099981) | 0.522256 / 0.434364 (0.087892) | 0.545809 / 0.540337 (0.005471) | 0.748437 / 1.386936 (-0.638499) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007789 / 0.011353 (-0.003564) | 0.004563 / 0.011008 (-0.006445) | 0.074631 / 0.038508 (0.036123) | 0.086892 / 0.023109 (0.063783) | 0.427014 / 0.275898 (0.151116) | 0.463257 / 0.323480 (0.139777) | 0.005987 / 0.007986 (-0.001999) | 0.003803 / 0.004328 (-0.000526) | 0.074799 / 0.004250 (0.070549) | 0.063473 / 0.037052 (0.026420) | 0.429905 / 0.258489 (0.171416) | 0.468967 / 0.293841 (0.175127) | 0.036768 / 0.128546 (-0.091778) | 0.009675 / 0.075646 (-0.065971) | 0.082546 / 0.419271 (-0.336725) | 0.058027 / 0.043533 (0.014494) | 0.429813 / 0.255139 (0.174674) | 0.449200 / 0.283200 (0.166001) | 0.026713 / 0.141683 (-0.114969) | 1.812022 / 1.452155 (0.359867) | 1.847305 / 1.492716 (0.354589) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.320383 / 0.018006 (0.302377) | 0.485995 / 0.000490 (0.485505) | 0.024365 / 0.000200 (0.024165) | 0.000156 / 0.000054 (0.000101) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036341 / 0.037411 (-0.001071) | 0.104635 / 0.014526 (0.090110) | 0.119456 / 0.176557 (-0.057101) | 0.182042 / 0.737135 (-0.555093) | 0.118944 / 0.296338 (-0.177395) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.506410 / 0.215209 (0.291201) | 5.061119 / 2.077655 (2.983465) | 2.756557 / 1.504120 (1.252437) | 2.546504 / 1.541195 (1.005309) | 2.585509 / 1.468490 (1.117019) | 0.564291 / 4.584777 (-4.020486) | 4.281219 / 3.745712 (0.535507) | 3.919439 / 5.269862 (-1.350423) | 2.588788 / 4.565676 (-1.976889) | 0.066900 / 0.424275 (-0.357375) | 0.008680 / 0.007607 (0.001073) | 0.598435 / 0.226044 (0.372390) | 5.976054 / 2.268929 (3.707125) | 3.260211 / 55.444624 (-52.184414) | 2.874597 / 6.876477 (-4.001880) | 3.105769 / 2.142072 (0.963697) | 0.692938 / 4.805227 (-4.112289) | 0.157777 / 6.500664 (-6.342887) | 0.073128 / 0.075469 (-0.002341) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.559380 / 1.841788 (-0.282408) | 22.986540 / 8.074308 (14.912232) | 16.305564 / 10.191392 (6.114172) | 0.174939 / 0.680424 (-0.505485) | 0.021932 / 0.534201 (-0.512269) | 0.468162 / 0.579283 (-0.111121) | 0.472610 / 0.434364 (0.038246) | 0.574574 / 0.540337 (0.034237) | 0.783505 / 1.386936 (-0.603431) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#550923b5d6ae64eb20b8f66da843395e9fa404ac \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.012553 / 0.011353 (0.001201) | 0.005358 / 0.011008 (-0.005650) | 0.108338 / 0.038508 (0.069830) | 0.101105 / 0.023109 (0.077995) | 0.416808 / 0.275898 (0.140910) | 0.454599 / 0.323480 (0.131119) | 0.006665 / 0.007986 (-0.001321) | 0.004186 / 0.004328 (-0.000143) | 0.084900 / 0.004250 (0.080649) | 0.062881 / 0.037052 (0.025829) | 0.424423 / 0.258489 (0.165934) | 0.482651 / 0.293841 (0.188810) | 0.055740 / 0.128546 (-0.072807) | 0.014469 / 0.075646 (-0.061177) | 0.383267 / 0.419271 (-0.036005) | 0.067487 / 0.043533 (0.023955) | 0.414983 / 0.255139 (0.159844) | 0.459437 / 0.283200 (0.176237) | 0.038679 / 0.141683 (-0.103004) | 1.828002 / 1.452155 (0.375847) | 1.951946 / 1.492716 (0.459230) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.288033 / 0.018006 (0.270027) | 0.603536 / 0.000490 (0.603046) | 0.004874 / 0.000200 (0.004674) | 0.000138 / 0.000054 (0.000084) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031988 / 0.037411 (-0.005423) | 0.095807 / 0.014526 (0.081281) | 0.113459 / 0.176557 (-0.063098) | 0.182012 / 0.737135 (-0.555123) | 0.113121 / 0.296338 (-0.183217) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.620709 / 0.215209 (0.405500) | 6.096569 / 2.077655 (4.018915) | 2.754612 / 1.504120 (1.250492) | 2.449786 / 1.541195 (0.908591) | 2.470694 / 1.468490 (1.002204) | 0.837016 / 4.584777 (-3.747761) | 5.237290 / 3.745712 (1.491578) | 4.713220 / 5.269862 (-0.556642) | 3.020934 / 4.565676 (-1.544743) | 0.096892 / 0.424275 (-0.327383) | 0.009423 / 0.007607 (0.001816) | 0.720313 / 0.226044 (0.494269) | 7.369673 / 2.268929 (5.100744) | 3.550384 / 55.444624 (-51.894241) | 2.868868 / 6.876477 (-4.007609) | 3.081469 / 2.142072 (0.939397) | 1.042968 / 4.805227 (-3.762259) | 0.232530 / 6.500664 (-6.268134) | 0.080805 / 0.075469 (0.005336) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.645777 / 1.841788 (-0.196011) | 24.590862 / 8.074308 (16.516554) | 21.315496 / 10.191392 (11.124104) | 0.228796 / 0.680424 (-0.451628) | 0.028479 / 0.534201 (-0.505722) | 0.494413 / 0.579283 (-0.084870) | 0.582773 / 0.434364 (0.148409) | 0.552575 / 0.540337 (0.012238) | 0.787217 / 1.386936 (-0.599719) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008743 / 0.011353 (-0.002609) | 0.005253 / 0.011008 (-0.005755) | 0.083766 / 0.038508 (0.045257) | 0.086305 / 0.023109 (0.063195) | 0.520171 / 0.275898 (0.244273) | 0.565812 / 0.323480 (0.242332) | 0.006465 / 0.007986 (-0.001520) | 0.004585 / 0.004328 (0.000257) | 0.085344 / 0.004250 (0.081094) | 0.063418 / 0.037052 (0.026366) | 0.519759 / 0.258489 (0.261270) | 0.552770 / 0.293841 (0.258929) | 0.049439 / 0.128546 (-0.079107) | 0.017564 / 0.075646 (-0.058082) | 0.092713 / 0.419271 (-0.326559) | 0.065837 / 0.043533 (0.022305) | 0.516133 / 0.255139 (0.260994) | 0.539813 / 0.283200 (0.256613) | 0.036531 / 0.141683 (-0.105152) | 1.919275 / 1.452155 (0.467121) | 2.039987 / 1.492716 (0.547271) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.297978 / 0.018006 (0.279972) | 0.608243 / 0.000490 (0.607753) | 0.006611 / 0.000200 (0.006411) | 0.000117 / 0.000054 (0.000062) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033909 / 0.037411 (-0.003503) | 0.106370 / 0.014526 (0.091844) | 0.119032 / 0.176557 (-0.057524) | 0.180319 / 0.737135 (-0.556816) | 0.122826 / 0.296338 (-0.173513) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.639265 / 0.215209 (0.424056) | 6.248430 / 2.077655 (4.170775) | 2.944760 / 1.504120 (1.440640) | 2.654005 / 1.541195 (1.112811) | 2.733625 / 1.468490 (1.265134) | 0.837172 / 4.584777 (-3.747605) | 5.245084 / 3.745712 (1.499372) | 4.722614 / 5.269862 (-0.547248) | 3.008286 / 4.565676 (-1.557391) | 0.102340 / 0.424275 (-0.321935) | 0.009433 / 0.007607 (0.001826) | 0.762991 / 0.226044 (0.536946) | 7.385020 / 2.268929 (5.116092) | 3.787648 / 55.444624 (-51.656977) | 3.234345 / 6.876477 (-3.642132) | 3.394444 / 2.142072 (1.252371) | 1.023472 / 4.805227 (-3.781756) | 0.208199 / 6.500664 (-6.292465) | 0.081513 / 0.075469 (0.006043) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.795864 / 1.841788 (-0.045923) | 25.270852 / 8.074308 (17.196544) | 23.356413 / 10.191392 (13.165021) | 0.228002 / 0.680424 (-0.452422) | 0.031851 / 0.534201 (-0.502350) | 0.499424 / 0.579283 (-0.079859) | 0.588027 / 0.434364 (0.153664) | 0.581746 / 0.540337 (0.041408) | 0.814183 / 1.386936 (-0.572753) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#33ee536876a667403ee44574bd685073261c4903 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006477 / 0.011353 (-0.004876) | 0.003878 / 0.011008 (-0.007130) | 0.084085 / 0.038508 (0.045577) | 0.071297 / 0.023109 (0.048188) | 0.309176 / 0.275898 (0.033278) | 0.342830 / 0.323480 (0.019350) | 0.005189 / 0.007986 (-0.002796) | 0.003263 / 0.004328 (-0.001065) | 0.063920 / 0.004250 (0.059670) | 0.052233 / 0.037052 (0.015180) | 0.324830 / 0.258489 (0.066341) | 0.357956 / 0.293841 (0.064115) | 0.030459 / 0.128546 (-0.098087) | 0.008350 / 0.075646 (-0.067297) | 0.287330 / 0.419271 (-0.131942) | 0.051005 / 0.043533 (0.007473) | 0.309227 / 0.255139 (0.054088) | 0.346184 / 0.283200 (0.062984) | 0.023961 / 0.141683 (-0.117722) | 1.463983 / 1.452155 (0.011829) | 1.573036 / 1.492716 (0.080319) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.205653 / 0.018006 (0.187647) | 0.457336 / 0.000490 (0.456846) | 0.005347 / 0.000200 (0.005147) | 0.000079 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028080 / 0.037411 (-0.009332) | 0.081755 / 0.014526 (0.067229) | 0.095716 / 0.176557 (-0.080841) | 0.151340 / 0.737135 (-0.585795) | 0.097174 / 0.296338 (-0.199164) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.390725 / 0.215209 (0.175516) | 3.899114 / 2.077655 (1.821459) | 1.895352 / 1.504120 (0.391232) | 1.716072 / 1.541195 (0.174877) | 1.784952 / 1.468490 (0.316462) | 0.477247 / 4.584777 (-4.107530) | 3.606641 / 3.745712 (-0.139071) | 3.203337 / 5.269862 (-2.066524) | 2.017003 / 4.565676 (-2.548674) | 0.056182 / 0.424275 (-0.368094) | 0.007508 / 0.007607 (-0.000099) | 0.461965 / 0.226044 (0.235921) | 4.605926 / 2.268929 (2.336997) | 2.466695 / 55.444624 (-52.977929) | 2.136376 / 6.876477 (-4.740100) | 2.277334 / 2.142072 (0.135261) | 0.576119 / 4.805227 (-4.229109) | 0.131497 / 6.500664 (-6.369167) | 0.060068 / 0.075469 (-0.015401) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.262681 / 1.841788 (-0.579107) | 19.411572 / 8.074308 (11.337264) | 14.383421 / 10.191392 (4.192029) | 0.166115 / 0.680424 (-0.514308) | 0.018366 / 0.534201 (-0.515835) | 0.393903 / 0.579283 (-0.185380) | 0.408788 / 0.434364 (-0.025576) | 0.461796 / 0.540337 (-0.078541) | 0.628460 / 1.386936 (-0.758476) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006501 / 0.011353 (-0.004852) | 0.003915 / 0.011008 (-0.007093) | 0.065245 / 0.038508 (0.026737) | 0.073146 / 0.023109 (0.050037) | 0.363537 / 0.275898 (0.087639) | 0.391571 / 0.323480 (0.068092) | 0.005181 / 0.007986 (-0.002805) | 0.003272 / 0.004328 (-0.001056) | 0.065060 / 0.004250 (0.060810) | 0.054302 / 0.037052 (0.017249) | 0.361571 / 0.258489 (0.103082) | 0.400221 / 0.293841 (0.106380) | 0.030762 / 0.128546 (-0.097784) | 0.008449 / 0.075646 (-0.067197) | 0.071148 / 0.419271 (-0.348123) | 0.048111 / 0.043533 (0.004578) | 0.360327 / 0.255139 (0.105188) | 0.379073 / 0.283200 (0.095874) | 0.024367 / 0.141683 (-0.117316) | 1.451080 / 1.452155 (-0.001074) | 1.510818 / 1.492716 (0.018102) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267078 / 0.018006 (0.249072) | 0.454074 / 0.000490 (0.453584) | 0.015055 / 0.000200 (0.014855) | 0.000129 / 0.000054 (0.000075) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030916 / 0.037411 (-0.006496) | 0.089212 / 0.014526 (0.074686) | 0.100005 / 0.176557 (-0.076552) | 0.155100 / 0.737135 (-0.582035) | 0.101759 / 0.296338 (-0.194580) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.412826 / 0.215209 (0.197616) | 4.122520 / 2.077655 (2.044865) | 2.107870 / 1.504120 (0.603750) | 1.911936 / 1.541195 (0.370741) | 1.984936 / 1.468490 (0.516446) | 0.483835 / 4.584777 (-4.100942) | 3.641860 / 3.745712 (-0.103852) | 3.220540 / 5.269862 (-2.049322) | 2.015521 / 4.565676 (-2.550155) | 0.056913 / 0.424275 (-0.367362) | 0.007285 / 0.007607 (-0.000322) | 0.484886 / 0.226044 (0.258842) | 4.854734 / 2.268929 (2.585805) | 2.593550 / 55.444624 (-52.851074) | 2.233904 / 6.876477 (-4.642572) | 2.438858 / 2.142072 (0.296785) | 0.580880 / 4.805227 (-4.224347) | 0.133891 / 6.500664 (-6.366773) | 0.061678 / 0.075469 (-0.013791) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.336843 / 1.841788 (-0.504944) | 19.731571 / 8.074308 (11.657263) | 14.290228 / 10.191392 (4.098836) | 0.167635 / 0.680424 (-0.512789) | 0.018767 / 0.534201 (-0.515434) | 0.394953 / 0.579283 (-0.184330) | 0.407711 / 0.434364 (-0.026653) | 0.472371 / 0.540337 (-0.067966) | 0.655278 / 1.386936 (-0.731658) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#528b15f775a4724836bdefdc38d932c06484d702 \"CML watermark\")\n" ]

"2023-08-17T21:58:24Z"

"2023-08-17T22:44:59Z"

"2023-08-17T22:36:04Z"

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"2023-08-17T20:49:51Z"

"2023-08-17T20:49:51Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008219 / 0.011353 (-0.003134) | 0.005201 / 0.011008 (-0.005807) | 0.108542 / 0.038508 (0.070034) | 0.076427 / 0.023109 (0.053318) | 0.441257 / 0.275898 (0.165358) | 0.436477 / 0.323480 (0.112997) | 0.006915 / 0.007986 (-0.001071) | 0.004215 / 0.004328 (-0.000113) | 0.072517 / 0.004250 (0.068267) | 0.066906 / 0.037052 (0.029853) | 0.431153 / 0.258489 (0.172664) | 0.413359 / 0.293841 (0.119518) | 0.051112 / 0.128546 (-0.077435) | 0.014664 / 0.075646 (-0.060982) | 0.358385 / 0.419271 (-0.060887) | 0.069682 / 0.043533 (0.026149) | 0.434810 / 0.255139 (0.179671) | 0.484372 / 0.283200 (0.201172) | 0.035731 / 0.141683 (-0.105952) | 1.827648 / 1.452155 (0.375494) | 2.039761 / 1.492716 (0.547045) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.277386 / 0.018006 (0.259379) | 0.599771 / 0.000490 (0.599282) | 0.005033 / 0.000200 (0.004833) | 0.000091 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030652 / 0.037411 (-0.006759) | 0.103435 / 0.014526 (0.088909) | 0.120072 / 0.176557 (-0.056485) | 0.177886 / 0.737135 (-0.559249) | 0.140636 / 0.296338 (-0.155702) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.603729 / 0.215209 (0.388520) | 6.144213 / 2.077655 (4.066558) | 2.785080 / 1.504120 (1.280960) | 2.368958 / 1.541195 (0.827763) | 2.409806 / 1.468490 (0.941316) | 0.836531 / 4.584777 (-3.748246) | 5.154035 / 3.745712 (1.408323) | 4.620224 / 5.269862 (-0.649638) | 2.879441 / 4.565676 (-1.686235) | 0.087322 / 0.424275 (-0.336953) | 0.007698 / 0.007607 (0.000090) | 0.678443 / 0.226044 (0.452399) | 7.431798 / 2.268929 (5.162869) | 3.589905 / 55.444624 (-51.854719) | 2.679349 / 6.876477 (-4.197127) | 3.100569 / 2.142072 (0.958496) | 1.021501 / 4.805227 (-3.783726) | 0.203150 / 6.500664 (-6.297514) | 0.073545 / 0.075469 (-0.001924) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.669981 / 1.841788 (-0.171806) | 23.379274 / 8.074308 (15.304966) | 19.811451 / 10.191392 (9.620059) | 0.197705 / 0.680424 (-0.482719) | 0.030112 / 0.534201 (-0.504089) | 0.501720 / 0.579283 (-0.077563) | 0.582413 / 0.434364 (0.148049) | 0.513261 / 0.540337 (-0.027076) | 0.729710 / 1.386936 (-0.657226) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011493 / 0.011353 (0.000140) | 0.005478 / 0.011008 (-0.005530) | 0.070955 / 0.038508 (0.032447) | 0.073877 / 0.023109 (0.050768) | 0.425765 / 0.275898 (0.149867) | 0.440869 / 0.323480 (0.117389) | 0.008322 / 0.007986 (0.000337) | 0.004004 / 0.004328 (-0.000325) | 0.071968 / 0.004250 (0.067718) | 0.060576 / 0.037052 (0.023524) | 0.448731 / 0.258489 (0.190242) | 0.517038 / 0.293841 (0.223197) | 0.051542 / 0.128546 (-0.077005) | 0.013219 / 0.075646 (-0.062427) | 0.077933 / 0.419271 (-0.341339) | 0.072879 / 0.043533 (0.029346) | 0.436553 / 0.255139 (0.181414) | 0.510050 / 0.283200 (0.226850) | 0.037136 / 0.141683 (-0.104547) | 1.535706 / 1.452155 (0.083552) | 1.611909 / 1.492716 (0.119192) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.335648 / 0.018006 (0.317642) | 0.612787 / 0.000490 (0.612297) | 0.021934 / 0.000200 (0.021734) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028164 / 0.037411 (-0.009247) | 0.097686 / 0.014526 (0.083160) | 0.093343 / 0.176557 (-0.083214) | 0.156871 / 0.737135 (-0.580264) | 0.102694 / 0.296338 (-0.193645) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.609348 / 0.215209 (0.394139) | 5.835798 / 2.077655 (3.758144) | 2.792700 / 1.504120 (1.288580) | 2.539597 / 1.541195 (0.998403) | 2.413003 / 1.468490 (0.944513) | 0.882404 / 4.584777 (-3.702372) | 5.170564 / 3.745712 (1.424852) | 4.621663 / 5.269862 (-0.648199) | 3.029683 / 4.565676 (-1.535993) | 0.097061 / 0.424275 (-0.327214) | 0.008940 / 0.007607 (0.001333) | 0.723052 / 0.226044 (0.497007) | 7.484947 / 2.268929 (5.216018) | 3.833049 / 55.444624 (-51.611575) | 3.019606 / 6.876477 (-3.856871) | 3.270503 / 2.142072 (1.128430) | 0.977870 / 4.805227 (-3.827357) | 0.210090 / 6.500664 (-6.290574) | 0.094723 / 0.075469 (0.019254) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.585278 / 1.841788 (-0.256510) | 22.769727 / 8.074308 (14.695419) | 19.503640 / 10.191392 (9.312248) | 0.231996 / 0.680424 (-0.448428) | 0.032641 / 0.534201 (-0.501560) | 0.429833 / 0.579283 (-0.149451) | 0.549606 / 0.434364 (0.115242) | 0.527405 / 0.540337 (-0.012933) | 0.713302 / 1.386936 (-0.673634) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#546c7bb5cbeff0f8673cf60c4432ea167283cc42 \"CML watermark\")\n" ]

"2023-08-17T17:02:11Z"

"2023-08-17T19:24:20Z"

"2023-08-17T19:13:15Z"

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[ "Thanks for reporting, but we can only fix this issue if you can provide a reproducer that consistently reproduces it.", "@mariosasko Ok. What exactly does it mean to provide a reproducer", "To provide a code that reproduces the issue :)", "@mariosasko I complete the above code, is it enough?", "@mariosasko That's all the code, I'm using locally stored data", "Does this error occur even if you change the cache directory (the `cache_dir` parameter in `load_dataset`)?", "@mariosasko I didn't add any parameters for catch. Nor did any cache configuration change." ]

"2023-08-17T15:48:11Z"

"2023-08-22T08:09:56Z"

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[ "@lhoestq ", "`_effective_generator` returns a RNG that takes into account `self._epoch` and the current dataset's base shuffling RNG (which can be set by specifying `seed=` in `.shuffle() for example`).\r\n\r\nTo fix your error you can pass `seed=` to `.shuffle()`. And the shuffling will depend on both this seed and `self._epoch`", "Thanks for the reply" ]

"2023-08-17T10:58:20Z"

"2023-08-17T14:33:15Z"

"2023-08-17T14:33:14Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009288 / 0.011353 (-0.002065) | 0.005950 / 0.011008 (-0.005058) | 0.122376 / 0.038508 (0.083868) | 0.093177 / 0.023109 (0.070068) | 0.448517 / 0.275898 (0.172619) | 0.474999 / 0.323480 (0.151520) | 0.005133 / 0.007986 (-0.002853) | 0.005123 / 0.004328 (0.000795) | 0.085479 / 0.004250 (0.081229) | 0.065613 / 0.037052 (0.028561) | 0.451179 / 0.258489 (0.192690) | 0.516876 / 0.293841 (0.223036) | 0.047536 / 0.128546 (-0.081010) | 0.013894 / 0.075646 (-0.061752) | 0.382149 / 0.419271 (-0.037122) | 0.067380 / 0.043533 (0.023848) | 0.419282 / 0.255139 (0.164143) | 0.482042 / 0.283200 (0.198842) | 0.041230 / 0.141683 (-0.100452) | 1.818127 / 1.452155 (0.365972) | 1.938123 / 1.492716 (0.445406) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271824 / 0.018006 (0.253817) | 0.604933 / 0.000490 (0.604443) | 0.004953 / 0.000200 (0.004753) | 0.000173 / 0.000054 (0.000119) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036682 / 0.037411 (-0.000729) | 0.095604 / 0.014526 (0.081078) | 0.116862 / 0.176557 (-0.059695) | 0.191335 / 0.737135 (-0.545800) | 0.116620 / 0.296338 (-0.179718) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.620735 / 0.215209 (0.405526) | 6.157119 / 2.077655 (4.079465) | 2.848548 / 1.504120 (1.344428) | 2.493731 / 1.541195 (0.952536) | 2.505801 / 1.468490 (1.037311) | 0.837315 / 4.584777 (-3.747462) | 5.360653 / 3.745712 (1.614941) | 4.908863 / 5.269862 (-0.360999) | 3.184672 / 4.565676 (-1.381004) | 0.105687 / 0.424275 (-0.318588) | 0.011350 / 0.007607 (0.003743) | 0.745729 / 0.226044 (0.519684) | 7.431584 / 2.268929 (5.162655) | 3.644670 / 55.444624 (-51.799954) | 2.910159 / 6.876477 (-3.966317) | 3.257137 / 2.142072 (1.115065) | 1.041377 / 4.805227 (-3.763851) | 0.213289 / 6.500664 (-6.287375) | 0.089208 / 0.075469 (0.013739) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.727274 / 1.841788 (-0.114513) | 25.448436 / 8.074308 (17.374128) | 23.016108 / 10.191392 (12.824716) | 0.219454 / 0.680424 (-0.460970) | 0.028531 / 0.534201 (-0.505670) | 0.500231 / 0.579283 (-0.079052) | 0.614631 / 0.434364 (0.180267) | 0.557926 / 0.540337 (0.017588) | 0.786261 / 1.386936 (-0.600675) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008608 / 0.011353 (-0.002745) | 0.006185 / 0.011008 (-0.004823) | 0.089258 / 0.038508 (0.050750) | 0.090109 / 0.023109 (0.067000) | 0.522200 / 0.275898 (0.246302) | 0.559218 / 0.323480 (0.235738) | 0.008983 / 0.007986 (0.000997) | 0.004488 / 0.004328 (0.000159) | 0.083658 / 0.004250 (0.079408) | 0.064962 / 0.037052 (0.027909) | 0.519477 / 0.258489 (0.260988) | 0.573842 / 0.293841 (0.280001) | 0.053984 / 0.128546 (-0.074562) | 0.014665 / 0.075646 (-0.060982) | 0.089438 / 0.419271 (-0.329834) | 0.065756 / 0.043533 (0.022223) | 0.525131 / 0.255139 (0.269992) | 0.568934 / 0.283200 (0.285734) | 0.037308 / 0.141683 (-0.104375) | 1.928790 / 1.452155 (0.476635) | 2.027926 / 1.492716 (0.535209) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.309595 / 0.018006 (0.291588) | 0.615675 / 0.000490 (0.615186) | 0.004869 / 0.000200 (0.004669) | 0.000116 / 0.000054 (0.000061) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033306 / 0.037411 (-0.004105) | 0.104429 / 0.014526 (0.089904) | 0.116989 / 0.176557 (-0.059568) | 0.183638 / 0.737135 (-0.553497) | 0.132624 / 0.296338 (-0.163714) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.644511 / 0.215209 (0.429302) | 6.425544 / 2.077655 (4.347889) | 3.079071 / 1.504120 (1.574951) | 2.720963 / 1.541195 (1.179769) | 2.835607 / 1.468490 (1.367117) | 0.863561 / 4.584777 (-3.721216) | 5.333462 / 3.745712 (1.587750) | 4.843183 / 5.269862 (-0.426678) | 3.106858 / 4.565676 (-1.458819) | 0.106790 / 0.424275 (-0.317485) | 0.008829 / 0.007607 (0.001222) | 0.759003 / 0.226044 (0.532958) | 7.771247 / 2.268929 (5.502318) | 3.896844 / 55.444624 (-51.547780) | 3.246671 / 6.876477 (-3.629806) | 3.486167 / 2.142072 (1.344094) | 1.071290 / 4.805227 (-3.733937) | 0.217972 / 6.500664 (-6.282692) | 0.089848 / 0.075469 (0.014379) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.816048 / 1.841788 (-0.025739) | 25.625084 / 8.074308 (17.550776) | 24.490882 / 10.191392 (14.299490) | 0.242356 / 0.680424 (-0.438067) | 0.027886 / 0.534201 (-0.506315) | 0.496997 / 0.579283 (-0.082286) | 0.613815 / 0.434364 (0.179451) | 0.607132 / 0.540337 (0.066795) | 0.833051 / 1.386936 (-0.553885) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0adfa9ada14c38fce5973b5e3f196a2c46dc9170 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011580 / 0.011353 (0.000227) | 0.004199 / 0.011008 (-0.006809) | 0.084055 / 0.038508 (0.045547) | 0.096824 / 0.023109 (0.073715) | 0.308755 / 0.275898 (0.032857) | 0.341717 / 0.323480 (0.018237) | 0.006018 / 0.007986 (-0.001968) | 0.003597 / 0.004328 (-0.000731) | 0.064953 / 0.004250 (0.060702) | 0.059577 / 0.037052 (0.022525) | 0.316292 / 0.258489 (0.057803) | 0.358991 / 0.293841 (0.065150) | 0.033925 / 0.128546 (-0.094621) | 0.008828 / 0.075646 (-0.066818) | 0.288673 / 0.419271 (-0.130599) | 0.055494 / 0.043533 (0.011961) | 0.311181 / 0.255139 (0.056042) | 0.345220 / 0.283200 (0.062021) | 0.024033 / 0.141683 (-0.117649) | 1.504709 / 1.452155 (0.052554) | 1.587920 / 1.492716 (0.095204) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.301099 / 0.018006 (0.283093) | 0.594497 / 0.000490 (0.594007) | 0.006244 / 0.000200 (0.006044) | 0.000228 / 0.000054 (0.000174) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027663 / 0.037411 (-0.009748) | 0.081767 / 0.014526 (0.067241) | 0.097342 / 0.176557 (-0.079215) | 0.153200 / 0.737135 (-0.583935) | 0.097474 / 0.296338 (-0.198864) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405929 / 0.215209 (0.190719) | 4.045398 / 2.077655 (1.967743) | 2.044669 / 1.504120 (0.540549) | 1.872889 / 1.541195 (0.331694) | 1.911901 / 1.468490 (0.443411) | 0.480939 / 4.584777 (-4.103838) | 3.652833 / 3.745712 (-0.092879) | 3.281659 / 5.269862 (-1.988202) | 2.038023 / 4.565676 (-2.527654) | 0.056501 / 0.424275 (-0.367775) | 0.007571 / 0.007607 (-0.000036) | 0.481053 / 0.226044 (0.255009) | 4.802048 / 2.268929 (2.533119) | 2.560479 / 55.444624 (-52.884145) | 2.164852 / 6.876477 (-4.711625) | 2.374595 / 2.142072 (0.232523) | 0.576309 / 4.805227 (-4.228918) | 0.134831 / 6.500664 (-6.365833) | 0.060649 / 0.075469 (-0.014820) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.254210 / 1.841788 (-0.587578) | 19.826143 / 8.074308 (11.751835) | 14.446391 / 10.191392 (4.254999) | 0.165707 / 0.680424 (-0.514717) | 0.018221 / 0.534201 (-0.515980) | 0.395996 / 0.579283 (-0.183287) | 0.424567 / 0.434364 (-0.009796) | 0.459836 / 0.540337 (-0.080501) | 0.635969 / 1.386936 (-0.750967) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006696 / 0.011353 (-0.004657) | 0.004131 / 0.011008 (-0.006877) | 0.064587 / 0.038508 (0.026079) | 0.079189 / 0.023109 (0.056080) | 0.359977 / 0.275898 (0.084079) | 0.389331 / 0.323480 (0.065851) | 0.005502 / 0.007986 (-0.002483) | 0.003492 / 0.004328 (-0.000837) | 0.064967 / 0.004250 (0.060716) | 0.055953 / 0.037052 (0.018901) | 0.363997 / 0.258489 (0.105508) | 0.398405 / 0.293841 (0.104564) | 0.031292 / 0.128546 (-0.097254) | 0.008693 / 0.075646 (-0.066953) | 0.070451 / 0.419271 (-0.348820) | 0.048965 / 0.043533 (0.005432) | 0.358288 / 0.255139 (0.103149) | 0.379136 / 0.283200 (0.095936) | 0.024364 / 0.141683 (-0.117319) | 1.478998 / 1.452155 (0.026843) | 1.547282 / 1.492716 (0.054566) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.328188 / 0.018006 (0.310182) | 0.525968 / 0.000490 (0.525478) | 0.003782 / 0.000200 (0.003582) | 0.000089 / 0.000054 (0.000034) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032528 / 0.037411 (-0.004883) | 0.087685 / 0.014526 (0.073159) | 0.100684 / 0.176557 (-0.075872) | 0.155944 / 0.737135 (-0.581192) | 0.101949 / 0.296338 (-0.194389) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.418591 / 0.215209 (0.203382) | 4.199235 / 2.077655 (2.121580) | 2.183880 / 1.504120 (0.679760) | 2.024502 / 1.541195 (0.483307) | 2.017435 / 1.468490 (0.548945) | 0.488881 / 4.584777 (-4.095896) | 3.635002 / 3.745712 (-0.110710) | 3.359992 / 5.269862 (-1.909870) | 2.089686 / 4.565676 (-2.475991) | 0.057813 / 0.424275 (-0.366462) | 0.007349 / 0.007607 (-0.000258) | 0.490719 / 0.226044 (0.264674) | 4.859950 / 2.268929 (2.591022) | 2.616711 / 55.444624 (-52.827914) | 2.238671 / 6.876477 (-4.637806) | 2.442262 / 2.142072 (0.300190) | 0.598368 / 4.805227 (-4.206859) | 0.135281 / 6.500664 (-6.365383) | 0.063072 / 0.075469 (-0.012397) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356396 / 1.841788 (-0.485392) | 20.075123 / 8.074308 (12.000815) | 14.191317 / 10.191392 (3.999925) | 0.167691 / 0.680424 (-0.512732) | 0.018290 / 0.534201 (-0.515911) | 0.392881 / 0.579283 (-0.186402) | 0.413665 / 0.434364 (-0.020699) | 0.480766 / 0.540337 (-0.059571) | 0.655625 / 1.386936 (-0.731311) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a46ca9cc138754629be261522301e725c7d14152 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007834 / 0.011353 (-0.003519) | 0.004744 / 0.011008 (-0.006264) | 0.102061 / 0.038508 (0.063553) | 0.089246 / 0.023109 (0.066137) | 0.399936 / 0.275898 (0.124038) | 0.436974 / 0.323480 (0.113494) | 0.004791 / 0.007986 (-0.003195) | 0.005976 / 0.004328 (0.001647) | 0.079336 / 0.004250 (0.075086) | 0.065947 / 0.037052 (0.028894) | 0.403747 / 0.258489 (0.145258) | 0.460249 / 0.293841 (0.166408) | 0.038065 / 0.128546 (-0.090482) | 0.010179 / 0.075646 (-0.065467) | 0.403620 / 0.419271 (-0.015652) | 0.066439 / 0.043533 (0.022906) | 0.412123 / 0.255139 (0.156984) | 0.452121 / 0.283200 (0.168921) | 0.033533 / 0.141683 (-0.108150) | 1.858650 / 1.452155 (0.406495) | 1.916248 / 1.492716 (0.423532) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237180 / 0.018006 (0.219174) | 0.526844 / 0.000490 (0.526354) | 0.004220 / 0.000200 (0.004020) | 0.000123 / 0.000054 (0.000069) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033860 / 0.037411 (-0.003552) | 0.105054 / 0.014526 (0.090528) | 0.116494 / 0.176557 (-0.060063) | 0.185990 / 0.737135 (-0.551145) | 0.119072 / 0.296338 (-0.177266) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.488549 / 0.215209 (0.273340) | 4.884950 / 2.077655 (2.807295) | 2.521819 / 1.504120 (1.017699) | 2.329382 / 1.541195 (0.788188) | 2.413710 / 1.468490 (0.945220) | 0.568325 / 4.584777 (-4.016452) | 4.243505 / 3.745712 (0.497793) | 3.785983 / 5.269862 (-1.483879) | 2.387146 / 4.565676 (-2.178531) | 0.067176 / 0.424275 (-0.357099) | 0.009145 / 0.007607 (0.001538) | 0.571482 / 0.226044 (0.345437) | 5.688822 / 2.268929 (3.419894) | 3.067346 / 55.444624 (-52.377278) | 2.688723 / 6.876477 (-4.187754) | 2.883785 / 2.142072 (0.741713) | 0.679326 / 4.805227 (-4.125901) | 0.156018 / 6.500664 (-6.344646) | 0.070947 / 0.075469 (-0.004522) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.556611 / 1.841788 (-0.285177) | 23.545074 / 8.074308 (15.470766) | 17.125108 / 10.191392 (6.933716) | 0.180180 / 0.680424 (-0.500244) | 0.021420 / 0.534201 (-0.512781) | 0.466888 / 0.579283 (-0.112395) | 0.485746 / 0.434364 (0.051383) | 0.606181 / 0.540337 (0.065843) | 0.776691 / 1.386936 (-0.610245) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007820 / 0.011353 (-0.003533) | 0.004531 / 0.011008 (-0.006478) | 0.076142 / 0.038508 (0.037634) | 0.086367 / 0.023109 (0.063258) | 0.456150 / 0.275898 (0.180252) | 0.499712 / 0.323480 (0.176232) | 0.006545 / 0.007986 (-0.001441) | 0.003760 / 0.004328 (-0.000568) | 0.076400 / 0.004250 (0.072150) | 0.069689 / 0.037052 (0.032637) | 0.459732 / 0.258489 (0.201243) | 0.504217 / 0.293841 (0.210376) | 0.037838 / 0.128546 (-0.090709) | 0.009804 / 0.075646 (-0.065843) | 0.084654 / 0.419271 (-0.334617) | 0.060301 / 0.043533 (0.016768) | 0.452984 / 0.255139 (0.197845) | 0.479956 / 0.283200 (0.196757) | 0.029674 / 0.141683 (-0.112009) | 1.814059 / 1.452155 (0.361904) | 1.878886 / 1.492716 (0.386170) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.326174 / 0.018006 (0.308168) | 0.539722 / 0.000490 (0.539232) | 0.025637 / 0.000200 (0.025437) | 0.000209 / 0.000054 (0.000154) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036328 / 0.037411 (-0.001084) | 0.106369 / 0.014526 (0.091843) | 0.118598 / 0.176557 (-0.057958) | 0.182760 / 0.737135 (-0.554376) | 0.120013 / 0.296338 (-0.176326) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.507328 / 0.215209 (0.292119) | 5.092689 / 2.077655 (3.015034) | 2.962334 / 1.504120 (1.458214) | 2.507699 / 1.541195 (0.966504) | 2.612245 / 1.468490 (1.143755) | 0.568625 / 4.584777 (-4.016152) | 4.296484 / 3.745712 (0.550772) | 4.037788 / 5.269862 (-1.232073) | 2.579826 / 4.565676 (-1.985850) | 0.068558 / 0.424275 (-0.355717) | 0.008916 / 0.007607 (0.001309) | 0.601054 / 0.226044 (0.375010) | 6.016061 / 2.268929 (3.747133) | 3.311880 / 55.444624 (-52.132744) | 2.912926 / 6.876477 (-3.963551) | 3.101465 / 2.142072 (0.959393) | 0.686848 / 4.805227 (-4.118380) | 0.160243 / 6.500664 (-6.340421) | 0.074084 / 0.075469 (-0.001385) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.754343 / 1.841788 (-0.087444) | 24.215302 / 8.074308 (16.140994) | 17.211007 / 10.191392 (7.019615) | 0.188370 / 0.680424 (-0.492054) | 0.028157 / 0.534201 (-0.506044) | 0.490879 / 0.579283 (-0.088404) | 0.501508 / 0.434364 (0.067144) | 0.599719 / 0.540337 (0.059381) | 0.852438 / 1.386936 (-0.534498) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d84cd1d6f51ca75ec5f5c3db3f372f093758cac9 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009736 / 0.011353 (-0.001617) | 0.004761 / 0.011008 (-0.006247) | 0.100069 / 0.038508 (0.061561) | 0.077944 / 0.023109 (0.054835) | 0.419944 / 0.275898 (0.144046) | 0.459803 / 0.323480 (0.136323) | 0.006296 / 0.007986 (-0.001689) | 0.005375 / 0.004328 (0.001047) | 0.089457 / 0.004250 (0.085207) | 0.060585 / 0.037052 (0.023532) | 0.437988 / 0.258489 (0.179499) | 0.482676 / 0.293841 (0.188835) | 0.049126 / 0.128546 (-0.079420) | 0.015043 / 0.075646 (-0.060603) | 0.342500 / 0.419271 (-0.076771) | 0.067088 / 0.043533 (0.023555) | 0.418364 / 0.255139 (0.163225) | 0.458259 / 0.283200 (0.175059) | 0.034091 / 0.141683 (-0.107592) | 1.721589 / 1.452155 (0.269434) | 1.823142 / 1.492716 (0.330426) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212110 / 0.018006 (0.194103) | 0.530957 / 0.000490 (0.530467) | 0.003581 / 0.000200 (0.003382) | 0.000112 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030202 / 0.037411 (-0.007210) | 0.100552 / 0.014526 (0.086026) | 0.108150 / 0.176557 (-0.068407) | 0.173203 / 0.737135 (-0.563932) | 0.108624 / 0.296338 (-0.187715) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.577340 / 0.215209 (0.362131) | 5.794197 / 2.077655 (3.716543) | 2.396285 / 1.504120 (0.892165) | 2.151972 / 1.541195 (0.610777) | 2.109485 / 1.468490 (0.640995) | 0.873906 / 4.584777 (-3.710871) | 5.083302 / 3.745712 (1.337589) | 4.600756 / 5.269862 (-0.669105) | 2.891731 / 4.565676 (-1.673945) | 0.096293 / 0.424275 (-0.327982) | 0.008651 / 0.007607 (0.001044) | 0.719095 / 0.226044 (0.493051) | 7.193225 / 2.268929 (4.924297) | 3.220145 / 55.444624 (-52.224479) | 2.496715 / 6.876477 (-4.379762) | 2.672972 / 2.142072 (0.530900) | 1.031656 / 4.805227 (-3.773571) | 0.207854 / 6.500664 (-6.292810) | 0.074507 / 0.075469 (-0.000962) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.552821 / 1.841788 (-0.288967) | 22.573015 / 8.074308 (14.498707) | 21.074321 / 10.191392 (10.882929) | 0.231911 / 0.680424 (-0.448513) | 0.027761 / 0.534201 (-0.506440) | 0.474644 / 0.579283 (-0.104639) | 0.563780 / 0.434364 (0.129416) | 0.527593 / 0.540337 (-0.012745) | 0.732299 / 1.386936 (-0.654637) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008675 / 0.011353 (-0.002678) | 0.005268 / 0.011008 (-0.005741) | 0.079078 / 0.038508 (0.040570) | 0.073505 / 0.023109 (0.050395) | 0.453982 / 0.275898 (0.178083) | 0.487839 / 0.323480 (0.164359) | 0.005950 / 0.007986 (-0.002035) | 0.003848 / 0.004328 (-0.000481) | 0.076004 / 0.004250 (0.071754) | 0.058410 / 0.037052 (0.021358) | 0.460099 / 0.258489 (0.201610) | 0.514860 / 0.293841 (0.221019) | 0.048843 / 0.128546 (-0.079703) | 0.014275 / 0.075646 (-0.061371) | 0.090243 / 0.419271 (-0.329029) | 0.060092 / 0.043533 (0.016559) | 0.455669 / 0.255139 (0.200530) | 0.484738 / 0.283200 (0.201538) | 0.033012 / 0.141683 (-0.108671) | 1.738854 / 1.452155 (0.286699) | 1.852552 / 1.492716 (0.359835) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245453 / 0.018006 (0.227447) | 0.519929 / 0.000490 (0.519439) | 0.007262 / 0.000200 (0.007062) | 0.000108 / 0.000054 (0.000054) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031446 / 0.037411 (-0.005965) | 0.094236 / 0.014526 (0.079710) | 0.114457 / 0.176557 (-0.062100) | 0.167448 / 0.737135 (-0.569687) | 0.108791 / 0.296338 (-0.187548) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.603331 / 0.215209 (0.388122) | 6.051556 / 2.077655 (3.973902) | 2.797110 / 1.504120 (1.292990) | 2.500517 / 1.541195 (0.959322) | 2.531421 / 1.468490 (1.062931) | 0.852075 / 4.584777 (-3.732702) | 5.034140 / 3.745712 (1.288427) | 4.576573 / 5.269862 (-0.693289) | 2.973541 / 4.565676 (-1.592135) | 0.101303 / 0.424275 (-0.322972) | 0.008467 / 0.007607 (0.000860) | 0.707143 / 0.226044 (0.481098) | 7.262803 / 2.268929 (4.993874) | 3.548841 / 55.444624 (-51.895783) | 2.895975 / 6.876477 (-3.980502) | 3.063521 / 2.142072 (0.921449) | 1.014961 / 4.805227 (-3.790266) | 0.208527 / 6.500664 (-6.292137) | 0.074939 / 0.075469 (-0.000530) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.670708 / 1.841788 (-0.171080) | 22.685227 / 8.074308 (14.610919) | 20.393017 / 10.191392 (10.201625) | 0.239303 / 0.680424 (-0.441121) | 0.027742 / 0.534201 (-0.506459) | 0.467230 / 0.579283 (-0.112053) | 0.564169 / 0.434364 (0.129805) | 0.554859 / 0.540337 (0.014522) | 0.767471 / 1.386936 (-0.619465) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#72a57356a46ded67f4d7a02741141a96061246a8 \"CML watermark\")\n" ]

"2023-08-17T09:49:48Z"

"2023-08-18T13:45:58Z"

"2023-08-18T13:35:13Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006829 / 0.011353 (-0.004524) | 0.004535 / 0.011008 (-0.006473) | 0.085255 / 0.038508 (0.046747) | 0.080861 / 0.023109 (0.057752) | 0.366023 / 0.275898 (0.090125) | 0.403095 / 0.323480 (0.079615) | 0.005615 / 0.007986 (-0.002370) | 0.003830 / 0.004328 (-0.000498) | 0.064502 / 0.004250 (0.060251) | 0.053916 / 0.037052 (0.016863) | 0.366010 / 0.258489 (0.107521) | 0.414565 / 0.293841 (0.120724) | 0.031500 / 0.128546 (-0.097046) | 0.009252 / 0.075646 (-0.066394) | 0.289584 / 0.419271 (-0.129688) | 0.052984 / 0.043533 (0.009451) | 0.352626 / 0.255139 (0.097487) | 0.390964 / 0.283200 (0.107764) | 0.025118 / 0.141683 (-0.116565) | 1.462316 / 1.452155 (0.010161) | 1.565682 / 1.492716 (0.072966) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.294432 / 0.018006 (0.276426) | 0.618366 / 0.000490 (0.617876) | 0.003270 / 0.000200 (0.003071) | 0.000081 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031194 / 0.037411 (-0.006217) | 0.088892 / 0.014526 (0.074366) | 0.102580 / 0.176557 (-0.073977) | 0.159449 / 0.737135 (-0.577686) | 0.104434 / 0.296338 (-0.191905) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.385690 / 0.215209 (0.170481) | 3.832782 / 2.077655 (1.755128) | 1.862521 / 1.504120 (0.358401) | 1.685674 / 1.541195 (0.144479) | 1.724984 / 1.468490 (0.256494) | 0.483700 / 4.584777 (-4.101077) | 3.664154 / 3.745712 (-0.081558) | 3.323023 / 5.269862 (-1.946839) | 2.055958 / 4.565676 (-2.509718) | 0.056990 / 0.424275 (-0.367285) | 0.007674 / 0.007607 (0.000067) | 0.460642 / 0.226044 (0.234598) | 4.609964 / 2.268929 (2.341036) | 2.434868 / 55.444624 (-53.009756) | 2.003347 / 6.876477 (-4.873130) | 2.209520 / 2.142072 (0.067448) | 0.629363 / 4.805227 (-4.175864) | 0.135434 / 6.500664 (-6.365230) | 0.060498 / 0.075469 (-0.014971) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.253917 / 1.841788 (-0.587870) | 19.988953 / 8.074308 (11.914645) | 14.353739 / 10.191392 (4.162347) | 0.165987 / 0.680424 (-0.514437) | 0.018299 / 0.534201 (-0.515902) | 0.395532 / 0.579283 (-0.183751) | 0.418708 / 0.434364 (-0.015656) | 0.460865 / 0.540337 (-0.079472) | 0.633925 / 1.386936 (-0.753011) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006631 / 0.011353 (-0.004722) | 0.004109 / 0.011008 (-0.006899) | 0.065003 / 0.038508 (0.026495) | 0.080407 / 0.023109 (0.057297) | 0.362966 / 0.275898 (0.087068) | 0.389727 / 0.323480 (0.066247) | 0.005588 / 0.007986 (-0.002397) | 0.003517 / 0.004328 (-0.000812) | 0.065821 / 0.004250 (0.061570) | 0.057614 / 0.037052 (0.020561) | 0.367422 / 0.258489 (0.108932) | 0.400706 / 0.293841 (0.106865) | 0.031560 / 0.128546 (-0.096986) | 0.008659 / 0.075646 (-0.066987) | 0.070756 / 0.419271 (-0.348516) | 0.049821 / 0.043533 (0.006288) | 0.360836 / 0.255139 (0.105697) | 0.383981 / 0.283200 (0.100781) | 0.023719 / 0.141683 (-0.117963) | 1.485197 / 1.452155 (0.033043) | 1.544899 / 1.492716 (0.052182) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.336480 / 0.018006 (0.318474) | 0.532839 / 0.000490 (0.532349) | 0.003767 / 0.000200 (0.003567) | 0.000087 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034132 / 0.037411 (-0.003280) | 0.090131 / 0.014526 (0.075605) | 0.104086 / 0.176557 (-0.072471) | 0.158385 / 0.737135 (-0.578751) | 0.106417 / 0.296338 (-0.189922) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.416462 / 0.215209 (0.201253) | 4.160409 / 2.077655 (2.082755) | 2.195355 / 1.504120 (0.691235) | 2.051234 / 1.541195 (0.510040) | 2.012116 / 1.468490 (0.543626) | 0.477414 / 4.584777 (-4.107363) | 3.590326 / 3.745712 (-0.155386) | 3.318490 / 5.269862 (-1.951371) | 2.064124 / 4.565676 (-2.501553) | 0.057040 / 0.424275 (-0.367235) | 0.007283 / 0.007607 (-0.000324) | 0.480490 / 0.226044 (0.254445) | 4.804013 / 2.268929 (2.535084) | 2.625940 / 55.444624 (-52.818685) | 2.231537 / 6.876477 (-4.644939) | 2.441649 / 2.142072 (0.299576) | 0.573207 / 4.805227 (-4.232020) | 0.131685 / 6.500664 (-6.368979) | 0.060112 / 0.075469 (-0.015357) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.358587 / 1.841788 (-0.483200) | 20.457562 / 8.074308 (12.383254) | 14.236304 / 10.191392 (4.044912) | 0.152860 / 0.680424 (-0.527563) | 0.018466 / 0.534201 (-0.515735) | 0.401391 / 0.579283 (-0.177893) | 0.410252 / 0.434364 (-0.024111) | 0.484335 / 0.540337 (-0.056002) | 0.663818 / 1.386936 (-0.723118) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#acac88873abcb585892dc361eb9f6a70a1fd9a59 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007725 / 0.011353 (-0.003628) | 0.004448 / 0.011008 (-0.006560) | 0.098689 / 0.038508 (0.060180) | 0.082919 / 0.023109 (0.059809) | 0.380707 / 0.275898 (0.104809) | 0.452977 / 0.323480 (0.129497) | 0.004430 / 0.007986 (-0.003555) | 0.003712 / 0.004328 (-0.000616) | 0.076675 / 0.004250 (0.072425) | 0.062281 / 0.037052 (0.025228) | 0.403370 / 0.258489 (0.144881) | 0.464557 / 0.293841 (0.170716) | 0.035646 / 0.128546 (-0.092900) | 0.009776 / 0.075646 (-0.065870) | 0.341955 / 0.419271 (-0.077316) | 0.059515 / 0.043533 (0.015983) | 0.388421 / 0.255139 (0.133282) | 0.439496 / 0.283200 (0.156296) | 0.029090 / 0.141683 (-0.112593) | 1.727473 / 1.452155 (0.275319) | 1.810448 / 1.492716 (0.317732) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.221215 / 0.018006 (0.203208) | 0.486660 / 0.000490 (0.486171) | 0.005467 / 0.000200 (0.005267) | 0.000110 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032491 / 0.037411 (-0.004920) | 0.094446 / 0.014526 (0.079920) | 0.110339 / 0.176557 (-0.066217) | 0.175004 / 0.737135 (-0.562131) | 0.109209 / 0.296338 (-0.187129) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.453966 / 0.215209 (0.238757) | 4.515842 / 2.077655 (2.438187) | 2.240512 / 1.504120 (0.736392) | 2.059911 / 1.541195 (0.518717) | 2.150635 / 1.468490 (0.682145) | 0.564509 / 4.584777 (-4.020268) | 4.055208 / 3.745712 (0.309496) | 3.614084 / 5.269862 (-1.655778) | 2.295760 / 4.565676 (-2.269917) | 0.066507 / 0.424275 (-0.357768) | 0.008909 / 0.007607 (0.001302) | 0.542604 / 0.226044 (0.316560) | 5.412162 / 2.268929 (3.143233) | 2.758757 / 55.444624 (-52.685867) | 2.430693 / 6.876477 (-4.445784) | 2.669866 / 2.142072 (0.527793) | 0.681756 / 4.805227 (-4.123471) | 0.156524 / 6.500664 (-6.344140) | 0.069499 / 0.075469 (-0.005970) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.571591 / 1.841788 (-0.270197) | 22.543437 / 8.074308 (14.469129) | 16.068426 / 10.191392 (5.877034) | 0.169860 / 0.680424 (-0.510564) | 0.021216 / 0.534201 (-0.512985) | 0.468745 / 0.579283 (-0.110538) | 0.475924 / 0.434364 (0.041560) | 0.535574 / 0.540337 (-0.004763) | 0.733823 / 1.386936 (-0.653113) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008038 / 0.011353 (-0.003315) | 0.004565 / 0.011008 (-0.006443) | 0.076892 / 0.038508 (0.038384) | 0.089559 / 0.023109 (0.066450) | 0.456752 / 0.275898 (0.180854) | 0.497282 / 0.323480 (0.173802) | 0.005991 / 0.007986 (-0.001995) | 0.003784 / 0.004328 (-0.000545) | 0.076339 / 0.004250 (0.072089) | 0.066050 / 0.037052 (0.028998) | 0.462708 / 0.258489 (0.204219) | 0.503711 / 0.293841 (0.209870) | 0.037098 / 0.128546 (-0.091448) | 0.009869 / 0.075646 (-0.065777) | 0.083678 / 0.419271 (-0.335594) | 0.058166 / 0.043533 (0.014633) | 0.461839 / 0.255139 (0.206700) | 0.481546 / 0.283200 (0.198347) | 0.027755 / 0.141683 (-0.113928) | 1.738490 / 1.452155 (0.286335) | 1.832276 / 1.492716 (0.339560) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.329935 / 0.018006 (0.311929) | 0.497438 / 0.000490 (0.496949) | 0.034644 / 0.000200 (0.034444) | 0.000199 / 0.000054 (0.000145) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035427 / 0.037411 (-0.001984) | 0.105689 / 0.014526 (0.091163) | 0.117706 / 0.176557 (-0.058850) | 0.177862 / 0.737135 (-0.559273) | 0.116791 / 0.296338 (-0.179547) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.484851 / 0.215209 (0.269642) | 4.804346 / 2.077655 (2.726691) | 2.494801 / 1.504120 (0.990681) | 2.320185 / 1.541195 (0.778990) | 2.374090 / 1.468490 (0.905600) | 0.567397 / 4.584777 (-4.017380) | 4.087402 / 3.745712 (0.341690) | 3.794245 / 5.269862 (-1.475616) | 2.378481 / 4.565676 (-2.187195) | 0.068228 / 0.424275 (-0.356047) | 0.008740 / 0.007607 (0.001133) | 0.574876 / 0.226044 (0.348832) | 5.742644 / 2.268929 (3.473716) | 3.047661 / 55.444624 (-52.396963) | 2.729742 / 6.876477 (-4.146735) | 2.852510 / 2.142072 (0.710438) | 0.679450 / 4.805227 (-4.125777) | 0.156162 / 6.500664 (-6.344502) | 0.074051 / 0.075469 (-0.001418) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.576182 / 1.841788 (-0.265605) | 23.298147 / 8.074308 (15.223839) | 16.344621 / 10.191392 (6.153229) | 0.167571 / 0.680424 (-0.512852) | 0.021423 / 0.534201 (-0.512778) | 0.464511 / 0.579283 (-0.114772) | 0.453257 / 0.434364 (0.018893) | 0.563439 / 0.540337 (0.023102) | 0.764759 / 1.386936 (-0.622177) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e8dc4b32b0d91bdb0971f8203ee37e6588c7770e \"CML watermark\")\n", "This should also fix https://github.com/huggingface/datasets/issues/6140, so please link it with this PR before merging.", "Done !", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006719 / 0.011353 (-0.004634) | 0.004299 / 0.011008 (-0.006709) | 0.085296 / 0.038508 (0.046788) | 0.085144 / 0.023109 (0.062035) | 0.361703 / 0.275898 (0.085805) | 0.397721 / 0.323480 (0.074241) | 0.005920 / 0.007986 (-0.002065) | 0.003853 / 0.004328 (-0.000476) | 0.065633 / 0.004250 (0.061383) | 0.057000 / 0.037052 (0.019947) | 0.379981 / 0.258489 (0.121492) | 0.419041 / 0.293841 (0.125200) | 0.031225 / 0.128546 (-0.097322) | 0.008868 / 0.075646 (-0.066779) | 0.288808 / 0.419271 (-0.130463) | 0.052391 / 0.043533 (0.008859) | 0.362349 / 0.255139 (0.107210) | 0.399858 / 0.283200 (0.116658) | 0.025843 / 0.141683 (-0.115840) | 1.498988 / 1.452155 (0.046834) | 1.547290 / 1.492716 (0.054574) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.278091 / 0.018006 (0.260085) | 0.621794 / 0.000490 (0.621305) | 0.003770 / 0.000200 (0.003570) | 0.000084 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029128 / 0.037411 (-0.008283) | 0.082061 / 0.014526 (0.067536) | 0.101758 / 0.176557 (-0.074799) | 0.155724 / 0.737135 (-0.581411) | 0.102173 / 0.296338 (-0.194165) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387145 / 0.215209 (0.171935) | 3.868262 / 2.077655 (1.790607) | 1.886440 / 1.504120 (0.382320) | 1.723305 / 1.541195 (0.182111) | 1.805411 / 1.468490 (0.336921) | 0.485024 / 4.584777 (-4.099753) | 3.637859 / 3.745712 (-0.107853) | 3.319593 / 5.269862 (-1.950269) | 2.087860 / 4.565676 (-2.477817) | 0.056992 / 0.424275 (-0.367283) | 0.007623 / 0.007607 (0.000016) | 0.468182 / 0.226044 (0.242138) | 4.681112 / 2.268929 (2.412183) | 2.407010 / 55.444624 (-53.037614) | 2.026604 / 6.876477 (-4.849872) | 2.298158 / 2.142072 (0.156086) | 0.581839 / 4.805227 (-4.223388) | 0.132101 / 6.500664 (-6.368563) | 0.060472 / 0.075469 (-0.014997) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.236422 / 1.841788 (-0.605365) | 20.505168 / 8.074308 (12.430860) | 14.356081 / 10.191392 (4.164689) | 0.148808 / 0.680424 (-0.531616) | 0.018433 / 0.534201 (-0.515768) | 0.391323 / 0.579283 (-0.187960) | 0.413142 / 0.434364 (-0.021222) | 0.453484 / 0.540337 (-0.086853) | 0.620771 / 1.386936 (-0.766165) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007030 / 0.011353 (-0.004323) | 0.004430 / 0.011008 (-0.006578) | 0.065578 / 0.038508 (0.027070) | 0.090751 / 0.023109 (0.067642) | 0.389121 / 0.275898 (0.113223) | 0.424657 / 0.323480 (0.101177) | 0.006575 / 0.007986 (-0.001410) | 0.003855 / 0.004328 (-0.000473) | 0.066175 / 0.004250 (0.061925) | 0.063255 / 0.037052 (0.026202) | 0.397161 / 0.258489 (0.138672) | 0.435291 / 0.293841 (0.141450) | 0.031622 / 0.128546 (-0.096925) | 0.008900 / 0.075646 (-0.066747) | 0.071694 / 0.419271 (-0.347577) | 0.049161 / 0.043533 (0.005628) | 0.386214 / 0.255139 (0.131075) | 0.404571 / 0.283200 (0.121372) | 0.024821 / 0.141683 (-0.116862) | 1.489514 / 1.452155 (0.037359) | 1.576139 / 1.492716 (0.083423) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.289884 / 0.018006 (0.271878) | 0.629342 / 0.000490 (0.628852) | 0.004799 / 0.000200 (0.004599) | 0.000160 / 0.000054 (0.000106) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032081 / 0.037411 (-0.005331) | 0.088152 / 0.014526 (0.073626) | 0.107289 / 0.176557 (-0.069267) | 0.164598 / 0.737135 (-0.572537) | 0.108395 / 0.296338 (-0.187944) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426723 / 0.215209 (0.211514) | 4.267719 / 2.077655 (2.190064) | 2.289657 / 1.504120 (0.785537) | 2.117435 / 1.541195 (0.576240) | 2.187292 / 1.468490 (0.718802) | 0.478387 / 4.584777 (-4.106390) | 3.625096 / 3.745712 (-0.120616) | 3.408036 / 5.269862 (-1.861826) | 2.124117 / 4.565676 (-2.441559) | 0.056537 / 0.424275 (-0.367738) | 0.007489 / 0.007607 (-0.000118) | 0.502434 / 0.226044 (0.276389) | 5.025357 / 2.268929 (2.756428) | 2.740554 / 55.444624 (-52.704070) | 2.418841 / 6.876477 (-4.457635) | 2.730764 / 2.142072 (0.588691) | 0.600013 / 4.805227 (-4.205214) | 0.133039 / 6.500664 (-6.367625) | 0.061466 / 0.075469 (-0.014003) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.330211 / 1.841788 (-0.511577) | 21.092100 / 8.074308 (13.017792) | 14.463054 / 10.191392 (4.271662) | 0.154149 / 0.680424 (-0.526274) | 0.018891 / 0.534201 (-0.515310) | 0.393078 / 0.579283 (-0.186205) | 0.415279 / 0.434364 (-0.019085) | 0.479469 / 0.540337 (-0.060868) | 0.659953 / 1.386936 (-0.726983) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5ca2ba050340829b4dd44791afc15db0d82a3276 \"CML watermark\")\n" ]

"2023-08-17T09:17:05Z"

"2023-08-17T20:46:25Z"

"2023-08-17T20:37:19Z"

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[]

[ "@lhoestq ", "Makes sense, I guess this can be fixed in the load_dataset_builder method.\r\nIt concerns every packaged builder I think (see values in `_PACKAGED_DATASETS_MODULES`)", "I think the behavior is related to these lines, which short circuited the error handling.\r\nhttps://github.com/huggingface/datasets/blob/664a1cb72ea1e6ef7c47e671e2686ca4a35e8d63/src/datasets/load.py#L946-L952\r\n\r\nSo should data_dir be checked here or still delegating to actual `DatasetModule`? In that case, how to properly set `data_files` here.", "This is location in PackagedDatasetModuleFactory.get_module seems the be the right place to check if at least data_dir or data_files are passed" ]

"2023-08-16T04:38:09Z"

"2023-08-17T13:45:18Z"

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[]

[ "`Dataset.sort` essentially does the same thing except it uses `pyarrow.compute.sort_indices` which doesn't involve copying the data into python objects (saving memory)\r\n\r\n```python\r\nsort_keys = [(col, \"ascending\") for col in column_names]\r\nindices = pc.sort_indices(self.data, sort_keys=sort_keys)\r\nreturn self.select(indices)\r\n```", "Ok interesting, I'll continue debugging to see what is going wrong on my end." ]

"2023-08-15T14:02:31Z"

"2023-08-21T14:38:26Z"

"2023-08-21T14:38:25Z"

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[]

[ "```\r\n dataset = IterableDataset(dataset) if type(dataset) != IterableDataset else dataset # to force dataset.take(batch_size) to work in non-streaming mode\r\n ```\r\n", "hf discuss: https://discuss.huggingface.co/t/how-does-one-make-dataset-take-512-work-with-streaming-false-with-hugging-face-data-set/50770", "so: https://stackoverflow.com/questions/76902824/how-does-one-make-dataset-take512-work-with-streaming-false-with-hugging-fac", "Feel free to work on this. In addition, `IterableDataset` supports `skip`, so we should also add this method to `Dataset`." ]

"2023-08-15T00:17:51Z"

"2023-08-17T13:49:37Z"

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[ "Looks like this regression was introduced in `datasets==2.13.0` (`2.12.0` could load a subset of columns)\r\n\r\nThis does not appear to be fixed by https://github.com/huggingface/datasets/pull/6045 (bug still exists on `main`)" ]

"2023-08-14T23:28:22Z"

"2023-08-17T22:36:05Z"

"2023-08-17T22:36:05Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006818 / 0.011353 (-0.004534) | 0.004166 / 0.011008 (-0.006842) | 0.086756 / 0.038508 (0.048248) | 0.084444 / 0.023109 (0.061335) | 0.319249 / 0.275898 (0.043351) | 0.358689 / 0.323480 (0.035209) | 0.004344 / 0.007986 (-0.003641) | 0.003564 / 0.004328 (-0.000765) | 0.065021 / 0.004250 (0.060771) | 0.055991 / 0.037052 (0.018939) | 0.319573 / 0.258489 (0.061084) | 0.373239 / 0.293841 (0.079398) | 0.031431 / 0.128546 (-0.097115) | 0.008671 / 0.075646 (-0.066975) | 0.288484 / 0.419271 (-0.130788) | 0.053501 / 0.043533 (0.009968) | 0.316934 / 0.255139 (0.061795) | 0.354233 / 0.283200 (0.071034) | 0.028088 / 0.141683 (-0.113595) | 1.510905 / 1.452155 (0.058750) | 1.568614 / 1.492716 (0.075898) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.292343 / 0.018006 (0.274337) | 0.592309 / 0.000490 (0.591819) | 0.003850 / 0.000200 (0.003650) | 0.000084 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033510 / 0.037411 (-0.003901) | 0.089546 / 0.014526 (0.075020) | 0.104909 / 0.176557 (-0.071648) | 0.162219 / 0.737135 (-0.574916) | 0.104137 / 0.296338 (-0.192202) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.407993 / 0.215209 (0.192784) | 4.063423 / 2.077655 (1.985768) | 2.050237 / 1.504120 (0.546117) | 1.888939 / 1.541195 (0.347744) | 2.015195 / 1.468490 (0.546704) | 0.492617 / 4.584777 (-4.092160) | 3.595871 / 3.745712 (-0.149841) | 3.320467 / 5.269862 (-1.949395) | 2.099987 / 4.565676 (-2.465690) | 0.058513 / 0.424275 (-0.365762) | 0.007709 / 0.007607 (0.000102) | 0.479277 / 0.226044 (0.253233) | 4.790712 / 2.268929 (2.521783) | 2.517292 / 55.444624 (-52.927332) | 2.167461 / 6.876477 (-4.709016) | 2.432011 / 2.142072 (0.289939) | 0.600537 / 4.805227 (-4.204690) | 0.133538 / 6.500664 (-6.367126) | 0.059621 / 0.075469 (-0.015848) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.280375 / 1.841788 (-0.561413) | 20.777971 / 8.074308 (12.703663) | 14.869539 / 10.191392 (4.678147) | 0.159372 / 0.680424 (-0.521052) | 0.018096 / 0.534201 (-0.516105) | 0.393945 / 0.579283 (-0.185338) | 0.409598 / 0.434364 (-0.024766) | 0.459202 / 0.540337 (-0.081136) | 0.632298 / 1.386936 (-0.754638) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006694 / 0.011353 (-0.004659) | 0.004299 / 0.011008 (-0.006709) | 0.064880 / 0.038508 (0.026372) | 0.083233 / 0.023109 (0.060124) | 0.366488 / 0.275898 (0.090590) | 0.405049 / 0.323480 (0.081569) | 0.005602 / 0.007986 (-0.002384) | 0.003623 / 0.004328 (-0.000705) | 0.064410 / 0.004250 (0.060160) | 0.057962 / 0.037052 (0.020910) | 0.365318 / 0.258489 (0.106829) | 0.403151 / 0.293841 (0.109310) | 0.031285 / 0.128546 (-0.097261) | 0.008867 / 0.075646 (-0.066780) | 0.071137 / 0.419271 (-0.348135) | 0.048398 / 0.043533 (0.004865) | 0.360187 / 0.255139 (0.105048) | 0.383872 / 0.283200 (0.100673) | 0.023232 / 0.141683 (-0.118451) | 1.526980 / 1.452155 (0.074826) | 1.587265 / 1.492716 (0.094549) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.362603 / 0.018006 (0.344596) | 0.557034 / 0.000490 (0.556544) | 0.025303 / 0.000200 (0.025103) | 0.000562 / 0.000054 (0.000508) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030636 / 0.037411 (-0.006775) | 0.088085 / 0.014526 (0.073559) | 0.103238 / 0.176557 (-0.073318) | 0.155208 / 0.737135 (-0.581928) | 0.106661 / 0.296338 (-0.189678) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.413660 / 0.215209 (0.198451) | 4.122717 / 2.077655 (2.045063) | 2.097656 / 1.504120 (0.593536) | 1.931995 / 1.541195 (0.390801) | 2.071497 / 1.468490 (0.603007) | 0.490257 / 4.584777 (-4.094520) | 3.588076 / 3.745712 (-0.157636) | 3.423087 / 5.269862 (-1.846774) | 2.147974 / 4.565676 (-2.417703) | 0.058783 / 0.424275 (-0.365492) | 0.007456 / 0.007607 (-0.000151) | 0.492350 / 0.226044 (0.266305) | 4.935935 / 2.268929 (2.667006) | 2.604217 / 55.444624 (-52.840407) | 2.333723 / 6.876477 (-4.542754) | 2.585293 / 2.142072 (0.443220) | 0.608800 / 4.805227 (-4.196427) | 0.135806 / 6.500664 (-6.364858) | 0.062716 / 0.075469 (-0.012753) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.347359 / 1.841788 (-0.494429) | 21.420505 / 8.074308 (13.346197) | 14.325914 / 10.191392 (4.134522) | 0.159617 / 0.680424 (-0.520806) | 0.018769 / 0.534201 (-0.515432) | 0.399677 / 0.579283 (-0.179606) | 0.402992 / 0.434364 (-0.031372) | 0.484629 / 0.540337 (-0.055709) | 0.656007 / 1.386936 (-0.730929) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ac94bb10d5c00ce8fdaf461eb1ff4b8572cfe956 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007291 / 0.011353 (-0.004062) | 0.004501 / 0.011008 (-0.006508) | 0.097529 / 0.038508 (0.059021) | 0.079257 / 0.023109 (0.056147) | 0.356390 / 0.275898 (0.080492) | 0.390065 / 0.323480 (0.066585) | 0.006071 / 0.007986 (-0.001914) | 0.003783 / 0.004328 (-0.000546) | 0.074598 / 0.004250 (0.070348) | 0.059626 / 0.037052 (0.022574) | 0.395344 / 0.258489 (0.136855) | 0.418564 / 0.293841 (0.124723) | 0.041843 / 0.128546 (-0.086704) | 0.009293 / 0.075646 (-0.066354) | 0.332668 / 0.419271 (-0.086604) | 0.065753 / 0.043533 (0.022220) | 0.357285 / 0.255139 (0.102146) | 0.402974 / 0.283200 (0.119775) | 0.028714 / 0.141683 (-0.112968) | 1.733913 / 1.452155 (0.281759) | 1.802574 / 1.492716 (0.309858) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.253114 / 0.018006 (0.235108) | 0.606338 / 0.000490 (0.605848) | 0.006871 / 0.000200 (0.006671) | 0.000126 / 0.000054 (0.000072) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031850 / 0.037411 (-0.005562) | 0.095148 / 0.014526 (0.080622) | 0.111499 / 0.176557 (-0.065057) | 0.174653 / 0.737135 (-0.562483) | 0.109396 / 0.296338 (-0.186943) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.440442 / 0.215209 (0.225233) | 4.408792 / 2.077655 (2.331137) | 2.149778 / 1.504120 (0.645658) | 1.922430 / 1.541195 (0.381235) | 2.029281 / 1.468490 (0.560791) | 0.611586 / 4.584777 (-3.973191) | 4.204571 / 3.745712 (0.458859) | 3.638194 / 5.269862 (-1.631668) | 2.336146 / 4.565676 (-2.229531) | 0.065383 / 0.424275 (-0.358892) | 0.008441 / 0.007607 (0.000834) | 0.527357 / 0.226044 (0.301313) | 5.247892 / 2.268929 (2.978963) | 2.654005 / 55.444624 (-52.790620) | 2.256596 / 6.876477 (-4.619881) | 2.432191 / 2.142072 (0.290119) | 0.672759 / 4.805227 (-4.132469) | 0.148494 / 6.500664 (-6.352170) | 0.068248 / 0.075469 (-0.007221) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.544250 / 1.841788 (-0.297538) | 21.882016 / 8.074308 (13.807708) | 16.470182 / 10.191392 (6.278790) | 0.166107 / 0.680424 (-0.514317) | 0.021305 / 0.534201 (-0.512896) | 0.445069 / 0.579283 (-0.134214) | 0.500631 / 0.434364 (0.066267) | 0.525801 / 0.540337 (-0.014536) | 0.806534 / 1.386936 (-0.580402) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007322 / 0.011353 (-0.004030) | 0.004206 / 0.011008 (-0.006802) | 0.074827 / 0.038508 (0.036319) | 0.084759 / 0.023109 (0.061650) | 0.421204 / 0.275898 (0.145306) | 0.464442 / 0.323480 (0.140962) | 0.006523 / 0.007986 (-0.001463) | 0.003613 / 0.004328 (-0.000716) | 0.073796 / 0.004250 (0.069545) | 0.066609 / 0.037052 (0.029557) | 0.430108 / 0.258489 (0.171619) | 0.463165 / 0.293841 (0.169324) | 0.036015 / 0.128546 (-0.092532) | 0.009696 / 0.075646 (-0.065951) | 0.083326 / 0.419271 (-0.335946) | 0.056804 / 0.043533 (0.013271) | 0.423333 / 0.255139 (0.168194) | 0.450538 / 0.283200 (0.167338) | 0.027067 / 0.141683 (-0.114616) | 1.700563 / 1.452155 (0.248408) | 1.748738 / 1.492716 (0.256021) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.395682 / 0.018006 (0.377675) | 0.540192 / 0.000490 (0.539702) | 0.140049 / 0.000200 (0.139849) | 0.000694 / 0.000054 (0.000639) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036643 / 0.037411 (-0.000769) | 0.104422 / 0.014526 (0.089896) | 0.113072 / 0.176557 (-0.063484) | 0.179561 / 0.737135 (-0.557575) | 0.118620 / 0.296338 (-0.177718) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.476547 / 0.215209 (0.261338) | 4.716009 / 2.077655 (2.638354) | 2.412111 / 1.504120 (0.907991) | 2.246389 / 1.541195 (0.705194) | 2.307058 / 1.468490 (0.838568) | 0.552759 / 4.584777 (-4.032018) | 4.172484 / 3.745712 (0.426771) | 3.848419 / 5.269862 (-1.421443) | 2.310338 / 4.565676 (-2.255339) | 0.071757 / 0.424275 (-0.352518) | 0.011206 / 0.007607 (0.003599) | 0.609526 / 0.226044 (0.383482) | 5.583065 / 2.268929 (3.314136) | 3.081227 / 55.444624 (-52.363397) | 2.637782 / 6.876477 (-4.238695) | 2.887561 / 2.142072 (0.745489) | 0.667227 / 4.805227 (-4.138000) | 0.154421 / 6.500664 (-6.346243) | 0.070772 / 0.075469 (-0.004697) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.605500 / 1.841788 (-0.236288) | 22.872717 / 8.074308 (14.798409) | 15.865333 / 10.191392 (5.673941) | 0.170353 / 0.680424 (-0.510071) | 0.021854 / 0.534201 (-0.512347) | 0.461467 / 0.579283 (-0.117816) | 0.477743 / 0.434364 (0.043379) | 0.597234 / 0.540337 (0.056896) | 0.800416 / 1.386936 (-0.586520) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a7f8d9019e7cb104eac4106bdc6ec0292f0dc61a \"CML watermark\")\n" ]

"2023-08-14T10:43:41Z"

"2023-08-17T08:54:06Z"

"2023-08-17T08:43:58Z"

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[]

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[ "The cause of the error seems to be that `datasets` adds \"gcs://\" as a schema, while `beam` checks only \"gs://\".\r\n\r\ndatasets: https://github.com/huggingface/datasets/blob/c02a44715c036b5261686669727394b1308a3a4b/src/datasets/builder.py#L822\r\n\r\nbeam: [link](https://github.com/apache/beam/blob/25e1a64641b1c8a3c0a6c75c6e86031b87307f22/sdks/python/apache_beam/io/filesystems.py#L98-L101)\r\n```\r\n systems = [\r\n fs for fs in FileSystem.get_all_subclasses()\r\n if fs.scheme() == path_scheme\r\n ]\r\n```" ]

"2023-08-14T03:11:34Z"

"2023-08-14T03:19:43Z"

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[ "I've tried clear the .cache file, doesn't work.", "This issue happens on AWS sagemaker", "This issue can happen if there is a directory named \"glue\" relative to the Python script with the `load_dataset` call (similar issue to this one: https://github.com/huggingface/datasets/issues/5228). Is this the case?" ]

"2023-08-13T05:17:56Z"

"2023-08-17T17:19:41Z"

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[ "This is an issue for the [Datasets repo](https://github.com/huggingface/datasets).", "> This is an issue for the [Datasets repo](https://github.com/huggingface/datasets).\r\n\r\nThanks @sgugger , I guess I will wait for them to address the issue . Looking forward to hearing from them ", "You can use `.push_to_hub(\"<username>/<repo>\")` to push a `Dataset` to the Hub." ]

"2023-08-13T04:42:22Z"

"2023-08-17T14:17:05Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006076 / 0.011353 (-0.005277) | 0.003730 / 0.011008 (-0.007279) | 0.080778 / 0.038508 (0.042270) | 0.062970 / 0.023109 (0.039860) | 0.395864 / 0.275898 (0.119966) | 0.430024 / 0.323480 (0.106544) | 0.004823 / 0.007986 (-0.003162) | 0.002949 / 0.004328 (-0.001379) | 0.062423 / 0.004250 (0.058172) | 0.047343 / 0.037052 (0.010291) | 0.403153 / 0.258489 (0.144664) | 0.443666 / 0.293841 (0.149825) | 0.027798 / 0.128546 (-0.100748) | 0.008056 / 0.075646 (-0.067590) | 0.262260 / 0.419271 (-0.157011) | 0.045958 / 0.043533 (0.002425) | 0.391349 / 0.255139 (0.136210) | 0.421831 / 0.283200 (0.138632) | 0.021837 / 0.141683 (-0.119846) | 1.485509 / 1.452155 (0.033355) | 1.542940 / 1.492716 (0.050224) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.196831 / 0.018006 (0.178825) | 0.435774 / 0.000490 (0.435285) | 0.003647 / 0.000200 (0.003447) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023756 / 0.037411 (-0.013655) | 0.075737 / 0.014526 (0.061211) | 0.303703 / 0.176557 (0.127146) | 0.164862 / 0.737135 (-0.572273) | 0.198483 / 0.296338 (-0.097855) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405220 / 0.215209 (0.190011) | 4.065983 / 2.077655 (1.988328) | 2.043001 / 1.504120 (0.538881) | 1.853318 / 1.541195 (0.312123) | 1.977452 / 1.468490 (0.508962) | 0.500897 / 4.584777 (-4.083880) | 3.065756 / 3.745712 (-0.679956) | 2.924096 / 5.269862 (-2.345765) | 1.876194 / 4.565676 (-2.689482) | 0.057774 / 0.424275 (-0.366501) | 0.006809 / 0.007607 (-0.000798) | 0.470979 / 0.226044 (0.244934) | 4.719546 / 2.268929 (2.450618) | 2.449651 / 55.444624 (-52.994973) | 2.211817 / 6.876477 (-4.664660) | 2.398760 / 2.142072 (0.256687) | 0.590608 / 4.805227 (-4.214619) | 0.125836 / 6.500664 (-6.374829) | 0.060759 / 0.075469 (-0.014710) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243609 / 1.841788 (-0.598179) | 18.836193 / 8.074308 (10.761885) | 13.835053 / 10.191392 (3.643661) | 0.129708 / 0.680424 (-0.550716) | 0.016708 / 0.534201 (-0.517493) | 0.337219 / 0.579283 (-0.242065) | 0.359045 / 0.434364 (-0.075319) | 0.383329 / 0.540337 (-0.157009) | 0.539629 / 1.386936 (-0.847307) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006073 / 0.011353 (-0.005280) | 0.003713 / 0.011008 (-0.007295) | 0.062642 / 0.038508 (0.024134) | 0.062618 / 0.023109 (0.039508) | 0.362029 / 0.275898 (0.086130) | 0.401924 / 0.323480 (0.078445) | 0.004689 / 0.007986 (-0.003297) | 0.002945 / 0.004328 (-0.001384) | 0.062720 / 0.004250 (0.058470) | 0.048901 / 0.037052 (0.011848) | 0.363780 / 0.258489 (0.105291) | 0.405111 / 0.293841 (0.111270) | 0.027738 / 0.128546 (-0.100808) | 0.008046 / 0.075646 (-0.067600) | 0.067752 / 0.419271 (-0.351519) | 0.041955 / 0.043533 (-0.001577) | 0.361615 / 0.255139 (0.106476) | 0.388762 / 0.283200 (0.105562) | 0.021302 / 0.141683 (-0.120380) | 1.473527 / 1.452155 (0.021372) | 1.529753 / 1.492716 (0.037037) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.300446 / 0.018006 (0.282440) | 0.425844 / 0.000490 (0.425354) | 0.054507 / 0.000200 (0.054307) | 0.000282 / 0.000054 (0.000228) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025478 / 0.037411 (-0.011933) | 0.078298 / 0.014526 (0.063772) | 0.087647 / 0.176557 (-0.088909) | 0.138978 / 0.737135 (-0.598157) | 0.088396 / 0.296338 (-0.207942) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.421345 / 0.215209 (0.206136) | 4.209188 / 2.077655 (2.131533) | 2.260731 / 1.504120 (0.756611) | 2.072329 / 1.541195 (0.531134) | 2.086778 / 1.468490 (0.618288) | 0.495425 / 4.584777 (-4.089352) | 2.987519 / 3.745712 (-0.758194) | 2.895106 / 5.269862 (-2.374756) | 1.874637 / 4.565676 (-2.691039) | 0.057080 / 0.424275 (-0.367195) | 0.006402 / 0.007607 (-0.001205) | 0.498233 / 0.226044 (0.272188) | 4.974385 / 2.268929 (2.705457) | 2.671755 / 55.444624 (-52.772870) | 2.356120 / 6.876477 (-4.520357) | 2.531374 / 2.142072 (0.389301) | 0.581955 / 4.805227 (-4.223272) | 0.125491 / 6.500664 (-6.375173) | 0.062267 / 0.075469 (-0.013202) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.307233 / 1.841788 (-0.534555) | 18.929740 / 8.074308 (10.855431) | 14.029693 / 10.191392 (3.838301) | 0.161992 / 0.680424 (-0.518431) | 0.017127 / 0.534201 (-0.517074) | 0.336644 / 0.579283 (-0.242639) | 0.336550 / 0.434364 (-0.097814) | 0.400554 / 0.540337 (-0.139783) | 0.560725 / 1.386936 (-0.826211) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#cb8c5de5145c7e7eee65391cb7f4d92f0d565d62 \"CML watermark\")\n" ]

"2023-08-12T07:00:14Z"

"2023-08-15T17:04:01Z"

"2023-08-15T16:55:24Z"

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[ "related: https://github.com/huggingface/datasets/issues/3504", "another file not found:\r\n```\r\nTraceback (most recent call last):\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/implementations/http.py\", line 417, in _info\r\n await _file_info(\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/implementations/http.py\", line 837, in _file_info\r\n r.raise_for_status()\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/aiohttp/client_reqrep.py\", line 1005, in raise_for_status\r\n raise ClientResponseError(\r\naiohttp.client_exceptions.ClientResponseError: 404, message='Not Found', url=URL('https://the-eye.eu/public/AI/pile_preliminary_components/pile_uspto.tar')\r\n\r\nThe above exception was the direct cause of the following exception:\r\n\r\nTraceback (most recent call last):\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/runpy.py\", line 196, in _run_module_as_main\r\n return _run_code(code, main_globals, None,\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/runpy.py\", line 86, in _run_code\r\n exec(code, run_globals)\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/adapter/../../debugpy/launcher/../../debugpy/__main__.py\", line 39, in <module>\r\n cli.main()\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py\", line 430, in main\r\n run()\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py\", line 284, in run_file\r\n runpy.run_path(target, run_name=\"__main__\")\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py\", line 321, in run_path\r\n return _run_module_code(code, init_globals, run_name,\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py\", line 135, in _run_module_code\r\n _run_code(code, mod_globals, init_globals,\r\n File \"/lfs/ampere1/0/brando9/.vscode-server-insiders/extensions/ms-python.python-2023.14.0/pythonFiles/lib/python/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py\", line 124, in _run_code\r\n exec(code, run_globals)\r\n File \"/lfs/ampere1/0/brando9/beyond-scale-language-data-diversity/src/diversity/div_coeff.py\", line 526, in <module>\r\n experiment_compute_diveristy_coeff_single_dataset_then_combined_datasets_with_domain_weights()\r\n File \"/lfs/ampere1/0/brando9/beyond-scale-language-data-diversity/src/diversity/div_coeff.py\", line 475, in experiment_compute_diveristy_coeff_single_dataset_then_combined_datasets_with_domain_weights\r\n column_names = next(iter(dataset)).keys()\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/datasets/iterable_dataset.py\", line 1353, in __iter__\r\n for key, example in ex_iterable:\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/datasets/iterable_dataset.py\", line 207, in __iter__\r\n yield from self.generate_examples_fn(**self.kwargs)\r\n File \"/lfs/ampere1/0/brando9/.cache/huggingface/modules/datasets_modules/datasets/EleutherAI--pile/ebea56d358e91cf4d37b0fde361d563bed1472fbd8221a21b38fc8bb4ba554fb/pile.py\", line 257, in _generate_examples\r\n for path, file in files[subset]:\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py\", line 840, in __iter__\r\n yield from self.generator(*self.args, **self.kwargs)\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py\", line 891, in _iter_from_urlpath\r\n with xopen(urlpath, \"rb\", download_config=download_config) as f:\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py\", line 496, in xopen\r\n file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/core.py\", line 134, in open\r\n return self.__enter__()\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/core.py\", line 102, in __enter__\r\n f = self.fs.open(self.path, mode=mode)\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/spec.py\", line 1241, in open\r\n f = self._open(\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/implementations/http.py\", line 356, in _open\r\n size = size or self.info(path, **kwargs)[\"size\"]\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/asyn.py\", line 121, in wrapper\r\n return sync(self.loop, func, *args, **kwargs)\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/asyn.py\", line 106, in sync\r\n raise return_result\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/asyn.py\", line 61, in _runner\r\n result[0] = await coro\r\n File \"/lfs/ampere1/0/brando9/miniconda/envs/beyond_scale/lib/python3.10/site-packages/fsspec/implementations/http.py\", line 430, in _info\r\n raise FileNotFoundError(url) from exc\r\nFileNotFoundError: https://the-eye.eu/public/AI/pile_preliminary_components/pile_uspto.tar\r\n```", "```\r\nFileNotFoundError: https://the-eye.eu/public/AI/pile_preliminary_components/pile_uspto.tar\r\n```\r\nmost relevant line I think.", "link to tweet: https://twitter.com/BrandoHablando/status/1690081313519489024?s=20 about issue", "so: https://stackoverflow.com/questions/76891189/how-to-download-data-from-hugging-face-that-is-visible-on-the-data-viewer-but-th", "this seems to work but it's rather annoying.\r\n\r\nSummary of how to make it work:\r\n1. get urls to parquet files into a list\r\n2. load list to load_dataset via `load_dataset('parquet', data_files=urls)` (note api names to hf are really confusing sometimes)\r\n3. then it should work, print a batch of text.\r\n\r\npresudo code\r\n```python\r\nurls_hacker_news = [\r\n \"https://huggingface.co/datasets/EleutherAI/pile/resolve/refs%2Fconvert%2Fparquet/hacker_news/pile-train-00000-of-00004.parquet\",\r\n \"https://huggingface.co/datasets/EleutherAI/pile/resolve/refs%2Fconvert%2Fparquet/hacker_news/pile-train-00001-of-00004.parquet\",\r\n \"https://huggingface.co/datasets/EleutherAI/pile/resolve/refs%2Fconvert%2Fparquet/hacker_news/pile-train-00002-of-00004.parquet\",\r\n \"https://huggingface.co/datasets/EleutherAI/pile/resolve/refs%2Fconvert%2Fparquet/hacker_news/pile-train-00003-of-00004.parquet\"\r\n]\r\n\r\n...\r\n\r\n\r\n # streaming = False\r\n from diversity.pile_subset_urls import urls_hacker_news\r\n path, name, data_files = 'parquet', 'hacker_news', urls_hacker_news\r\n # not changing\r\n batch_size = 512\r\n today = datetime.datetime.now().strftime('%Y-m%m-d%d-t%Hh_%Mm_%Ss')\r\n run_name = f'{path} div_coeff_{num_batches=} ({today=} ({name=}) {data_mixture_name=} {probabilities=})'\r\n print(f'{run_name=}')\r\n\r\n # - Init wandb\r\n debug: bool = mode == 'dryrun'\r\n run = wandb.init(mode=mode, project=\"beyond-scale\", name=run_name, save_code=True)\r\n wandb.config.update({\"num_batches\": num_batches, \"path\": path, \"name\": name, \"today\": today, 'probabilities': probabilities, 'batch_size': batch_size, 'debug': debug, 'data_mixture_name': data_mixture_name, 'streaming': streaming, 'data_files': data_files})\r\n # run.notify_on_failure() # https://community.wandb.ai/t/how-do-i-set-the-wandb-alert-programatically-for-my-current-run/4891\r\n print(f'{debug=}')\r\n print(f'{wandb.config=}')\r\n\r\n # -- Get probe network\r\n from datasets import load_dataset\r\n import torch\r\n from transformers import GPT2Tokenizer, GPT2LMHeadModel\r\n\r\n tokenizer = GPT2Tokenizer.from_pretrained(\"gpt2\")\r\n if tokenizer.pad_token_id is None:\r\n tokenizer.pad_token = tokenizer.eos_token\r\n probe_network = GPT2LMHeadModel.from_pretrained(\"gpt2\")\r\n device = torch.device(f\"cuda:{0}\" if torch.cuda.is_available() else \"cpu\")\r\n probe_network = probe_network.to(device)\r\n\r\n # -- Get data set\r\n def my_load_dataset(path, name):\r\n print(f'{path=} {name=} {streaming=}')\r\n if path == 'json' or path == 'bin' or path == 'csv':\r\n print(f'{data_files_prefix+name=}')\r\n return load_dataset(path, data_files=data_files_prefix+name, streaming=streaming, split=\"train\").with_format(\"torch\")\r\n elif path == 'parquet':\r\n print(f'{data_files=}')\r\n return load_dataset(path, data_files=data_files, streaming=streaming, split=\"train\").with_format(\"torch\")\r\n else:\r\n return load_dataset(path, name, streaming=streaming, split=\"train\").with_format(\"torch\")\r\n # - get data set for real now\r\n if isinstance(path, str):\r\n dataset = my_load_dataset(path, name)\r\n else:\r\n print('-- interleaving datasets')\r\n datasets = [my_load_dataset(path, name).with_format(\"torch\") for path, name in zip(path, name)]\r\n [print(f'{dataset.description=}') for dataset in datasets]\r\n dataset = interleave_datasets(datasets, probabilities)\r\n print(f'{dataset=}')\r\n batch = dataset.take(batch_size)\r\n print(f'{next(iter(batch))=}')\r\n column_names = next(iter(batch)).keys()\r\n print(f'{column_names=}')\r\n\r\n # - Prepare functions to tokenize batch\r\n def preprocess(examples):\r\n return tokenizer(examples[\"text\"], padding=\"max_length\", max_length=128, truncation=True, return_tensors=\"pt\")\r\n remove_columns = column_names # remove all keys that are not tensors to avoid bugs in collate function in task2vec's pytorch data loader\r\n def map(batch):\r\n return batch.map(preprocess, batched=True, remove_columns=remove_columns)\r\n tokenized_batch = map(batch)\r\n print(f'{next(iter(tokenized_batch))=}')\r\n```\r\n\r\nhttps://stackoverflow.com/questions/76891189/how-to-download-data-from-hugging-face-that-is-visible-on-the-data-viewer-but-th/76902681#76902681\r\n\r\nhttps://discuss.huggingface.co/t/how-to-download-data-from-hugging-face-that-is-visible-on-the-data-viewer-but-the-files-are-not-available/50555/5?u=severo" ]

"2023-08-11T19:05:25Z"

"2023-08-14T23:28:38Z"

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[ "@severo ", "It seems that some parquet files have additional columns.\r\n\r\nI ran a scan and found that two files have the additional `__id__` column:\r\n\r\n1. `hf://datasets/bigcode/the-stack-dedup/data/numpy/data-00000-of-00001.parquet`\r\n2. `hf://datasets/bigcode/the-stack-dedup/data/omgrofl/data-00000-of-00001.parquet`\r\n\r\nWe should open a PR to fix those two files", "I opened https://huggingface.co/datasets/bigcode/the-stack-dedup/discussions/31", "The files have been fixed ! I'm closing this one but feel free to re-open if you still have the issue" ]

"2023-08-11T05:10:49Z"

"2023-08-17T09:26:13Z"

"2023-08-17T09:26:13Z"

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[ "Hi! I cannot reproduce this error on my machine or in Colab. Which version of `fsspec` do you have installed?" ]

"2023-08-11T02:40:32Z"

"2023-08-17T18:09:23Z"

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"2023-08-10T15:07:34Z"

"2023-08-17T20:37:20Z"

"2023-08-17T20:37:20Z"

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[ "Hi, thanks for the suggestion. It's not possible at the moment. The viewer is part of the Hub codebase and only works on public datasets. Also, it relies on [Datasets Server](https://github.com/huggingface/datasets-server/), which prepares the data and provides an API to access the rows, size, etc.\r\n\r\nIf you're interested in hosting your data as a private dataset on the Hub, you might want to look at https://github.com/huggingface/datasets-server/issues/39." ]

"2023-08-10T11:30:00Z"

"2023-08-10T14:37:38Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006536 / 0.011353 (-0.004817) | 0.003890 / 0.011008 (-0.007118) | 0.084044 / 0.038508 (0.045536) | 0.071893 / 0.023109 (0.048784) | 0.346926 / 0.275898 (0.071028) | 0.397487 / 0.323480 (0.074007) | 0.004065 / 0.007986 (-0.003921) | 0.003218 / 0.004328 (-0.001111) | 0.064670 / 0.004250 (0.060420) | 0.052414 / 0.037052 (0.015362) | 0.355413 / 0.258489 (0.096924) | 0.398894 / 0.293841 (0.105053) | 0.030763 / 0.128546 (-0.097783) | 0.008590 / 0.075646 (-0.067056) | 0.286857 / 0.419271 (-0.132415) | 0.051126 / 0.043533 (0.007593) | 0.346125 / 0.255139 (0.090986) | 0.395673 / 0.283200 (0.112474) | 0.025766 / 0.141683 (-0.115917) | 1.466238 / 1.452155 (0.014084) | 1.543117 / 1.492716 (0.050400) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.213210 / 0.018006 (0.195204) | 0.451981 / 0.000490 (0.451491) | 0.003784 / 0.000200 (0.003585) | 0.000096 / 0.000054 (0.000041) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027756 / 0.037411 (-0.009655) | 0.082446 / 0.014526 (0.067920) | 0.095414 / 0.176557 (-0.081142) | 0.151812 / 0.737135 (-0.585323) | 0.096296 / 0.296338 (-0.200042) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383729 / 0.215209 (0.168520) | 3.835126 / 2.077655 (1.757471) | 1.891972 / 1.504120 (0.387852) | 1.719934 / 1.541195 (0.178739) | 1.899980 / 1.468490 (0.431490) | 0.488741 / 4.584777 (-4.096036) | 3.634120 / 3.745712 (-0.111592) | 3.243314 / 5.269862 (-2.026547) | 2.028382 / 4.565676 (-2.537294) | 0.057355 / 0.424275 (-0.366920) | 0.007717 / 0.007607 (0.000110) | 0.459835 / 0.226044 (0.233790) | 4.591793 / 2.268929 (2.322864) | 2.346861 / 55.444624 (-53.097764) | 2.067357 / 6.876477 (-4.809120) | 2.254954 / 2.142072 (0.112882) | 0.587016 / 4.805227 (-4.218211) | 0.133918 / 6.500664 (-6.366746) | 0.060311 / 0.075469 (-0.015158) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.250016 / 1.841788 (-0.591772) | 19.674333 / 8.074308 (11.600025) | 14.522764 / 10.191392 (4.331372) | 0.145741 / 0.680424 (-0.534683) | 0.018593 / 0.534201 (-0.515608) | 0.392833 / 0.579283 (-0.186450) | 0.408194 / 0.434364 (-0.026170) | 0.455164 / 0.540337 (-0.085174) | 0.622722 / 1.386936 (-0.764214) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006583 / 0.011353 (-0.004770) | 0.004008 / 0.011008 (-0.007000) | 0.064688 / 0.038508 (0.026180) | 0.074969 / 0.023109 (0.051860) | 0.360504 / 0.275898 (0.084606) | 0.396926 / 0.323480 (0.073446) | 0.005190 / 0.007986 (-0.002796) | 0.003363 / 0.004328 (-0.000966) | 0.064372 / 0.004250 (0.060122) | 0.054428 / 0.037052 (0.017376) | 0.361204 / 0.258489 (0.102715) | 0.400917 / 0.293841 (0.107077) | 0.031117 / 0.128546 (-0.097429) | 0.008406 / 0.075646 (-0.067241) | 0.069655 / 0.419271 (-0.349617) | 0.048582 / 0.043533 (0.005049) | 0.365396 / 0.255139 (0.110257) | 0.381344 / 0.283200 (0.098145) | 0.023809 / 0.141683 (-0.117874) | 1.472926 / 1.452155 (0.020772) | 1.547298 / 1.492716 (0.054582) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.276912 / 0.018006 (0.258906) | 0.449096 / 0.000490 (0.448607) | 0.018921 / 0.000200 (0.018721) | 0.000111 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030237 / 0.037411 (-0.007174) | 0.088610 / 0.014526 (0.074084) | 0.101529 / 0.176557 (-0.075027) | 0.154070 / 0.737135 (-0.583065) | 0.103471 / 0.296338 (-0.192867) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.416047 / 0.215209 (0.200838) | 4.152374 / 2.077655 (2.074719) | 2.111181 / 1.504120 (0.607061) | 1.943582 / 1.541195 (0.402387) | 2.031729 / 1.468490 (0.563239) | 0.486740 / 4.584777 (-4.098037) | 3.631547 / 3.745712 (-0.114165) | 3.251202 / 5.269862 (-2.018660) | 2.041272 / 4.565676 (-2.524405) | 0.057287 / 0.424275 (-0.366988) | 0.007303 / 0.007607 (-0.000304) | 0.491027 / 0.226044 (0.264982) | 4.906757 / 2.268929 (2.637829) | 2.581694 / 55.444624 (-52.862931) | 2.250996 / 6.876477 (-4.625481) | 2.441771 / 2.142072 (0.299698) | 0.600714 / 4.805227 (-4.204514) | 0.133233 / 6.500664 (-6.367431) | 0.060856 / 0.075469 (-0.014613) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.340062 / 1.841788 (-0.501725) | 19.973899 / 8.074308 (11.899591) | 14.347381 / 10.191392 (4.155989) | 0.166651 / 0.680424 (-0.513773) | 0.018691 / 0.534201 (-0.515510) | 0.393580 / 0.579283 (-0.185703) | 0.409425 / 0.434364 (-0.024939) | 0.474409 / 0.540337 (-0.065929) | 0.649423 / 1.386936 (-0.737514) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c5da68102297c3639207a7901952d2765a4cdb8b \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006593 / 0.011353 (-0.004760) | 0.004123 / 0.011008 (-0.006885) | 0.084424 / 0.038508 (0.045916) | 0.076867 / 0.023109 (0.053758) | 0.309149 / 0.275898 (0.033251) | 0.348572 / 0.323480 (0.025092) | 0.005463 / 0.007986 (-0.002523) | 0.003440 / 0.004328 (-0.000889) | 0.064604 / 0.004250 (0.060353) | 0.053920 / 0.037052 (0.016868) | 0.345221 / 0.258489 (0.086732) | 0.363209 / 0.293841 (0.069368) | 0.031209 / 0.128546 (-0.097337) | 0.008690 / 0.075646 (-0.066956) | 0.288851 / 0.419271 (-0.130421) | 0.052239 / 0.043533 (0.008707) | 0.308643 / 0.255139 (0.053504) | 0.346407 / 0.283200 (0.063207) | 0.023935 / 0.141683 (-0.117748) | 1.469207 / 1.452155 (0.017052) | 1.532855 / 1.492716 (0.040138) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.290885 / 0.018006 (0.272879) | 0.580561 / 0.000490 (0.580071) | 0.004698 / 0.000200 (0.004498) | 0.000286 / 0.000054 (0.000231) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028015 / 0.037411 (-0.009396) | 0.081172 / 0.014526 (0.066646) | 0.096822 / 0.176557 (-0.079735) | 0.151355 / 0.737135 (-0.585781) | 0.098017 / 0.296338 (-0.198321) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384069 / 0.215209 (0.168859) | 3.828635 / 2.077655 (1.750980) | 1.829311 / 1.504120 (0.325192) | 1.672520 / 1.541195 (0.131325) | 1.743944 / 1.468490 (0.275453) | 0.481594 / 4.584777 (-4.103183) | 3.556204 / 3.745712 (-0.189509) | 3.279499 / 5.269862 (-1.990363) | 2.033243 / 4.565676 (-2.532434) | 0.056525 / 0.424275 (-0.367750) | 0.007717 / 0.007607 (0.000109) | 0.466815 / 0.226044 (0.240771) | 4.657022 / 2.268929 (2.388094) | 2.438600 / 55.444624 (-53.006024) | 2.097999 / 6.876477 (-4.778478) | 2.263122 / 2.142072 (0.121049) | 0.636001 / 4.805227 (-4.169226) | 0.147727 / 6.500664 (-6.352937) | 0.059293 / 0.075469 (-0.016176) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243111 / 1.841788 (-0.598677) | 19.558379 / 8.074308 (11.484071) | 14.141017 / 10.191392 (3.949625) | 0.169840 / 0.680424 (-0.510583) | 0.017912 / 0.534201 (-0.516289) | 0.391325 / 0.579283 (-0.187958) | 0.417169 / 0.434364 (-0.017195) | 0.457129 / 0.540337 (-0.083209) | 0.629907 / 1.386936 (-0.757029) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006687 / 0.011353 (-0.004666) | 0.004165 / 0.011008 (-0.006844) | 0.064738 / 0.038508 (0.026230) | 0.077286 / 0.023109 (0.054177) | 0.364236 / 0.275898 (0.088338) | 0.393228 / 0.323480 (0.069748) | 0.005451 / 0.007986 (-0.002535) | 0.003547 / 0.004328 (-0.000781) | 0.065761 / 0.004250 (0.061510) | 0.056526 / 0.037052 (0.019474) | 0.365523 / 0.258489 (0.107034) | 0.403331 / 0.293841 (0.109490) | 0.030900 / 0.128546 (-0.097646) | 0.008757 / 0.075646 (-0.066889) | 0.070961 / 0.419271 (-0.348311) | 0.048394 / 0.043533 (0.004861) | 0.365908 / 0.255139 (0.110769) | 0.381197 / 0.283200 (0.097998) | 0.022940 / 0.141683 (-0.118743) | 1.487909 / 1.452155 (0.035754) | 1.532931 / 1.492716 (0.040215) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.317506 / 0.018006 (0.299500) | 0.513391 / 0.000490 (0.512902) | 0.005464 / 0.000200 (0.005264) | 0.000214 / 0.000054 (0.000159) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032289 / 0.037411 (-0.005122) | 0.090157 / 0.014526 (0.075631) | 0.103514 / 0.176557 (-0.073043) | 0.158236 / 0.737135 (-0.578899) | 0.106554 / 0.296338 (-0.189784) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.406455 / 0.215209 (0.191246) | 4.061563 / 2.077655 (1.983908) | 2.082201 / 1.504120 (0.578081) | 1.914433 / 1.541195 (0.373238) | 2.039342 / 1.468490 (0.570852) | 0.478444 / 4.584777 (-4.106333) | 3.599755 / 3.745712 (-0.145957) | 3.294453 / 5.269862 (-1.975409) | 2.028519 / 4.565676 (-2.537158) | 0.056118 / 0.424275 (-0.368157) | 0.007325 / 0.007607 (-0.000282) | 0.493177 / 0.226044 (0.267132) | 4.926218 / 2.268929 (2.657289) | 2.605033 / 55.444624 (-52.839591) | 2.239933 / 6.876477 (-4.636544) | 2.454210 / 2.142072 (0.312137) | 0.571905 / 4.805227 (-4.233322) | 0.133251 / 6.500664 (-6.367413) | 0.062422 / 0.075469 (-0.013047) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352752 / 1.841788 (-0.489036) | 20.265109 / 8.074308 (12.190801) | 14.293064 / 10.191392 (4.101672) | 0.169267 / 0.680424 (-0.511157) | 0.018607 / 0.534201 (-0.515594) | 0.393655 / 0.579283 (-0.185628) | 0.402132 / 0.434364 (-0.032232) | 0.477566 / 0.540337 (-0.062772) | 0.651773 / 1.386936 (-0.735163) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#80023f36b2b6678347979421ef973d8969d31306 \"CML watermark\")\n" ]

"2023-08-10T11:03:15Z"

"2023-08-10T11:31:45Z"

"2023-08-10T11:22:56Z"

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"2023-08-10T11:03:08Z"

"2023-08-10T11:03:08Z"

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[]

"2023-08-10T10:19:50Z"

"2023-08-10T11:22:58Z"

"2023-08-10T11:22:58Z"

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[]

[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009055 / 0.011353 (-0.002298) | 0.008835 / 0.011008 (-0.002173) | 0.117048 / 0.038508 (0.078540) | 0.096268 / 0.023109 (0.073159) | 0.474678 / 0.275898 (0.198780) | 0.550509 / 0.323480 (0.227029) | 0.005552 / 0.007986 (-0.002434) | 0.004315 / 0.004328 (-0.000013) | 0.094336 / 0.004250 (0.090086) | 0.061945 / 0.037052 (0.024892) | 0.461422 / 0.258489 (0.202933) | 0.521271 / 0.293841 (0.227430) | 0.049116 / 0.128546 (-0.079430) | 0.015007 / 0.075646 (-0.060639) | 0.414351 / 0.419271 (-0.004920) | 0.137520 / 0.043533 (0.093987) | 0.465627 / 0.255139 (0.210488) | 0.537244 / 0.283200 (0.254044) | 0.068577 / 0.141683 (-0.073106) | 1.921373 / 1.452155 (0.469219) | 2.506653 / 1.492716 (1.013937) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.273970 / 0.018006 (0.255963) | 0.750295 / 0.000490 (0.749805) | 0.004241 / 0.000200 (0.004041) | 0.000128 / 0.000054 (0.000073) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033793 / 0.037411 (-0.003618) | 0.105562 / 0.014526 (0.091037) | 0.131771 / 0.176557 (-0.044786) | 0.196890 / 0.737135 (-0.540245) | 0.119842 / 0.296338 (-0.176496) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.634881 / 0.215209 (0.419672) | 6.069221 / 2.077655 (3.991566) | 2.678765 / 1.504120 (1.174646) | 2.460309 / 1.541195 (0.919114) | 2.517579 / 1.468490 (1.049089) | 0.869558 / 4.584777 (-3.715219) | 5.407686 / 3.745712 (1.661974) | 4.920687 / 5.269862 (-0.349175) | 3.130066 / 4.565676 (-1.435611) | 0.100337 / 0.424275 (-0.323938) | 0.009615 / 0.007607 (0.002008) | 0.745275 / 0.226044 (0.519231) | 7.577890 / 2.268929 (5.308962) | 3.607887 / 55.444624 (-51.836738) | 2.922211 / 6.876477 (-3.954266) | 3.205592 / 2.142072 (1.063519) | 1.052298 / 4.805227 (-3.752929) | 0.218798 / 6.500664 (-6.281866) | 0.082137 / 0.075469 (0.006667) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.696551 / 1.841788 (-0.145237) | 24.946074 / 8.074308 (16.871766) | 23.114202 / 10.191392 (12.922810) | 0.220498 / 0.680424 (-0.459925) | 0.029388 / 0.534201 (-0.504813) | 0.494721 / 0.579283 (-0.084562) | 0.603085 / 0.434364 (0.168722) | 0.573093 / 0.540337 (0.032756) | 0.784937 / 1.386936 (-0.601999) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009642 / 0.011353 (-0.001711) | 0.007551 / 0.011008 (-0.003457) | 0.085224 / 0.038508 (0.046716) | 0.099493 / 0.023109 (0.076384) | 0.503824 / 0.275898 (0.227926) | 0.546583 / 0.323480 (0.223103) | 0.006385 / 0.007986 (-0.001601) | 0.004751 / 0.004328 (0.000423) | 0.084699 / 0.004250 (0.080449) | 0.067875 / 0.037052 (0.030823) | 0.485313 / 0.258489 (0.226824) | 0.535808 / 0.293841 (0.241967) | 0.049935 / 0.128546 (-0.078611) | 0.014427 / 0.075646 (-0.061219) | 0.095531 / 0.419271 (-0.323741) | 0.068487 / 0.043533 (0.024954) | 0.502204 / 0.255139 (0.247065) | 0.514393 / 0.283200 (0.231193) | 0.037350 / 0.141683 (-0.104333) | 1.849380 / 1.452155 (0.397226) | 1.920151 / 1.492716 (0.427434) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.298363 / 0.018006 (0.280357) | 0.651555 / 0.000490 (0.651065) | 0.005910 / 0.000200 (0.005710) | 0.000103 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039170 / 0.037411 (0.001758) | 0.106436 / 0.014526 (0.091910) | 0.129880 / 0.176557 (-0.046677) | 0.185401 / 0.737135 (-0.551734) | 0.125732 / 0.296338 (-0.170607) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.643248 / 0.215209 (0.428039) | 6.374807 / 2.077655 (4.297152) | 3.057296 / 1.504120 (1.553176) | 2.779534 / 1.541195 (1.238340) | 2.790165 / 1.468490 (1.321675) | 0.841580 / 4.584777 (-3.743197) | 5.371478 / 3.745712 (1.625766) | 4.973251 / 5.269862 (-0.296610) | 3.235817 / 4.565676 (-1.329860) | 0.097276 / 0.424275 (-0.326999) | 0.008840 / 0.007607 (0.001233) | 0.728678 / 0.226044 (0.502634) | 7.526382 / 2.268929 (5.257454) | 3.792550 / 55.444624 (-51.652074) | 3.439134 / 6.876477 (-3.437342) | 3.466626 / 2.142072 (1.324553) | 1.035894 / 4.805227 (-3.769333) | 0.211670 / 6.500664 (-6.288994) | 0.087596 / 0.075469 (0.012127) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.782755 / 1.841788 (-0.059033) | 25.704407 / 8.074308 (17.630099) | 23.799672 / 10.191392 (13.608280) | 0.233952 / 0.680424 (-0.446472) | 0.030810 / 0.534201 (-0.503391) | 0.505857 / 0.579283 (-0.073426) | 0.629331 / 0.434364 (0.194967) | 0.608530 / 0.540337 (0.068192) | 0.813688 / 1.386936 (-0.573248) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ed4d6bb5f1331576c41b04acd9872a5349a0915c \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006401 / 0.011353 (-0.004952) | 0.003916 / 0.011008 (-0.007092) | 0.083976 / 0.038508 (0.045468) | 0.072583 / 0.023109 (0.049474) | 0.322747 / 0.275898 (0.046849) | 0.345159 / 0.323480 (0.021679) | 0.005366 / 0.007986 (-0.002620) | 0.003399 / 0.004328 (-0.000930) | 0.064232 / 0.004250 (0.059982) | 0.053313 / 0.037052 (0.016261) | 0.353127 / 0.258489 (0.094638) | 0.361398 / 0.293841 (0.067557) | 0.030604 / 0.128546 (-0.097942) | 0.008615 / 0.075646 (-0.067031) | 0.285806 / 0.419271 (-0.133466) | 0.050887 / 0.043533 (0.007354) | 0.312293 / 0.255139 (0.057154) | 0.349716 / 0.283200 (0.066516) | 0.024546 / 0.141683 (-0.117137) | 1.472318 / 1.452155 (0.020163) | 1.536063 / 1.492716 (0.043347) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280012 / 0.018006 (0.262006) | 0.593574 / 0.000490 (0.593085) | 0.004083 / 0.000200 (0.003883) | 0.000195 / 0.000054 (0.000141) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027715 / 0.037411 (-0.009696) | 0.081392 / 0.014526 (0.066866) | 0.096445 / 0.176557 (-0.080112) | 0.152131 / 0.737135 (-0.585004) | 0.094825 / 0.296338 (-0.201514) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.380749 / 0.215209 (0.165540) | 3.806994 / 2.077655 (1.729339) | 1.842544 / 1.504120 (0.338424) | 1.682829 / 1.541195 (0.141635) | 1.701679 / 1.468490 (0.233189) | 0.484830 / 4.584777 (-4.099947) | 3.517359 / 3.745712 (-0.228353) | 3.231211 / 5.269862 (-2.038651) | 2.029371 / 4.565676 (-2.536306) | 0.057199 / 0.424275 (-0.367077) | 0.007653 / 0.007607 (0.000046) | 0.458572 / 0.226044 (0.232528) | 4.579835 / 2.268929 (2.310907) | 2.326467 / 55.444624 (-53.118157) | 1.939646 / 6.876477 (-4.936831) | 2.133150 / 2.142072 (-0.008922) | 0.596251 / 4.805227 (-4.208976) | 0.131979 / 6.500664 (-6.368686) | 0.059226 / 0.075469 (-0.016243) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.234833 / 1.841788 (-0.606955) | 19.475522 / 8.074308 (11.401214) | 14.102760 / 10.191392 (3.911368) | 0.159657 / 0.680424 (-0.520767) | 0.018292 / 0.534201 (-0.515909) | 0.391079 / 0.579283 (-0.188204) | 0.406736 / 0.434364 (-0.027628) | 0.459159 / 0.540337 (-0.081178) | 0.618159 / 1.386936 (-0.768777) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006592 / 0.011353 (-0.004761) | 0.004052 / 0.011008 (-0.006957) | 0.064536 / 0.038508 (0.026028) | 0.075051 / 0.023109 (0.051942) | 0.379596 / 0.275898 (0.103698) | 0.412413 / 0.323480 (0.088933) | 0.005377 / 0.007986 (-0.002608) | 0.003466 / 0.004328 (-0.000863) | 0.064958 / 0.004250 (0.060708) | 0.055265 / 0.037052 (0.018213) | 0.391505 / 0.258489 (0.133016) | 0.425345 / 0.293841 (0.131504) | 0.030750 / 0.128546 (-0.097796) | 0.008652 / 0.075646 (-0.066994) | 0.072107 / 0.419271 (-0.347165) | 0.048340 / 0.043533 (0.004807) | 0.387714 / 0.255139 (0.132575) | 0.402602 / 0.283200 (0.119402) | 0.023492 / 0.141683 (-0.118191) | 1.528377 / 1.452155 (0.076222) | 1.574827 / 1.492716 (0.082110) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.316999 / 0.018006 (0.298993) | 0.528391 / 0.000490 (0.527901) | 0.005183 / 0.000200 (0.004983) | 0.000085 / 0.000054 (0.000031) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029670 / 0.037411 (-0.007741) | 0.087130 / 0.014526 (0.072604) | 0.099897 / 0.176557 (-0.076660) | 0.154074 / 0.737135 (-0.583062) | 0.104309 / 0.296338 (-0.192030) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.408804 / 0.215209 (0.193595) | 4.072248 / 2.077655 (1.994593) | 2.103333 / 1.504120 (0.599213) | 1.931972 / 1.541195 (0.390777) | 1.980132 / 1.468490 (0.511642) | 0.482623 / 4.584777 (-4.102154) | 3.532789 / 3.745712 (-0.212923) | 3.304962 / 5.269862 (-1.964899) | 2.036672 / 4.565676 (-2.529004) | 0.056944 / 0.424275 (-0.367331) | 0.007190 / 0.007607 (-0.000417) | 0.490650 / 0.226044 (0.264606) | 4.903604 / 2.268929 (2.634675) | 2.586247 / 55.444624 (-52.858377) | 2.227631 / 6.876477 (-4.648846) | 2.397286 / 2.142072 (0.255214) | 0.579167 / 4.805227 (-4.226060) | 0.132037 / 6.500664 (-6.368627) | 0.059971 / 0.075469 (-0.015498) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.336430 / 1.841788 (-0.505358) | 19.915846 / 8.074308 (11.841538) | 14.102781 / 10.191392 (3.911389) | 0.147956 / 0.680424 (-0.532468) | 0.018192 / 0.534201 (-0.516009) | 0.397949 / 0.579283 (-0.181334) | 0.408529 / 0.434364 (-0.025835) | 0.479382 / 0.540337 (-0.060955) | 0.659735 / 1.386936 (-0.727201) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#98074122449bc031f7269f298f1c55f20e39b975 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005880 / 0.011353 (-0.005473) | 0.003677 / 0.011008 (-0.007332) | 0.080022 / 0.038508 (0.041514) | 0.055554 / 0.023109 (0.032445) | 0.397449 / 0.275898 (0.121551) | 0.428346 / 0.323480 (0.104867) | 0.004613 / 0.007986 (-0.003373) | 0.002873 / 0.004328 (-0.001455) | 0.062226 / 0.004250 (0.057976) | 0.044721 / 0.037052 (0.007669) | 0.404792 / 0.258489 (0.146303) | 0.437467 / 0.293841 (0.143626) | 0.027166 / 0.128546 (-0.101381) | 0.008077 / 0.075646 (-0.067569) | 0.260469 / 0.419271 (-0.158803) | 0.043551 / 0.043533 (0.000018) | 0.401712 / 0.255139 (0.146573) | 0.427294 / 0.283200 (0.144094) | 0.021243 / 0.141683 (-0.120440) | 1.464553 / 1.452155 (0.012398) | 1.507112 / 1.492716 (0.014396) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.198415 / 0.018006 (0.180408) | 0.427940 / 0.000490 (0.427450) | 0.004236 / 0.000200 (0.004036) | 0.000067 / 0.000054 (0.000013) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023759 / 0.037411 (-0.013652) | 0.073262 / 0.014526 (0.058736) | 0.677113 / 0.176557 (0.500557) | 0.194964 / 0.737135 (-0.542172) | 0.086121 / 0.296338 (-0.210217) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401176 / 0.215209 (0.185967) | 4.028688 / 2.077655 (1.951034) | 2.026804 / 1.504120 (0.522685) | 1.887964 / 1.541195 (0.346770) | 2.008991 / 1.468490 (0.540501) | 0.498847 / 4.584777 (-4.085930) | 3.015920 / 3.745712 (-0.729792) | 2.837019 / 5.269862 (-2.432843) | 1.849976 / 4.565676 (-2.715701) | 0.057545 / 0.424275 (-0.366730) | 0.006645 / 0.007607 (-0.000962) | 0.470225 / 0.226044 (0.244180) | 4.720910 / 2.268929 (2.451982) | 2.473693 / 55.444624 (-52.970931) | 2.177525 / 6.876477 (-4.698952) | 2.374702 / 2.142072 (0.232630) | 0.588253 / 4.805227 (-4.216974) | 0.125512 / 6.500664 (-6.375152) | 0.061247 / 0.075469 (-0.014222) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.255829 / 1.841788 (-0.585959) | 18.251689 / 8.074308 (10.177381) | 13.690373 / 10.191392 (3.498981) | 0.146928 / 0.680424 (-0.533496) | 0.016534 / 0.534201 (-0.517667) | 0.335249 / 0.579283 (-0.244034) | 0.338940 / 0.434364 (-0.095424) | 0.382170 / 0.540337 (-0.158168) | 0.529570 / 1.386936 (-0.857366) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005920 / 0.011353 (-0.005433) | 0.003557 / 0.011008 (-0.007451) | 0.062776 / 0.038508 (0.024267) | 0.058473 / 0.023109 (0.035364) | 0.358780 / 0.275898 (0.082882) | 0.394161 / 0.323480 (0.070682) | 0.004636 / 0.007986 (-0.003349) | 0.002865 / 0.004328 (-0.001463) | 0.062033 / 0.004250 (0.057782) | 0.047154 / 0.037052 (0.010101) | 0.367718 / 0.258489 (0.109229) | 0.400814 / 0.293841 (0.106973) | 0.026919 / 0.128546 (-0.101628) | 0.008071 / 0.075646 (-0.067575) | 0.067802 / 0.419271 (-0.351469) | 0.040894 / 0.043533 (-0.002638) | 0.358757 / 0.255139 (0.103618) | 0.384971 / 0.283200 (0.101771) | 0.020019 / 0.141683 (-0.121664) | 1.458578 / 1.452155 (0.006423) | 1.525059 / 1.492716 (0.032342) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.207795 / 0.018006 (0.189789) | 0.413201 / 0.000490 (0.412712) | 0.005199 / 0.000200 (0.004999) | 0.000085 / 0.000054 (0.000031) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025716 / 0.037411 (-0.011696) | 0.078434 / 0.014526 (0.063908) | 0.086920 / 0.176557 (-0.089637) | 0.138327 / 0.737135 (-0.598808) | 0.088120 / 0.296338 (-0.208219) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434344 / 0.215209 (0.219135) | 4.343114 / 2.077655 (2.265459) | 2.384439 / 1.504120 (0.880319) | 2.253929 / 1.541195 (0.712735) | 2.306811 / 1.468490 (0.838321) | 0.497572 / 4.584777 (-4.087205) | 3.028794 / 3.745712 (-0.716919) | 2.833484 / 5.269862 (-2.436377) | 1.878918 / 4.565676 (-2.686759) | 0.057133 / 0.424275 (-0.367143) | 0.006357 / 0.007607 (-0.001251) | 0.508019 / 0.226044 (0.281975) | 5.076935 / 2.268929 (2.808007) | 2.745784 / 55.444624 (-52.698841) | 2.476291 / 6.876477 (-4.400186) | 2.677264 / 2.142072 (0.535191) | 0.587173 / 4.805227 (-4.218054) | 0.126373 / 6.500664 (-6.374291) | 0.062815 / 0.075469 (-0.012654) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.355482 / 1.841788 (-0.486305) | 18.818227 / 8.074308 (10.743919) | 13.954289 / 10.191392 (3.762896) | 0.143413 / 0.680424 (-0.537011) | 0.016844 / 0.534201 (-0.517357) | 0.338334 / 0.579283 (-0.240949) | 0.344559 / 0.434364 (-0.089805) | 0.400669 / 0.540337 (-0.139669) | 0.563835 / 1.386936 (-0.823101) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c02a44715c036b5261686669727394b1308a3a4b \"CML watermark\")\n" ]

"2023-08-10T10:09:54Z"

"2023-08-10T12:08:38Z"

"2023-08-10T12:00:02Z"

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[ "I noticed that this is actually covered by issue #5613, which for some reason I didn't see when I searched the issues in this repo the first time." ]

"2023-08-10T06:54:32Z"

"2023-08-10T15:22:22Z"

"2023-08-10T15:22:10Z"

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[ "@lhoestq ", "It's roughly the same code between the two so we can expected roughly the same speed, could you share a benchmark ?" ]

"2023-08-10T06:36:23Z"

"2023-08-16T09:18:54Z"

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[ "Fixed with PR" ]

"2023-08-09T15:15:03Z"

"2023-08-16T04:43:36Z"

"2023-08-16T04:43:29Z"

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[ "@lhoestq ", "What should be the behavior in this case ? Should it override the default config with the added parameter ?", "I know why it should be treated as a new config if overriding parameters are passed. But in some case, I just pass in some common fields like `data_dir`.\r\n\r\nFor example, I want to extend the FolderBasedBuilder as a multi-config version, the `data_dir` or `data_files` are always passed by user and should not be considered as overriding the default config. In current state, I cannot leverage the feature of default config since passing `data_dir` will disable the default config.", "Thinking more about it I think the current behavior is the right one.\r\n\r\nProvided parameters should be passed to instantiate a new BuilderConfig.\r\n\r\nWhat's the error you're getting ?", "For example, this works to use default config with name '_all_':\r\n```python\r\ndatasets.load_dataset(\"indonesian-nlp/librivox-indonesia\", split=\"train\")\r\n```\r\nwhile this failed to use default config\r\n```python\r\ndatasets.load_dataset(\"indonesian-nlp/librivox-indonesia\", split=\"train\", data_dir='.')\r\n```\r\nAfter manually specifying it, it works again.\r\n```python\r\ndatasets.load_dataset(\"indonesian-nlp/librivox-indonesia\", \"_all_\", split=\"train\", data_dir='.')\r\n```", "@lhoestq ", "It should work if you explicitly ask for the config you want to override\r\n\r\n```python\r\nload_dataset('/dataset/with/multiple/config', 'name_of_the_default_config', some_field_in_config='some')\r\n```\r\n\r\nAlternatively you can have a BuilderConfig class that when instantiated returns a config with the right default values. In this case this code would instantiate this config with the default values except for the parameter to override:\r\n\r\n```python\r\nload_dataset('/dataset/with/multiple/config', some_field_in_config='some')\r\n```", "@lhoestq Yes. But it doesn't work for me.\r\n\r\nHere's my dataset for example.\r\n```\r\nlass MyDatasetConfig(datasets.BuilderConfig):\r\n def __init__(self, name: str, version: str, **kwargs):\r\n self.option1 = kwargs.pop(\"option1\", False)\r\n self.option2 = kwargs.pop(\"option2\", 5)\r\n\r\n super().__init__(\r\n name=name,\r\n version=datasets.Version(version),\r\n **kwargs)\r\n\r\n\r\nclass MyDataset(datasets.GeneratorBasedBuilder):\r\n DEFAULT_CONFIG_NAME = \"v1\"\r\n\r\n BUILDER_CONFIGS = [\r\n UnifiedTtsDatasetConfig(\r\n name=\"v1\",\r\n version=\"1.0.0\",\r\n description=\"Initial version of the dataset\"\r\n ),\r\n ]\r\n\r\n def _info(self) -> DatasetInfo:\r\n _ = self.option1\r\n ....\r\n```\r\n\r\nHere it's okay to use `load_dataset('my_dataset.py')` for loading the default config `v1`.\r\n\r\nBut if I want to override the default values in config with `load_dataset('my_dataset.py', option2=3)`, it failed to find my default config `v1.\r\n\r\nUnless I use `load_dataset('my_dataset.py', 'v1', option2=3)`\r\n\r\nSo according to your advice, how can I modify my dataset to be able to override default config without manually specifying it.", "What's the error ? It should try to instantiate `MyDatasetConfig` with `option2=3`", "@lhoestq The error is\r\n```\r\ndef _info(self) -> DatasetInfo:\r\n _ = self.option1 <-\r\n ....\r\nAttributeError: 'BuilderConfig' object has no attribute 'option1'\r\n```\r\nwhich seems to find another unknown config.\r\n\r\nYou can try this line `datasets.load_dataset(\"indonesian-nlp/librivox-indonesia\", split=\"train\", data_dir='.')`, it's a multi-config dataset on HF hub and the error is the same.\r\n\r\nMy insights:\r\nhttps://github.com/huggingface/datasets/blob/12cfc1196e62847e2e8239fbd727a02cbc86ddec/src/datasets/builder.py#L518\r\nif `config_kwargs` is provided here, the if branch is skipped.", "I see, you just have to set this class attribute to your builder class :)\r\n\r\n```python\r\nBUILDER_CONFIG_CLASS = MyDatasetConfig\r\n```", "So what does this attribute do? In most cases it's not used and the [documents for multi-config dataset](https://huggingface.co/docs/datasets/main/en/image_dataset#multiple-configurations) never mentioned that.", "It tells which builder config class to instantiate if additional config parameters are passed to load_dataset", "@lhoestq maybe we can enhance the document to say something about the common attributes of `DatasetBuilder`", "Ah indeed it's missing in the docs, thanks for reporting. I'm opening a PR" ]

"2023-08-09T12:43:15Z"

"2023-08-22T10:03:41Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006053 / 0.011353 (-0.005299) | 0.003532 / 0.011008 (-0.007476) | 0.081930 / 0.038508 (0.043422) | 0.059043 / 0.023109 (0.035934) | 0.322785 / 0.275898 (0.046887) | 0.378158 / 0.323480 (0.054678) | 0.004709 / 0.007986 (-0.003277) | 0.002907 / 0.004328 (-0.001421) | 0.061516 / 0.004250 (0.057266) | 0.047209 / 0.037052 (0.010157) | 0.346885 / 0.258489 (0.088396) | 0.381011 / 0.293841 (0.087170) | 0.027491 / 0.128546 (-0.101055) | 0.008014 / 0.075646 (-0.067632) | 0.260663 / 0.419271 (-0.158608) | 0.045427 / 0.043533 (0.001894) | 0.315277 / 0.255139 (0.060138) | 0.377902 / 0.283200 (0.094703) | 0.021371 / 0.141683 (-0.120311) | 1.416350 / 1.452155 (-0.035804) | 1.483345 / 1.492716 (-0.009372) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.203660 / 0.018006 (0.185654) | 0.569081 / 0.000490 (0.568591) | 0.002742 / 0.000200 (0.002542) | 0.000074 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023456 / 0.037411 (-0.013955) | 0.073954 / 0.014526 (0.059428) | 0.082991 / 0.176557 (-0.093566) | 0.144781 / 0.737135 (-0.592354) | 0.083346 / 0.296338 (-0.212992) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.391542 / 0.215209 (0.176333) | 3.909505 / 2.077655 (1.831850) | 1.862234 / 1.504120 (0.358114) | 1.676076 / 1.541195 (0.134881) | 1.727595 / 1.468490 (0.259105) | 0.501769 / 4.584777 (-4.083008) | 3.083697 / 3.745712 (-0.662016) | 2.819751 / 5.269862 (-2.450111) | 1.867265 / 4.565676 (-2.698411) | 0.057575 / 0.424275 (-0.366700) | 0.006478 / 0.007607 (-0.001129) | 0.466684 / 0.226044 (0.240640) | 4.657982 / 2.268929 (2.389054) | 2.347052 / 55.444624 (-53.097573) | 1.964688 / 6.876477 (-4.911789) | 2.077821 / 2.142072 (-0.064252) | 0.590591 / 4.805227 (-4.214636) | 0.124585 / 6.500664 (-6.376079) | 0.059468 / 0.075469 (-0.016001) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.223484 / 1.841788 (-0.618304) | 18.104638 / 8.074308 (10.030330) | 13.755126 / 10.191392 (3.563734) | 0.143158 / 0.680424 (-0.537266) | 0.017147 / 0.534201 (-0.517054) | 0.337427 / 0.579283 (-0.241856) | 0.352270 / 0.434364 (-0.082094) | 0.383718 / 0.540337 (-0.156619) | 0.534973 / 1.386936 (-0.851963) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006039 / 0.011353 (-0.005314) | 0.003735 / 0.011008 (-0.007274) | 0.061954 / 0.038508 (0.023446) | 0.061786 / 0.023109 (0.038677) | 0.429420 / 0.275898 (0.153522) | 0.457629 / 0.323480 (0.134149) | 0.004748 / 0.007986 (-0.003237) | 0.002843 / 0.004328 (-0.001485) | 0.061811 / 0.004250 (0.057560) | 0.048740 / 0.037052 (0.011687) | 0.430066 / 0.258489 (0.171577) | 0.465971 / 0.293841 (0.172130) | 0.027577 / 0.128546 (-0.100969) | 0.007981 / 0.075646 (-0.067665) | 0.067580 / 0.419271 (-0.351692) | 0.042058 / 0.043533 (-0.001475) | 0.428412 / 0.255139 (0.173273) | 0.451054 / 0.283200 (0.167855) | 0.020850 / 0.141683 (-0.120833) | 1.453907 / 1.452155 (0.001752) | 1.509914 / 1.492716 (0.017197) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237713 / 0.018006 (0.219707) | 0.418064 / 0.000490 (0.417575) | 0.006411 / 0.000200 (0.006211) | 0.000078 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024950 / 0.037411 (-0.012462) | 0.076806 / 0.014526 (0.062281) | 0.085237 / 0.176557 (-0.091320) | 0.137940 / 0.737135 (-0.599196) | 0.086266 / 0.296338 (-0.210072) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.418666 / 0.215209 (0.203457) | 4.160547 / 2.077655 (2.082893) | 2.135671 / 1.504120 (0.631551) | 1.964985 / 1.541195 (0.423790) | 2.009447 / 1.468490 (0.540957) | 0.501377 / 4.584777 (-4.083400) | 3.064293 / 3.745712 (-0.681419) | 2.827153 / 5.269862 (-2.442709) | 1.854698 / 4.565676 (-2.710978) | 0.057662 / 0.424275 (-0.366613) | 0.006829 / 0.007607 (-0.000778) | 0.496730 / 0.226044 (0.270686) | 4.964663 / 2.268929 (2.695735) | 2.583133 / 55.444624 (-52.861491) | 2.329700 / 6.876477 (-4.546776) | 2.415521 / 2.142072 (0.273449) | 0.591973 / 4.805227 (-4.213255) | 0.126801 / 6.500664 (-6.373863) | 0.062811 / 0.075469 (-0.012659) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.348575 / 1.841788 (-0.493212) | 18.282861 / 8.074308 (10.208553) | 13.734056 / 10.191392 (3.542664) | 0.154987 / 0.680424 (-0.525437) | 0.016996 / 0.534201 (-0.517205) | 0.335264 / 0.579283 (-0.244019) | 0.356907 / 0.434364 (-0.077456) | 0.399185 / 0.540337 (-0.141152) | 0.540209 / 1.386936 (-0.846727) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#887bef1217e0f4441d57bf0f4d1e806df12f2c50 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006768 / 0.011353 (-0.004585) | 0.004250 / 0.011008 (-0.006758) | 0.086780 / 0.038508 (0.048272) | 0.080872 / 0.023109 (0.057762) | 0.309281 / 0.275898 (0.033383) | 0.352293 / 0.323480 (0.028814) | 0.005604 / 0.007986 (-0.002382) | 0.003544 / 0.004328 (-0.000784) | 0.066910 / 0.004250 (0.062659) | 0.055568 / 0.037052 (0.018516) | 0.314931 / 0.258489 (0.056442) | 0.366026 / 0.293841 (0.072185) | 0.031247 / 0.128546 (-0.097300) | 0.008860 / 0.075646 (-0.066786) | 0.293210 / 0.419271 (-0.126061) | 0.052868 / 0.043533 (0.009335) | 0.316769 / 0.255139 (0.061630) | 0.352128 / 0.283200 (0.068929) | 0.025492 / 0.141683 (-0.116190) | 1.478379 / 1.452155 (0.026224) | 1.573652 / 1.492716 (0.080936) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.294975 / 0.018006 (0.276968) | 0.615093 / 0.000490 (0.614603) | 0.004279 / 0.000200 (0.004079) | 0.000102 / 0.000054 (0.000047) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031557 / 0.037411 (-0.005855) | 0.085026 / 0.014526 (0.070500) | 0.101221 / 0.176557 (-0.075336) | 0.157432 / 0.737135 (-0.579703) | 0.102350 / 0.296338 (-0.193988) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384158 / 0.215209 (0.168949) | 3.826656 / 2.077655 (1.749001) | 1.873510 / 1.504120 (0.369390) | 1.721913 / 1.541195 (0.180718) | 1.848779 / 1.468490 (0.380289) | 0.485128 / 4.584777 (-4.099649) | 3.656660 / 3.745712 (-0.089052) | 3.441964 / 5.269862 (-1.827898) | 2.150611 / 4.565676 (-2.415066) | 0.056869 / 0.424275 (-0.367406) | 0.007382 / 0.007607 (-0.000225) | 0.458751 / 0.226044 (0.232707) | 4.585028 / 2.268929 (2.316099) | 2.439538 / 55.444624 (-53.005086) | 2.116959 / 6.876477 (-4.759518) | 2.459220 / 2.142072 (0.317147) | 0.580907 / 4.805227 (-4.224321) | 0.134502 / 6.500664 (-6.366162) | 0.062528 / 0.075469 (-0.012941) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.251006 / 1.841788 (-0.590782) | 20.755849 / 8.074308 (12.681541) | 14.456950 / 10.191392 (4.265558) | 0.167074 / 0.680424 (-0.513350) | 0.018482 / 0.534201 (-0.515719) | 0.395867 / 0.579283 (-0.183416) | 0.415620 / 0.434364 (-0.018744) | 0.462247 / 0.540337 (-0.078090) | 0.645762 / 1.386936 (-0.741174) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007050 / 0.011353 (-0.004303) | 0.004421 / 0.011008 (-0.006587) | 0.065312 / 0.038508 (0.026804) | 0.089790 / 0.023109 (0.066681) | 0.366318 / 0.275898 (0.090420) | 0.403542 / 0.323480 (0.080062) | 0.005695 / 0.007986 (-0.002290) | 0.003642 / 0.004328 (-0.000687) | 0.064540 / 0.004250 (0.060289) | 0.060933 / 0.037052 (0.023881) | 0.369004 / 0.258489 (0.110515) | 0.408056 / 0.293841 (0.114215) | 0.032124 / 0.128546 (-0.096422) | 0.008960 / 0.075646 (-0.066686) | 0.071267 / 0.419271 (-0.348005) | 0.049745 / 0.043533 (0.006212) | 0.367203 / 0.255139 (0.112064) | 0.383009 / 0.283200 (0.099809) | 0.025330 / 0.141683 (-0.116353) | 1.518290 / 1.452155 (0.066135) | 1.581738 / 1.492716 (0.089022) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.338281 / 0.018006 (0.320275) | 0.538195 / 0.000490 (0.537706) | 0.008498 / 0.000200 (0.008298) | 0.000121 / 0.000054 (0.000067) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033279 / 0.037411 (-0.004133) | 0.093233 / 0.014526 (0.078707) | 0.106019 / 0.176557 (-0.070538) | 0.161262 / 0.737135 (-0.575874) | 0.109935 / 0.296338 (-0.186404) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.411563 / 0.215209 (0.196354) | 4.102149 / 2.077655 (2.024495) | 2.108513 / 1.504120 (0.604393) | 1.945344 / 1.541195 (0.404150) | 2.066964 / 1.468490 (0.598474) | 0.482771 / 4.584777 (-4.102006) | 3.659160 / 3.745712 (-0.086552) | 3.420833 / 5.269862 (-1.849029) | 2.147276 / 4.565676 (-2.418400) | 0.056957 / 0.424275 (-0.367318) | 0.007898 / 0.007607 (0.000290) | 0.482401 / 0.226044 (0.256357) | 4.821044 / 2.268929 (2.552115) | 2.567993 / 55.444624 (-52.876631) | 2.336165 / 6.876477 (-4.540312) | 2.545066 / 2.142072 (0.402994) | 0.580888 / 4.805227 (-4.224339) | 0.134092 / 6.500664 (-6.366572) | 0.062681 / 0.075469 (-0.012788) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.379124 / 1.841788 (-0.462664) | 21.627949 / 8.074308 (13.553641) | 15.064818 / 10.191392 (4.873426) | 0.169707 / 0.680424 (-0.510716) | 0.018671 / 0.534201 (-0.515530) | 0.400496 / 0.579283 (-0.178787) | 0.415542 / 0.434364 (-0.018822) | 0.484351 / 0.540337 (-0.055986) | 0.646046 / 1.386936 (-0.740890) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#53d55f33bfac9febb0c355e136f2847e5f3e3b53 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007113 / 0.011353 (-0.004240) | 0.004436 / 0.011008 (-0.006572) | 0.087422 / 0.038508 (0.048914) | 0.085996 / 0.023109 (0.062887) | 0.311772 / 0.275898 (0.035873) | 0.353281 / 0.323480 (0.029801) | 0.004562 / 0.007986 (-0.003423) | 0.003840 / 0.004328 (-0.000488) | 0.066500 / 0.004250 (0.062250) | 0.061293 / 0.037052 (0.024241) | 0.328840 / 0.258489 (0.070351) | 0.365587 / 0.293841 (0.071746) | 0.031802 / 0.128546 (-0.096744) | 0.008881 / 0.075646 (-0.066765) | 0.289671 / 0.419271 (-0.129601) | 0.053348 / 0.043533 (0.009816) | 0.307822 / 0.255139 (0.052683) | 0.342559 / 0.283200 (0.059360) | 0.025760 / 0.141683 (-0.115923) | 1.509944 / 1.452155 (0.057789) | 1.556634 / 1.492716 (0.063918) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.282036 / 0.018006 (0.264029) | 0.608350 / 0.000490 (0.607860) | 0.004843 / 0.000200 (0.004643) | 0.000108 / 0.000054 (0.000054) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029810 / 0.037411 (-0.007601) | 0.086215 / 0.014526 (0.071689) | 0.102200 / 0.176557 (-0.074356) | 0.158051 / 0.737135 (-0.579084) | 0.103083 / 0.296338 (-0.193255) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.392119 / 0.215209 (0.176910) | 3.895796 / 2.077655 (1.818141) | 1.921118 / 1.504120 (0.416998) | 1.754271 / 1.541195 (0.213076) | 1.880991 / 1.468490 (0.412501) | 0.481158 / 4.584777 (-4.103618) | 3.609210 / 3.745712 (-0.136502) | 3.412018 / 5.269862 (-1.857843) | 2.131710 / 4.565676 (-2.433967) | 0.057122 / 0.424275 (-0.367153) | 0.007444 / 0.007607 (-0.000163) | 0.468880 / 0.226044 (0.242835) | 4.682441 / 2.268929 (2.413512) | 2.505613 / 55.444624 (-52.939012) | 2.149655 / 6.876477 (-4.726822) | 2.465904 / 2.142072 (0.323832) | 0.578877 / 4.805227 (-4.226350) | 0.133504 / 6.500664 (-6.367160) | 0.061422 / 0.075469 (-0.014047) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.269395 / 1.841788 (-0.572393) | 21.107558 / 8.074308 (13.033250) | 15.318502 / 10.191392 (5.127110) | 0.165273 / 0.680424 (-0.515151) | 0.018783 / 0.534201 (-0.515418) | 0.396259 / 0.579283 (-0.183024) | 0.412907 / 0.434364 (-0.021457) | 0.465723 / 0.540337 (-0.074615) | 0.638414 / 1.386936 (-0.748522) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007083 / 0.011353 (-0.004270) | 0.004216 / 0.011008 (-0.006793) | 0.065362 / 0.038508 (0.026854) | 0.095454 / 0.023109 (0.072345) | 0.364220 / 0.275898 (0.088322) | 0.417650 / 0.323480 (0.094170) | 0.006114 / 0.007986 (-0.001872) | 0.003577 / 0.004328 (-0.000751) | 0.064830 / 0.004250 (0.060579) | 0.062535 / 0.037052 (0.025483) | 0.381844 / 0.258489 (0.123355) | 0.418996 / 0.293841 (0.125155) | 0.031386 / 0.128546 (-0.097160) | 0.008913 / 0.075646 (-0.066733) | 0.070860 / 0.419271 (-0.348411) | 0.049132 / 0.043533 (0.005599) | 0.360406 / 0.255139 (0.105267) | 0.392407 / 0.283200 (0.109207) | 0.024611 / 0.141683 (-0.117072) | 1.509051 / 1.452155 (0.056896) | 1.570288 / 1.492716 (0.077572) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.368611 / 0.018006 (0.350605) | 0.537587 / 0.000490 (0.537098) | 0.028056 / 0.000200 (0.027856) | 0.000317 / 0.000054 (0.000262) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031570 / 0.037411 (-0.005841) | 0.088985 / 0.014526 (0.074460) | 0.105268 / 0.176557 (-0.071288) | 0.156724 / 0.737135 (-0.580412) | 0.105266 / 0.296338 (-0.191073) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.413861 / 0.215209 (0.198652) | 4.127001 / 2.077655 (2.049347) | 2.112114 / 1.504120 (0.607994) | 1.945200 / 1.541195 (0.404005) | 2.083031 / 1.468490 (0.614540) | 0.488086 / 4.584777 (-4.096691) | 3.565584 / 3.745712 (-0.180128) | 3.380782 / 5.269862 (-1.889079) | 2.103481 / 4.565676 (-2.462195) | 0.058203 / 0.424275 (-0.366072) | 0.007996 / 0.007607 (0.000389) | 0.487986 / 0.226044 (0.261941) | 4.871023 / 2.268929 (2.602095) | 2.584632 / 55.444624 (-52.859992) | 2.240103 / 6.876477 (-4.636374) | 2.555165 / 2.142072 (0.413092) | 0.591950 / 4.805227 (-4.213278) | 0.134919 / 6.500664 (-6.365745) | 0.062868 / 0.075469 (-0.012601) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.369731 / 1.841788 (-0.472057) | 21.497888 / 8.074308 (13.423580) | 14.555054 / 10.191392 (4.363662) | 0.168768 / 0.680424 (-0.511656) | 0.018837 / 0.534201 (-0.515364) | 0.394512 / 0.579283 (-0.184771) | 0.405459 / 0.434364 (-0.028905) | 0.475479 / 0.540337 (-0.064858) | 0.631994 / 1.386936 (-0.754942) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#53d55f33bfac9febb0c355e136f2847e5f3e3b53 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009072 / 0.011353 (-0.002280) | 0.004894 / 0.011008 (-0.006114) | 0.108790 / 0.038508 (0.070282) | 0.081783 / 0.023109 (0.058674) | 0.381963 / 0.275898 (0.106064) | 0.450700 / 0.323480 (0.127220) | 0.006961 / 0.007986 (-0.001025) | 0.004035 / 0.004328 (-0.000293) | 0.081420 / 0.004250 (0.077169) | 0.058029 / 0.037052 (0.020976) | 0.437453 / 0.258489 (0.178964) | 0.472607 / 0.293841 (0.178766) | 0.048663 / 0.128546 (-0.079884) | 0.013512 / 0.075646 (-0.062134) | 0.406009 / 0.419271 (-0.013262) | 0.067616 / 0.043533 (0.024084) | 0.383641 / 0.255139 (0.128502) | 0.456734 / 0.283200 (0.173534) | 0.033391 / 0.141683 (-0.108292) | 1.753529 / 1.452155 (0.301375) | 1.859831 / 1.492716 (0.367115) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.215128 / 0.018006 (0.197122) | 0.538261 / 0.000490 (0.537771) | 0.005430 / 0.000200 (0.005230) | 0.000124 / 0.000054 (0.000069) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032664 / 0.037411 (-0.004748) | 0.093465 / 0.014526 (0.078939) | 0.106637 / 0.176557 (-0.069919) | 0.173642 / 0.737135 (-0.563494) | 0.113944 / 0.296338 (-0.182394) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.629212 / 0.215209 (0.414003) | 6.116729 / 2.077655 (4.039075) | 2.818000 / 1.504120 (1.313880) | 2.515317 / 1.541195 (0.974122) | 2.466588 / 1.468490 (0.998098) | 0.850815 / 4.584777 (-3.733962) | 5.051292 / 3.745712 (1.305579) | 4.472138 / 5.269862 (-0.797724) | 2.968317 / 4.565676 (-1.597360) | 0.100173 / 0.424275 (-0.324102) | 0.008407 / 0.007607 (0.000800) | 0.743972 / 0.226044 (0.517928) | 7.397619 / 2.268929 (5.128690) | 3.596681 / 55.444624 (-51.847943) | 2.854674 / 6.876477 (-4.021803) | 3.114274 / 2.142072 (0.972201) | 1.064879 / 4.805227 (-3.740348) | 0.215981 / 6.500664 (-6.284683) | 0.078159 / 0.075469 (0.002690) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.543291 / 1.841788 (-0.298497) | 23.244641 / 8.074308 (15.170333) | 20.784610 / 10.191392 (10.593218) | 0.222002 / 0.680424 (-0.458422) | 0.028584 / 0.534201 (-0.505617) | 0.478563 / 0.579283 (-0.100720) | 0.556101 / 0.434364 (0.121737) | 0.547446 / 0.540337 (0.007109) | 0.764318 / 1.386936 (-0.622618) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008651 / 0.011353 (-0.002702) | 0.004925 / 0.011008 (-0.006083) | 0.078995 / 0.038508 (0.040487) | 0.092878 / 0.023109 (0.069769) | 0.485615 / 0.275898 (0.209717) | 0.532157 / 0.323480 (0.208677) | 0.008228 / 0.007986 (0.000243) | 0.004777 / 0.004328 (0.000449) | 0.076892 / 0.004250 (0.072642) | 0.066905 / 0.037052 (0.029853) | 0.465497 / 0.258489 (0.207008) | 0.520153 / 0.293841 (0.226312) | 0.047357 / 0.128546 (-0.081189) | 0.016870 / 0.075646 (-0.058776) | 0.090481 / 0.419271 (-0.328791) | 0.060774 / 0.043533 (0.017241) | 0.474368 / 0.255139 (0.219229) | 0.503981 / 0.283200 (0.220781) | 0.036025 / 0.141683 (-0.105658) | 1.769939 / 1.452155 (0.317784) | 1.851518 / 1.492716 (0.358802) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.265947 / 0.018006 (0.247941) | 0.532317 / 0.000490 (0.531828) | 0.004997 / 0.000200 (0.004797) | 0.000130 / 0.000054 (0.000076) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034112 / 0.037411 (-0.003299) | 0.102290 / 0.014526 (0.087764) | 0.109989 / 0.176557 (-0.066567) | 0.182813 / 0.737135 (-0.554323) | 0.111774 / 0.296338 (-0.184565) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.584893 / 0.215209 (0.369684) | 6.138505 / 2.077655 (4.060850) | 2.925761 / 1.504120 (1.421641) | 2.607320 / 1.541195 (1.066125) | 2.655827 / 1.468490 (1.187337) | 0.871140 / 4.584777 (-3.713637) | 5.051171 / 3.745712 (1.305459) | 4.708008 / 5.269862 (-0.561854) | 3.027485 / 4.565676 (-1.538191) | 0.100970 / 0.424275 (-0.323305) | 0.009640 / 0.007607 (0.002033) | 0.747818 / 0.226044 (0.521774) | 7.539930 / 2.268929 (5.271001) | 3.611693 / 55.444624 (-51.832931) | 2.924087 / 6.876477 (-3.952390) | 3.141993 / 2.142072 (0.999920) | 1.062921 / 4.805227 (-3.742306) | 0.213185 / 6.500664 (-6.287479) | 0.077146 / 0.075469 (0.001677) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.669182 / 1.841788 (-0.172606) | 23.810242 / 8.074308 (15.735934) | 21.220649 / 10.191392 (11.029257) | 0.212639 / 0.680424 (-0.467785) | 0.026705 / 0.534201 (-0.507496) | 0.469231 / 0.579283 (-0.110053) | 0.551672 / 0.434364 (0.117308) | 0.575043 / 0.540337 (0.034706) | 0.767511 / 1.386936 (-0.619425) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#53d55f33bfac9febb0c355e136f2847e5f3e3b53 \"CML watermark\")\n" ]

"2023-08-08T15:43:56Z"

"2023-08-08T16:08:22Z"

"2023-08-08T15:49:06Z"

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[ "Hi @TomasAndersonFang,\r\n\r\nHave you tried instead to use `torch_compile` in `transformers.TrainingArguments`? https://huggingface.co/docs/transformers/v4.31.0/en/main_classes/trainer#transformers.TrainingArguments.torch_compile", "> \r\n\r\nI tried this and got the following error:\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 324, in _compile\r\n out_code = transform_code_object(code, transform)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/bytecode_transformation.py\", line 445, in transform_code_object\r\n transformations(instructions, code_options)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 311, in transform\r\n tracer.run()\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py\", line 1726, in run\r\n super().run()\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py\", line 576, in run\r\n and self.step()\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py\", line 540, in step\r\n getattr(self, inst.opname)(inst)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py\", line 1030, in LOAD_ATTR\r\n result = BuiltinVariable(getattr).call_function(\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py\", line 566, in call_function\r\n result = handler(tx, *args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py\", line 931, in call_getattr\r\n return obj.var_getattr(tx, name).add_options(options)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/variables/nn_module.py\", line 124, in var_getattr\r\n subobj = inspect.getattr_static(base, name)\r\n File \"/apps/Arch/software/Python/3.10.8-GCCcore-12.2.0/lib/python3.10/inspect.py\", line 1777, in getattr_static\r\n raise AttributeError(attr)\r\nAttributeError: config\r\n\r\nfrom user code:\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/peft/peft_model.py\", line 909, in forward\r\n if self.base_model.config.model_type == \"mpt\":\r\n\r\nSet torch._dynamo.config.verbose=True for more information\r\n\r\n\r\nYou can suppress this exception and fall back to eager by setting:\r\n torch._dynamo.config.suppress_errors = True\r\n\r\n\r\nThe above exception was the direct cause of the following exception:\r\n\r\nTraceback (most recent call last):\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/llm-copt/fine-tune/falcon/falcon_sft.py\", line 228, in <module>\r\n main()\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/llm-copt/fine-tune/falcon/falcon_sft.py\", line 221, in main\r\n trainer.train()\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/transformers/trainer.py\", line 1539, in train\r\n return inner_training_loop(\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/transformers/trainer.py\", line 1809, in _inner_training_loop\r\n tr_loss_step = self.training_step(model, inputs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/transformers/trainer.py\", line 2654, in training_step\r\n loss = self.compute_loss(model, inputs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/transformers/trainer.py\", line 2679, in compute_loss\r\n outputs = model(**inputs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/nn/modules/module.py\", line 1501, in _call_impl\r\n return forward_call(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py\", line 82, in forward\r\n return self.dynamo_ctx(self._orig_mod.forward)(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py\", line 209, in _fn\r\n return fn(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/accelerate/utils/operations.py\", line 581, in forward\r\n return model_forward(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/accelerate/utils/operations.py\", line 569, in __call__\r\n return convert_to_fp32(self.model_forward(*args, **kwargs))\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/amp/autocast_mode.py\", line 14, in decorate_autocast\r\n return func(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py\", line 337, in catch_errors\r\n return callback(frame, cache_size, hooks)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 404, in _convert_frame\r\n result = inner_convert(frame, cache_size, hooks)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 104, in _fn\r\n return fn(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 262, in _convert_frame_assert\r\n return _compile(\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/utils.py\", line 163, in time_wrapper\r\n r = func(*args, **kwargs)\r\n File \"/cephyr/NOBACKUP/groups/snic2021-23-24/LLM4-CodeOpt/env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py\", line 394, in _compile\r\n raise InternalTorchDynamoError() from e\r\ntorch._dynamo.exc.InternalTorchDynamoError\r\n```", "Hi @TomasAndersonFang,\r\n\r\nI guess in this case it may be an issue with `transformers` (or `PyTorch`). I would recommend you open an issue on their repo.", "@albertvillanova Thanks for your recommendation. I'll do it" ]

"2023-08-08T15:32:08Z"

"2023-08-11T13:35:09Z"

"2023-08-11T13:35:09Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006103 / 0.011353 (-0.005250) | 0.003588 / 0.011008 (-0.007420) | 0.080335 / 0.038508 (0.041827) | 0.059634 / 0.023109 (0.036525) | 0.356093 / 0.275898 (0.080195) | 0.407376 / 0.323480 (0.083896) | 0.005343 / 0.007986 (-0.002643) | 0.002928 / 0.004328 (-0.001400) | 0.062580 / 0.004250 (0.058330) | 0.047544 / 0.037052 (0.010491) | 0.364305 / 0.258489 (0.105816) | 0.421463 / 0.293841 (0.127623) | 0.027249 / 0.128546 (-0.101298) | 0.008010 / 0.075646 (-0.067636) | 0.262543 / 0.419271 (-0.156728) | 0.044978 / 0.043533 (0.001445) | 0.339344 / 0.255139 (0.084205) | 0.395288 / 0.283200 (0.112088) | 0.021425 / 0.141683 (-0.120258) | 1.439767 / 1.452155 (-0.012387) | 1.498081 / 1.492716 (0.005365) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.196976 / 0.018006 (0.178970) | 0.435383 / 0.000490 (0.434893) | 0.004559 / 0.000200 (0.004359) | 0.000071 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023653 / 0.037411 (-0.013759) | 0.072944 / 0.014526 (0.058418) | 0.083651 / 0.176557 (-0.092906) | 0.144590 / 0.737135 (-0.592545) | 0.084844 / 0.296338 (-0.211494) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398752 / 0.215209 (0.183543) | 3.959539 / 2.077655 (1.881884) | 1.935277 / 1.504120 (0.431157) | 1.751994 / 1.541195 (0.210799) | 1.828386 / 1.468490 (0.359896) | 0.500492 / 4.584777 (-4.084284) | 3.086630 / 3.745712 (-0.659082) | 2.851664 / 5.269862 (-2.418198) | 1.869792 / 4.565676 (-2.695885) | 0.058509 / 0.424275 (-0.365766) | 0.006500 / 0.007607 (-0.001107) | 0.467468 / 0.226044 (0.241424) | 4.686168 / 2.268929 (2.417240) | 2.427632 / 55.444624 (-53.016993) | 2.193194 / 6.876477 (-4.683283) | 2.408574 / 2.142072 (0.266501) | 0.592173 / 4.805227 (-4.213054) | 0.125381 / 6.500664 (-6.375283) | 0.060679 / 0.075469 (-0.014790) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.236066 / 1.841788 (-0.605722) | 18.591689 / 8.074308 (10.517381) | 14.138774 / 10.191392 (3.947382) | 0.147455 / 0.680424 (-0.532968) | 0.016921 / 0.534201 (-0.517280) | 0.328129 / 0.579283 (-0.251154) | 0.348872 / 0.434364 (-0.085491) | 0.380311 / 0.540337 (-0.160026) | 0.532901 / 1.386936 (-0.854035) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005914 / 0.011353 (-0.005438) | 0.003614 / 0.011008 (-0.007394) | 0.062857 / 0.038508 (0.024349) | 0.060633 / 0.023109 (0.037524) | 0.419684 / 0.275898 (0.143786) | 0.449025 / 0.323480 (0.125546) | 0.004595 / 0.007986 (-0.003391) | 0.002861 / 0.004328 (-0.001467) | 0.063253 / 0.004250 (0.059003) | 0.048770 / 0.037052 (0.011718) | 0.419838 / 0.258489 (0.161349) | 0.465183 / 0.293841 (0.171342) | 0.027350 / 0.128546 (-0.101196) | 0.008065 / 0.075646 (-0.067582) | 0.068321 / 0.419271 (-0.350950) | 0.041083 / 0.043533 (-0.002449) | 0.400831 / 0.255139 (0.145692) | 0.449286 / 0.283200 (0.166086) | 0.020472 / 0.141683 (-0.121210) | 1.437215 / 1.452155 (-0.014940) | 1.503679 / 1.492716 (0.010963) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230764 / 0.018006 (0.212758) | 0.420774 / 0.000490 (0.420285) | 0.004012 / 0.000200 (0.003812) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026009 / 0.037411 (-0.011402) | 0.077943 / 0.014526 (0.063417) | 0.087281 / 0.176557 (-0.089276) | 0.139422 / 0.737135 (-0.597713) | 0.089090 / 0.296338 (-0.207248) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.417298 / 0.215209 (0.202088) | 4.152303 / 2.077655 (2.074648) | 2.179996 / 1.504120 (0.675877) | 2.020619 / 1.541195 (0.479424) | 2.085241 / 1.468490 (0.616751) | 0.501111 / 4.584777 (-4.083666) | 3.079849 / 3.745712 (-0.665863) | 2.820607 / 5.269862 (-2.449255) | 1.863988 / 4.565676 (-2.701688) | 0.057662 / 0.424275 (-0.366613) | 0.006778 / 0.007607 (-0.000830) | 0.498661 / 0.226044 (0.272616) | 4.986503 / 2.268929 (2.717574) | 2.620676 / 55.444624 (-52.823949) | 2.297546 / 6.876477 (-4.578931) | 2.458148 / 2.142072 (0.316075) | 0.599490 / 4.805227 (-4.205738) | 0.125102 / 6.500664 (-6.375562) | 0.061411 / 0.075469 (-0.014059) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.323816 / 1.841788 (-0.517971) | 18.462614 / 8.074308 (10.388306) | 13.845826 / 10.191392 (3.654434) | 0.146115 / 0.680424 (-0.534309) | 0.016862 / 0.534201 (-0.517339) | 0.335449 / 0.579283 (-0.243834) | 0.343792 / 0.434364 (-0.090572) | 0.394068 / 0.540337 (-0.146269) | 0.536378 / 1.386936 (-0.850558) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#de3f00368c9236e9410821f5fddb95d6069883c1 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006825 / 0.011353 (-0.004527) | 0.004005 / 0.011008 (-0.007003) | 0.085504 / 0.038508 (0.046996) | 0.077252 / 0.023109 (0.054143) | 0.351891 / 0.275898 (0.075993) | 0.383404 / 0.323480 (0.059924) | 0.004153 / 0.007986 (-0.003833) | 0.003344 / 0.004328 (-0.000985) | 0.064936 / 0.004250 (0.060685) | 0.057653 / 0.037052 (0.020601) | 0.368155 / 0.258489 (0.109666) | 0.406122 / 0.293841 (0.112282) | 0.032049 / 0.128546 (-0.096497) | 0.008698 / 0.075646 (-0.066949) | 0.292394 / 0.419271 (-0.126878) | 0.053634 / 0.043533 (0.010101) | 0.358273 / 0.255139 (0.103134) | 0.378441 / 0.283200 (0.095242) | 0.026928 / 0.141683 (-0.114755) | 1.458718 / 1.452155 (0.006563) | 1.536231 / 1.492716 (0.043515) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.213956 / 0.018006 (0.195950) | 0.458620 / 0.000490 (0.458130) | 0.002718 / 0.000200 (0.002519) | 0.000078 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027870 / 0.037411 (-0.009541) | 0.083922 / 0.014526 (0.069396) | 0.152056 / 0.176557 (-0.024501) | 0.151584 / 0.737135 (-0.585552) | 0.095698 / 0.296338 (-0.200641) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.407762 / 0.215209 (0.192553) | 4.074324 / 2.077655 (1.996669) | 2.089929 / 1.504120 (0.585809) | 1.920024 / 1.541195 (0.378829) | 2.013410 / 1.468490 (0.544920) | 0.486056 / 4.584777 (-4.098721) | 3.656869 / 3.745712 (-0.088843) | 3.304008 / 5.269862 (-1.965854) | 2.074363 / 4.565676 (-2.491313) | 0.057293 / 0.424275 (-0.366982) | 0.007240 / 0.007607 (-0.000367) | 0.482696 / 0.226044 (0.256652) | 4.833251 / 2.268929 (2.564322) | 2.570391 / 55.444624 (-52.874233) | 2.220619 / 6.876477 (-4.655857) | 2.426316 / 2.142072 (0.284243) | 0.584811 / 4.805227 (-4.220416) | 0.134907 / 6.500664 (-6.365757) | 0.061115 / 0.075469 (-0.014354) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.251969 / 1.841788 (-0.589818) | 19.601611 / 8.074308 (11.527303) | 14.190217 / 10.191392 (3.998825) | 0.166296 / 0.680424 (-0.514128) | 0.018334 / 0.534201 (-0.515867) | 0.395172 / 0.579283 (-0.184111) | 0.410440 / 0.434364 (-0.023924) | 0.462263 / 0.540337 (-0.078074) | 0.645504 / 1.386936 (-0.741432) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006991 / 0.011353 (-0.004362) | 0.004084 / 0.011008 (-0.006924) | 0.065208 / 0.038508 (0.026700) | 0.077809 / 0.023109 (0.054699) | 0.386472 / 0.275898 (0.110574) | 0.418686 / 0.323480 (0.095206) | 0.005346 / 0.007986 (-0.002640) | 0.003416 / 0.004328 (-0.000912) | 0.066209 / 0.004250 (0.061958) | 0.057517 / 0.037052 (0.020465) | 0.407684 / 0.258489 (0.149195) | 0.425438 / 0.293841 (0.131597) | 0.032166 / 0.128546 (-0.096380) | 0.008662 / 0.075646 (-0.066985) | 0.071712 / 0.419271 (-0.347560) | 0.049764 / 0.043533 (0.006231) | 0.394882 / 0.255139 (0.139743) | 0.403589 / 0.283200 (0.120389) | 0.023688 / 0.141683 (-0.117995) | 1.468488 / 1.452155 (0.016334) | 1.533118 / 1.492716 (0.040401) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.252949 / 0.018006 (0.234943) | 0.447355 / 0.000490 (0.446865) | 0.011721 / 0.000200 (0.011521) | 0.000107 / 0.000054 (0.000052) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031444 / 0.037411 (-0.005968) | 0.089390 / 0.014526 (0.074864) | 0.100103 / 0.176557 (-0.076454) | 0.153301 / 0.737135 (-0.583835) | 0.101336 / 0.296338 (-0.195003) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.408574 / 0.215209 (0.193365) | 4.073135 / 2.077655 (1.995480) | 2.086550 / 1.504120 (0.582430) | 1.930651 / 1.541195 (0.389457) | 2.013548 / 1.468490 (0.545058) | 0.477235 / 4.584777 (-4.107542) | 3.547545 / 3.745712 (-0.198167) | 3.321957 / 5.269862 (-1.947905) | 2.057705 / 4.565676 (-2.507971) | 0.056730 / 0.424275 (-0.367545) | 0.007882 / 0.007607 (0.000275) | 0.487297 / 0.226044 (0.261253) | 4.874184 / 2.268929 (2.605255) | 2.631129 / 55.444624 (-52.813496) | 2.235755 / 6.876477 (-4.640722) | 2.463329 / 2.142072 (0.321257) | 0.578308 / 4.805227 (-4.226919) | 0.132726 / 6.500664 (-6.367938) | 0.064883 / 0.075469 (-0.010586) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.347564 / 1.841788 (-0.494223) | 20.192973 / 8.074308 (12.118665) | 14.563553 / 10.191392 (4.372161) | 0.168244 / 0.680424 (-0.512180) | 0.018638 / 0.534201 (-0.515563) | 0.394789 / 0.579283 (-0.184494) | 0.419677 / 0.434364 (-0.014687) | 0.480274 / 0.540337 (-0.060063) | 0.641204 / 1.386936 (-0.745732) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9c7a0d56b60bf700d6a491fa30eaf66500969315 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005939 / 0.011353 (-0.005413) | 0.003457 / 0.011008 (-0.007551) | 0.079985 / 0.038508 (0.041477) | 0.056492 / 0.023109 (0.033383) | 0.312356 / 0.275898 (0.036458) | 0.354038 / 0.323480 (0.030558) | 0.004551 / 0.007986 (-0.003435) | 0.002828 / 0.004328 (-0.001501) | 0.062369 / 0.004250 (0.058119) | 0.044712 / 0.037052 (0.007660) | 0.318244 / 0.258489 (0.059755) | 0.361977 / 0.293841 (0.068136) | 0.026460 / 0.128546 (-0.102086) | 0.007928 / 0.075646 (-0.067719) | 0.261378 / 0.419271 (-0.157894) | 0.044209 / 0.043533 (0.000676) | 0.313931 / 0.255139 (0.058792) | 0.339553 / 0.283200 (0.056354) | 0.019776 / 0.141683 (-0.121907) | 1.443126 / 1.452155 (-0.009029) | 1.508149 / 1.492716 (0.015432) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.183801 / 0.018006 (0.165795) | 0.427967 / 0.000490 (0.427477) | 0.002028 / 0.000200 (0.001828) | 0.000062 / 0.000054 (0.000007) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023697 / 0.037411 (-0.013715) | 0.072128 / 0.014526 (0.057602) | 0.083701 / 0.176557 (-0.092855) | 0.142821 / 0.737135 (-0.594315) | 0.082276 / 0.296338 (-0.214063) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434427 / 0.215209 (0.219218) | 4.325962 / 2.077655 (2.248308) | 2.277115 / 1.504120 (0.772995) | 2.093736 / 1.541195 (0.552541) | 2.127984 / 1.468490 (0.659494) | 0.502336 / 4.584777 (-4.082441) | 3.023243 / 3.745712 (-0.722469) | 2.805154 / 5.269862 (-2.464708) | 1.821273 / 4.565676 (-2.744403) | 0.057480 / 0.424275 (-0.366795) | 0.006365 / 0.007607 (-0.001242) | 0.508258 / 0.226044 (0.282213) | 5.087950 / 2.268929 (2.819022) | 2.705029 / 55.444624 (-52.739596) | 2.378392 / 6.876477 (-4.498085) | 2.515380 / 2.142072 (0.373307) | 0.589283 / 4.805227 (-4.215944) | 0.125719 / 6.500664 (-6.374945) | 0.061074 / 0.075469 (-0.014395) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.221895 / 1.841788 (-0.619893) | 18.025917 / 8.074308 (9.951609) | 13.556901 / 10.191392 (3.365509) | 0.142614 / 0.680424 (-0.537809) | 0.016731 / 0.534201 (-0.517469) | 0.328374 / 0.579283 (-0.250910) | 0.342553 / 0.434364 (-0.091811) | 0.374502 / 0.540337 (-0.165836) | 0.534173 / 1.386936 (-0.852763) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005817 / 0.011353 (-0.005536) | 0.003500 / 0.011008 (-0.007509) | 0.062240 / 0.038508 (0.023732) | 0.058128 / 0.023109 (0.035019) | 0.424014 / 0.275898 (0.148116) | 0.468453 / 0.323480 (0.144973) | 0.004641 / 0.007986 (-0.003345) | 0.002821 / 0.004328 (-0.001508) | 0.062180 / 0.004250 (0.057930) | 0.047578 / 0.037052 (0.010526) | 0.427367 / 0.258489 (0.168878) | 0.467889 / 0.293841 (0.174048) | 0.027144 / 0.128546 (-0.101403) | 0.007969 / 0.075646 (-0.067678) | 0.067764 / 0.419271 (-0.351508) | 0.040719 / 0.043533 (-0.002814) | 0.423663 / 0.255139 (0.168524) | 0.458556 / 0.283200 (0.175356) | 0.019196 / 0.141683 (-0.122487) | 1.471546 / 1.452155 (0.019392) | 1.547541 / 1.492716 (0.054825) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228777 / 0.018006 (0.210770) | 0.406663 / 0.000490 (0.406173) | 0.003688 / 0.000200 (0.003488) | 0.000075 / 0.000054 (0.000021) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025494 / 0.037411 (-0.011917) | 0.076339 / 0.014526 (0.061814) | 0.084233 / 0.176557 (-0.092324) | 0.136995 / 0.737135 (-0.600140) | 0.085443 / 0.296338 (-0.210895) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420441 / 0.215209 (0.205232) | 4.187018 / 2.077655 (2.109363) | 2.142139 / 1.504120 (0.638019) | 1.974530 / 1.541195 (0.433335) | 2.027321 / 1.468490 (0.558831) | 0.498116 / 4.584777 (-4.086661) | 2.988514 / 3.745712 (-0.757198) | 2.782046 / 5.269862 (-2.487816) | 1.821725 / 4.565676 (-2.743951) | 0.057711 / 0.424275 (-0.366564) | 0.006664 / 0.007607 (-0.000944) | 0.491015 / 0.226044 (0.264971) | 4.921037 / 2.268929 (2.652108) | 2.574964 / 55.444624 (-52.869661) | 2.251703 / 6.876477 (-4.624774) | 2.361154 / 2.142072 (0.219082) | 0.593362 / 4.805227 (-4.211865) | 0.126107 / 6.500664 (-6.374557) | 0.061840 / 0.075469 (-0.013630) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.327459 / 1.841788 (-0.514328) | 18.062960 / 8.074308 (9.988652) | 13.669253 / 10.191392 (3.477861) | 0.130719 / 0.680424 (-0.549705) | 0.016564 / 0.534201 (-0.517637) | 0.335821 / 0.579283 (-0.243462) | 0.341691 / 0.434364 (-0.092673) | 0.392651 / 0.540337 (-0.147686) | 0.529650 / 1.386936 (-0.857286) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c65806b0542996e56825ab46a3ce8f9c07ab0df3 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009625 / 0.011353 (-0.001728) | 0.005354 / 0.011008 (-0.005654) | 0.114350 / 0.038508 (0.075842) | 0.086637 / 0.023109 (0.063528) | 0.465381 / 0.275898 (0.189483) | 0.490411 / 0.323480 (0.166931) | 0.006575 / 0.007986 (-0.001411) | 0.004287 / 0.004328 (-0.000041) | 0.093134 / 0.004250 (0.088884) | 0.060209 / 0.037052 (0.023156) | 0.459570 / 0.258489 (0.201080) | 0.523320 / 0.293841 (0.229479) | 0.047943 / 0.128546 (-0.080603) | 0.014764 / 0.075646 (-0.060882) | 0.383887 / 0.419271 (-0.035384) | 0.069864 / 0.043533 (0.026331) | 0.469122 / 0.255139 (0.213983) | 0.509953 / 0.283200 (0.226753) | 0.037800 / 0.141683 (-0.103883) | 1.877589 / 1.452155 (0.425434) | 2.014913 / 1.492716 (0.522197) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.309146 / 0.018006 (0.291140) | 0.644390 / 0.000490 (0.643900) | 0.005017 / 0.000200 (0.004817) | 0.000102 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032964 / 0.037411 (-0.004447) | 0.103236 / 0.014526 (0.088711) | 0.119950 / 0.176557 (-0.056607) | 0.207674 / 0.737135 (-0.529461) | 0.117278 / 0.296338 (-0.179060) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.605464 / 0.215209 (0.390255) | 6.027805 / 2.077655 (3.950150) | 2.719725 / 1.504120 (1.215605) | 2.262752 / 1.541195 (0.721558) | 2.330310 / 1.468490 (0.861820) | 0.862537 / 4.584777 (-3.722240) | 5.347080 / 3.745712 (1.601368) | 4.792170 / 5.269862 (-0.477691) | 3.103694 / 4.565676 (-1.461983) | 0.103646 / 0.424275 (-0.320629) | 0.009411 / 0.007607 (0.001804) | 0.743052 / 0.226044 (0.517008) | 7.289684 / 2.268929 (5.020755) | 3.436530 / 55.444624 (-52.008094) | 2.722440 / 6.876477 (-4.154036) | 2.952380 / 2.142072 (0.810308) | 1.047688 / 4.805227 (-3.757539) | 0.212724 / 6.500664 (-6.287940) | 0.081473 / 0.075469 (0.006004) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.714437 / 1.841788 (-0.127351) | 24.384330 / 8.074308 (16.310022) | 22.444162 / 10.191392 (12.252770) | 0.226264 / 0.680424 (-0.454160) | 0.030530 / 0.534201 (-0.503671) | 0.473999 / 0.579283 (-0.105284) | 0.575005 / 0.434364 (0.140641) | 0.542789 / 0.540337 (0.002451) | 0.776079 / 1.386936 (-0.610857) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009366 / 0.011353 (-0.001987) | 0.005239 / 0.011008 (-0.005769) | 0.085116 / 0.038508 (0.046608) | 0.089600 / 0.023109 (0.066491) | 0.485778 / 0.275898 (0.209880) | 0.540054 / 0.323480 (0.216574) | 0.006290 / 0.007986 (-0.001695) | 0.004054 / 0.004328 (-0.000274) | 0.083535 / 0.004250 (0.079284) | 0.067200 / 0.037052 (0.030148) | 0.519520 / 0.258489 (0.261031) | 0.544049 / 0.293841 (0.250208) | 0.054300 / 0.128546 (-0.074246) | 0.013650 / 0.075646 (-0.061996) | 0.102515 / 0.419271 (-0.316757) | 0.063054 / 0.043533 (0.019522) | 0.491724 / 0.255139 (0.236585) | 0.547498 / 0.283200 (0.264298) | 0.039266 / 0.141683 (-0.102416) | 1.801226 / 1.452155 (0.349071) | 1.861778 / 1.492716 (0.369061) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.313009 / 0.018006 (0.295003) | 0.587695 / 0.000490 (0.587205) | 0.004972 / 0.000200 (0.004772) | 0.000110 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029230 / 0.037411 (-0.008181) | 0.091154 / 0.014526 (0.076628) | 0.110505 / 0.176557 (-0.066052) | 0.164204 / 0.737135 (-0.572932) | 0.107812 / 0.296338 (-0.188526) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.610535 / 0.215209 (0.395326) | 6.162517 / 2.077655 (4.084862) | 2.866718 / 1.504120 (1.362598) | 2.542412 / 1.541195 (1.001218) | 2.584136 / 1.468490 (1.115645) | 0.874319 / 4.584777 (-3.710458) | 5.257184 / 3.745712 (1.511472) | 4.705840 / 5.269862 (-0.564022) | 2.971708 / 4.565676 (-1.593969) | 0.099026 / 0.424275 (-0.325249) | 0.009142 / 0.007607 (0.001535) | 0.728660 / 0.226044 (0.502615) | 7.560922 / 2.268929 (5.291994) | 3.439521 / 55.444624 (-52.005103) | 2.854730 / 6.876477 (-4.021746) | 3.088951 / 2.142072 (0.946879) | 0.973621 / 4.805227 (-3.831606) | 0.209792 / 6.500664 (-6.290872) | 0.081107 / 0.075469 (0.005638) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.716809 / 1.841788 (-0.124978) | 24.386927 / 8.074308 (16.312619) | 20.715524 / 10.191392 (10.524131) | 0.260831 / 0.680424 (-0.419592) | 0.030701 / 0.534201 (-0.503500) | 0.490018 / 0.579283 (-0.089265) | 0.590424 / 0.434364 (0.156060) | 0.589942 / 0.540337 (0.049604) | 0.798094 / 1.386936 (-0.588842) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c0a77dc943de68a17f23f141517028c734c78623 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006592 / 0.011353 (-0.004761) | 0.003880 / 0.011008 (-0.007128) | 0.083761 / 0.038508 (0.045253) | 0.075966 / 0.023109 (0.052857) | 0.315291 / 0.275898 (0.039393) | 0.355920 / 0.323480 (0.032440) | 0.004972 / 0.007986 (-0.003014) | 0.003053 / 0.004328 (-0.001275) | 0.063553 / 0.004250 (0.059302) | 0.050794 / 0.037052 (0.013742) | 0.317681 / 0.258489 (0.059192) | 0.361991 / 0.293841 (0.068150) | 0.028119 / 0.128546 (-0.100427) | 0.008203 / 0.075646 (-0.067443) | 0.271756 / 0.419271 (-0.147516) | 0.046701 / 0.043533 (0.003168) | 0.316520 / 0.255139 (0.061381) | 0.350499 / 0.283200 (0.067300) | 0.022399 / 0.141683 (-0.119284) | 1.416017 / 1.452155 (-0.036138) | 1.503087 / 1.492716 (0.010371) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208250 / 0.018006 (0.190244) | 0.470345 / 0.000490 (0.469856) | 0.003687 / 0.000200 (0.003487) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026163 / 0.037411 (-0.011248) | 0.083315 / 0.014526 (0.068789) | 0.088541 / 0.176557 (-0.088015) | 0.150078 / 0.737135 (-0.587057) | 0.088862 / 0.296338 (-0.207476) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.404911 / 0.215209 (0.189702) | 4.059257 / 2.077655 (1.981602) | 1.890987 / 1.504120 (0.386867) | 1.726608 / 1.541195 (0.185413) | 1.767479 / 1.468490 (0.298989) | 0.518826 / 4.584777 (-4.065951) | 3.212145 / 3.745712 (-0.533567) | 3.029933 / 5.269862 (-2.239929) | 2.000203 / 4.565676 (-2.565474) | 0.059631 / 0.424275 (-0.364644) | 0.006707 / 0.007607 (-0.000900) | 0.485741 / 0.226044 (0.259697) | 4.871938 / 2.268929 (2.603010) | 2.418856 / 55.444624 (-53.025769) | 2.084847 / 6.876477 (-4.791630) | 2.207992 / 2.142072 (0.065920) | 0.614354 / 4.805227 (-4.190873) | 0.128932 / 6.500664 (-6.371732) | 0.062342 / 0.075469 (-0.013127) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.325792 / 1.841788 (-0.515995) | 19.718995 / 8.074308 (11.644687) | 15.278535 / 10.191392 (5.087143) | 0.146719 / 0.680424 (-0.533705) | 0.017718 / 0.534201 (-0.516483) | 0.335709 / 0.579283 (-0.243574) | 0.378060 / 0.434364 (-0.056304) | 0.391135 / 0.540337 (-0.149202) | 0.548045 / 1.386936 (-0.838891) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006504 / 0.011353 (-0.004849) | 0.003742 / 0.011008 (-0.007266) | 0.064405 / 0.038508 (0.025897) | 0.077618 / 0.023109 (0.054509) | 0.365325 / 0.275898 (0.089427) | 0.408109 / 0.323480 (0.084629) | 0.004909 / 0.007986 (-0.003076) | 0.002972 / 0.004328 (-0.001356) | 0.063933 / 0.004250 (0.059682) | 0.052916 / 0.037052 (0.015863) | 0.370891 / 0.258489 (0.112402) | 0.412134 / 0.293841 (0.118293) | 0.028171 / 0.128546 (-0.100375) | 0.008150 / 0.075646 (-0.067497) | 0.069248 / 0.419271 (-0.350024) | 0.042353 / 0.043533 (-0.001180) | 0.368117 / 0.255139 (0.112978) | 0.397548 / 0.283200 (0.114348) | 0.022967 / 0.141683 (-0.118716) | 1.472740 / 1.452155 (0.020586) | 1.524028 / 1.492716 (0.031311) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.256854 / 0.018006 (0.238848) | 0.471499 / 0.000490 (0.471009) | 0.009609 / 0.000200 (0.009409) | 0.000109 / 0.000054 (0.000054) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027978 / 0.037411 (-0.009433) | 0.086741 / 0.014526 (0.072215) | 0.091189 / 0.176557 (-0.085368) | 0.146117 / 0.737135 (-0.591018) | 0.092358 / 0.296338 (-0.203980) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426356 / 0.215209 (0.211147) | 4.263782 / 2.077655 (2.186127) | 2.178198 / 1.504120 (0.674078) | 2.015405 / 1.541195 (0.474211) | 2.055966 / 1.468490 (0.587476) | 0.507531 / 4.584777 (-4.077246) | 3.175967 / 3.745712 (-0.569745) | 3.055697 / 5.269862 (-2.214165) | 1.987663 / 4.565676 (-2.578014) | 0.058452 / 0.424275 (-0.365823) | 0.006944 / 0.007607 (-0.000663) | 0.502534 / 0.226044 (0.276489) | 5.024693 / 2.268929 (2.755765) | 2.754971 / 55.444624 (-52.689653) | 2.470845 / 6.876477 (-4.405632) | 2.698675 / 2.142072 (0.556602) | 0.602357 / 4.805227 (-4.202871) | 0.129490 / 6.500664 (-6.371174) | 0.065127 / 0.075469 (-0.010342) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.398487 / 1.841788 (-0.443301) | 19.692279 / 8.074308 (11.617971) | 15.124064 / 10.191392 (4.932672) | 0.148938 / 0.680424 (-0.531486) | 0.017418 / 0.534201 (-0.516783) | 0.340480 / 0.579283 (-0.238803) | 0.377223 / 0.434364 (-0.057141) | 0.405303 / 0.540337 (-0.135034) | 0.548923 / 1.386936 (-0.838013) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#58e62af004b6b8b84dcfd897a4bc71637cfa6c3f \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006433 / 0.011353 (-0.004920) | 0.004002 / 0.011008 (-0.007006) | 0.084130 / 0.038508 (0.045622) | 0.070628 / 0.023109 (0.047519) | 0.312372 / 0.275898 (0.036474) | 0.343993 / 0.323480 (0.020513) | 0.003936 / 0.007986 (-0.004050) | 0.003336 / 0.004328 (-0.000993) | 0.064715 / 0.004250 (0.060465) | 0.052511 / 0.037052 (0.015458) | 0.314092 / 0.258489 (0.055603) | 0.363152 / 0.293841 (0.069311) | 0.030898 / 0.128546 (-0.097648) | 0.008396 / 0.075646 (-0.067250) | 0.288083 / 0.419271 (-0.131188) | 0.051654 / 0.043533 (0.008122) | 0.315252 / 0.255139 (0.060113) | 0.346756 / 0.283200 (0.063556) | 0.025167 / 0.141683 (-0.116515) | 1.487265 / 1.452155 (0.035110) | 1.557528 / 1.492716 (0.064812) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206517 / 0.018006 (0.188510) | 0.458359 / 0.000490 (0.457869) | 0.003719 / 0.000200 (0.003519) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029631 / 0.037411 (-0.007780) | 0.083856 / 0.014526 (0.069330) | 0.340431 / 0.176557 (0.163875) | 0.153864 / 0.737135 (-0.583271) | 0.095951 / 0.296338 (-0.200388) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.379182 / 0.215209 (0.163973) | 3.783396 / 2.077655 (1.705741) | 1.835932 / 1.504120 (0.331813) | 1.667563 / 1.541195 (0.126369) | 1.739309 / 1.468490 (0.270818) | 0.478957 / 4.584777 (-4.105820) | 3.521974 / 3.745712 (-0.223738) | 3.237635 / 5.269862 (-2.032227) | 2.000300 / 4.565676 (-2.565377) | 0.056389 / 0.424275 (-0.367887) | 0.007242 / 0.007607 (-0.000365) | 0.452642 / 0.226044 (0.226598) | 4.524339 / 2.268929 (2.255411) | 2.346210 / 55.444624 (-53.098414) | 1.957196 / 6.876477 (-4.919281) | 2.180051 / 2.142072 (0.037979) | 0.570205 / 4.805227 (-4.235022) | 0.131346 / 6.500664 (-6.369318) | 0.059327 / 0.075469 (-0.016142) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.244709 / 1.841788 (-0.597079) | 19.566277 / 8.074308 (11.491969) | 14.172598 / 10.191392 (3.981206) | 0.166493 / 0.680424 (-0.513931) | 0.018281 / 0.534201 (-0.515920) | 0.391608 / 0.579283 (-0.187675) | 0.402642 / 0.434364 (-0.031722) | 0.464974 / 0.540337 (-0.075364) | 0.637565 / 1.386936 (-0.749371) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006929 / 0.011353 (-0.004424) | 0.004114 / 0.011008 (-0.006894) | 0.064589 / 0.038508 (0.026081) | 0.083334 / 0.023109 (0.060225) | 0.391280 / 0.275898 (0.115382) | 0.426157 / 0.323480 (0.102678) | 0.005336 / 0.007986 (-0.002650) | 0.003395 / 0.004328 (-0.000934) | 0.064560 / 0.004250 (0.060310) | 0.057094 / 0.037052 (0.020042) | 0.398959 / 0.258489 (0.140470) | 0.432470 / 0.293841 (0.138629) | 0.031412 / 0.128546 (-0.097134) | 0.008670 / 0.075646 (-0.066976) | 0.071249 / 0.419271 (-0.348022) | 0.048934 / 0.043533 (0.005401) | 0.384207 / 0.255139 (0.129068) | 0.407992 / 0.283200 (0.124792) | 0.024492 / 0.141683 (-0.117191) | 1.467788 / 1.452155 (0.015634) | 1.541011 / 1.492716 (0.048295) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.279607 / 0.018006 (0.261600) | 0.448899 / 0.000490 (0.448410) | 0.020990 / 0.000200 (0.020790) | 0.000132 / 0.000054 (0.000078) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030313 / 0.037411 (-0.007099) | 0.089209 / 0.014526 (0.074684) | 0.101024 / 0.176557 (-0.075532) | 0.153468 / 0.737135 (-0.583667) | 0.103219 / 0.296338 (-0.193120) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429176 / 0.215209 (0.213967) | 4.302234 / 2.077655 (2.224580) | 2.291103 / 1.504120 (0.786983) | 2.126257 / 1.541195 (0.585062) | 2.207090 / 1.468490 (0.738600) | 0.484643 / 4.584777 (-4.100134) | 3.557429 / 3.745712 (-0.188283) | 3.253804 / 5.269862 (-2.016058) | 2.026087 / 4.565676 (-2.539589) | 0.057793 / 0.424275 (-0.366482) | 0.007761 / 0.007607 (0.000154) | 0.504819 / 0.226044 (0.278775) | 5.046868 / 2.268929 (2.777940) | 2.773149 / 55.444624 (-52.671475) | 2.398036 / 6.876477 (-4.478440) | 2.608094 / 2.142072 (0.466021) | 0.630499 / 4.805227 (-4.174729) | 0.135496 / 6.500664 (-6.365168) | 0.061329 / 0.075469 (-0.014140) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.327124 / 1.841788 (-0.514664) | 19.889796 / 8.074308 (11.815488) | 14.196100 / 10.191392 (4.004708) | 0.161963 / 0.680424 (-0.518461) | 0.018529 / 0.534201 (-0.515672) | 0.392325 / 0.579283 (-0.186958) | 0.404836 / 0.434364 (-0.029528) | 0.475898 / 0.540337 (-0.064439) | 0.633563 / 1.386936 (-0.753373) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e4684fc1032321abf0d494b0c130ea7c82ebda80 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006390 / 0.011353 (-0.004963) | 0.003683 / 0.011008 (-0.007325) | 0.081274 / 0.038508 (0.042766) | 0.062193 / 0.023109 (0.039083) | 0.355360 / 0.275898 (0.079462) | 0.396471 / 0.323480 (0.072992) | 0.003569 / 0.007986 (-0.004416) | 0.003928 / 0.004328 (-0.000400) | 0.062292 / 0.004250 (0.058041) | 0.049700 / 0.037052 (0.012648) | 0.354604 / 0.258489 (0.096115) | 0.419436 / 0.293841 (0.125595) | 0.027151 / 0.128546 (-0.101395) | 0.007954 / 0.075646 (-0.067692) | 0.262231 / 0.419271 (-0.157041) | 0.045483 / 0.043533 (0.001950) | 0.354285 / 0.255139 (0.099146) | 0.385178 / 0.283200 (0.101978) | 0.021183 / 0.141683 (-0.120500) | 1.420785 / 1.452155 (-0.031370) | 1.531545 / 1.492716 (0.038829) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202298 / 0.018006 (0.184292) | 0.442172 / 0.000490 (0.441683) | 0.003565 / 0.000200 (0.003366) | 0.000074 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024229 / 0.037411 (-0.013183) | 0.074352 / 0.014526 (0.059826) | 0.087530 / 0.176557 (-0.089026) | 0.146478 / 0.737135 (-0.590658) | 0.085145 / 0.296338 (-0.211194) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.388395 / 0.215209 (0.173186) | 3.877623 / 2.077655 (1.799968) | 1.882444 / 1.504120 (0.378324) | 1.707871 / 1.541195 (0.166676) | 1.772132 / 1.468490 (0.303642) | 0.491937 / 4.584777 (-4.092840) | 3.057947 / 3.745712 (-0.687765) | 2.822390 / 5.269862 (-2.447471) | 1.879719 / 4.565676 (-2.685957) | 0.056830 / 0.424275 (-0.367445) | 0.006415 / 0.007607 (-0.001192) | 0.458945 / 0.226044 (0.232900) | 4.594502 / 2.268929 (2.325574) | 2.339677 / 55.444624 (-53.104948) | 1.983750 / 6.876477 (-4.892727) | 2.173792 / 2.142072 (0.031719) | 0.580390 / 4.805227 (-4.224838) | 0.124568 / 6.500664 (-6.376096) | 0.061694 / 0.075469 (-0.013775) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.265108 / 1.841788 (-0.576680) | 18.415254 / 8.074308 (10.340946) | 13.963829 / 10.191392 (3.772437) | 0.148926 / 0.680424 (-0.531498) | 0.016919 / 0.534201 (-0.517282) | 0.331082 / 0.579283 (-0.248201) | 0.345777 / 0.434364 (-0.088587) | 0.381123 / 0.540337 (-0.159214) | 0.543297 / 1.386936 (-0.843639) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006121 / 0.011353 (-0.005232) | 0.003717 / 0.011008 (-0.007291) | 0.063653 / 0.038508 (0.025144) | 0.063723 / 0.023109 (0.040613) | 0.360233 / 0.275898 (0.084335) | 0.398353 / 0.323480 (0.074873) | 0.004696 / 0.007986 (-0.003290) | 0.002876 / 0.004328 (-0.001452) | 0.063057 / 0.004250 (0.058806) | 0.050258 / 0.037052 (0.013206) | 0.362946 / 0.258489 (0.104457) | 0.403260 / 0.293841 (0.109419) | 0.027738 / 0.128546 (-0.100809) | 0.008025 / 0.075646 (-0.067621) | 0.068781 / 0.419271 (-0.350491) | 0.042114 / 0.043533 (-0.001419) | 0.363546 / 0.255139 (0.108407) | 0.385640 / 0.283200 (0.102440) | 0.021757 / 0.141683 (-0.119926) | 1.482364 / 1.452155 (0.030209) | 1.571859 / 1.492716 (0.079143) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235628 / 0.018006 (0.217622) | 0.439909 / 0.000490 (0.439419) | 0.003070 / 0.000200 (0.002870) | 0.000075 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027045 / 0.037411 (-0.010366) | 0.080413 / 0.014526 (0.065887) | 0.088953 / 0.176557 (-0.087603) | 0.141907 / 0.737135 (-0.595228) | 0.090604 / 0.296338 (-0.205735) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.423250 / 0.215209 (0.208041) | 4.216510 / 2.077655 (2.138855) | 2.162946 / 1.504120 (0.658826) | 2.014561 / 1.541195 (0.473366) | 2.086347 / 1.468490 (0.617857) | 0.496591 / 4.584777 (-4.088186) | 3.089594 / 3.745712 (-0.656118) | 2.853640 / 5.269862 (-2.416221) | 1.878149 / 4.565676 (-2.687527) | 0.056914 / 0.424275 (-0.367361) | 0.006762 / 0.007607 (-0.000845) | 0.493470 / 0.226044 (0.267426) | 4.929966 / 2.268929 (2.661037) | 2.640885 / 55.444624 (-52.803739) | 2.335950 / 6.876477 (-4.540527) | 2.565866 / 2.142072 (0.423793) | 0.585433 / 4.805227 (-4.219794) | 0.124969 / 6.500664 (-6.375695) | 0.062361 / 0.075469 (-0.013108) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.369144 / 1.841788 (-0.472644) | 19.037582 / 8.074308 (10.963274) | 14.069141 / 10.191392 (3.877749) | 0.146469 / 0.680424 (-0.533954) | 0.016911 / 0.534201 (-0.517290) | 0.336802 / 0.579283 (-0.242482) | 0.336411 / 0.434364 (-0.097953) | 0.392360 / 0.540337 (-0.147977) | 0.536078 / 1.386936 (-0.850858) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#12cfc1196e62847e2e8239fbd727a02cbc86ddec \"CML watermark\")\n" ]

"2023-08-07T15:41:25Z"

"2023-08-08T15:24:59Z"

"2023-08-08T15:16:22Z"

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[ "Our CI did not catch this issue because with current implementation, stored token in `HfFolder` (which always exists) is used by default.", "I can confirm this and have the same problem (and just went almost crazy because I couldn't figure out the source of this problem because on another computer everything worked well even with `DownloadMode.FORCE_REDOWNLOAD`).", "We are planning to do a patch release today, after the merge of the fix:\r\n- #6127\r\n\r\nIn the meantime, the problem can be circumvented by passing `download_config` instead:\r\n```python\r\nfrom datasets import DownloadConfig, load_dataset\r\n\r\nload_dataset(\"<DATASET-NAME>\", split=\"train\", download_config=DownloadConfig(token=\"<TOKEN>\"))\r\n``` ", "> We are planning to do a patch release today, after the merge of the fix:\r\n> \r\n> * [Fix authentication issues #6127](https://github.com/huggingface/datasets/pull/6127)\r\n> \r\n> \r\n> In the meantime, the problem can be circumvented by passing `download_config` instead:\r\n> \r\n> ```python\r\n> from datasets import DownloadConfig, load_dataset\r\n> \r\n> load_dataset(\"<DATASET-NAME>\", split=\"train\", download_config=DownloadConfig(token=\"<TOKEN>\"))\r\n> ```\r\n\r\nThis did not work for me (there was some other error with the split being an unexpected size 0). Downgrading to 2.13 fixed it...." ]

"2023-08-07T15:06:47Z"

"2023-08-08T15:16:23Z"

"2023-08-08T15:16:23Z"

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"2023-08-05T23:59:42Z"

"2023-08-18T12:28:42Z"

"2023-08-18T12:28:42Z"

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[ "i once had the same error and I could fix that by pushing a fake or a dummy commit on my hugging face dataset repo", "Hi! We need a reproducer to fix this. Can you provide a link to the dataset (if it's public)?", "> Hi! We need a reproducer to fix this. Can you provide a link to the dataset (if it's public)?\r\n\r\nHi Mario,\r\n\r\nUnfortunately, the dataset in question is currently private until the model is trained and released.\r\n\r\nThis is not happening with one dataset but numerous hosted private datasets.\r\n\r\nI am only loading the dataset and doing nothing else currently. It seems to happen completely sporadically.\r\n\r\nThank you,\r\n\r\nEnrico" ]

"2023-08-05T17:48:56Z"

"2023-08-20T17:33:15Z"

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[ "Hi! Thanks for the investigation, but we are not the authors of these datasets, so please report this on the Hub instead so that the actual authors can fix it." ]

"2023-08-05T14:34:13Z"

"2023-08-17T14:25:27Z"

"2023-08-17T14:25:26Z"

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[]

[ "You can use `huggingface_hub`'s [Card API](https://huggingface.co/docs/huggingface_hub/package_reference/cards) to programmatically push a dataset card to the Hub." ]

"2023-08-04T21:00:27Z"

"2023-08-21T18:18:54Z"

"2023-08-21T18:18:54Z"

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[ "Hi,\r\n\r\nI found a small typo in the code example of create imagefolder dataset. It confused me a little when I first saw it.\r\n\r\nBest Regards.\r\n\r\nXin" ]

"2023-08-04T13:36:59Z"

"2023-08-04T13:45:32Z"

"2023-08-04T13:41:43Z"

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[]

[ "In which format is your dataset? We could expose the `pre_buffer` flag for Parquet to use PyArrow's background thread pool to speed up loading. " ]

"2023-08-04T04:01:52Z"

"2023-08-17T17:48:42Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007755 / 0.011353 (-0.003598) | 0.004618 / 0.011008 (-0.006391) | 0.098132 / 0.038508 (0.059624) | 0.086759 / 0.023109 (0.063650) | 0.374668 / 0.275898 (0.098770) | 0.417131 / 0.323480 (0.093651) | 0.004604 / 0.007986 (-0.003382) | 0.005461 / 0.004328 (0.001132) | 0.077249 / 0.004250 (0.072999) | 0.063247 / 0.037052 (0.026195) | 0.391801 / 0.258489 (0.133312) | 0.432139 / 0.293841 (0.138298) | 0.036755 / 0.128546 (-0.091791) | 0.010011 / 0.075646 (-0.065636) | 0.346175 / 0.419271 (-0.073097) | 0.061503 / 0.043533 (0.017971) | 0.374063 / 0.255139 (0.118924) | 0.435873 / 0.283200 (0.152673) | 0.029476 / 0.141683 (-0.112207) | 1.786945 / 1.452155 (0.334790) | 1.857190 / 1.492716 (0.364474) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.253939 / 0.018006 (0.235933) | 0.506847 / 0.000490 (0.506358) | 0.007278 / 0.000200 (0.007079) | 0.000451 / 0.000054 (0.000397) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032938 / 0.037411 (-0.004474) | 0.097493 / 0.014526 (0.082967) | 0.112090 / 0.176557 (-0.064467) | 0.177986 / 0.737135 (-0.559149) | 0.112060 / 0.296338 (-0.184278) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.481858 / 0.215209 (0.266649) | 4.814894 / 2.077655 (2.737239) | 2.496428 / 1.504120 (0.992308) | 2.309965 / 1.541195 (0.768770) | 2.393819 / 1.468490 (0.925329) | 0.564670 / 4.584777 (-4.020107) | 4.151222 / 3.745712 (0.405510) | 3.676115 / 5.269862 (-1.593747) | 2.346165 / 4.565676 (-2.219512) | 0.066344 / 0.424275 (-0.357931) | 0.009006 / 0.007607 (0.001399) | 0.567699 / 0.226044 (0.341654) | 5.686799 / 2.268929 (3.417871) | 3.031044 / 55.444624 (-52.413580) | 2.606259 / 6.876477 (-4.270217) | 2.864876 / 2.142072 (0.722804) | 0.681730 / 4.805227 (-4.123498) | 0.155405 / 6.500664 (-6.345259) | 0.071492 / 0.075469 (-0.003977) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.514446 / 1.841788 (-0.327341) | 22.624912 / 8.074308 (14.550604) | 16.754145 / 10.191392 (6.562753) | 0.193113 / 0.680424 (-0.487311) | 0.021808 / 0.534201 (-0.512393) | 0.468241 / 0.579283 (-0.111042) | 0.499647 / 0.434364 (0.065283) | 0.539571 / 0.540337 (-0.000766) | 0.771268 / 1.386936 (-0.615668) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007562 / 0.011353 (-0.003791) | 0.004548 / 0.011008 (-0.006460) | 0.075998 / 0.038508 (0.037490) | 0.081648 / 0.023109 (0.058539) | 0.462876 / 0.275898 (0.186978) | 0.499366 / 0.323480 (0.175886) | 0.005839 / 0.007986 (-0.002147) | 0.003753 / 0.004328 (-0.000576) | 0.075918 / 0.004250 (0.071668) | 0.063233 / 0.037052 (0.026181) | 0.459024 / 0.258489 (0.200535) | 0.506388 / 0.293841 (0.212547) | 0.036179 / 0.128546 (-0.092367) | 0.009961 / 0.075646 (-0.065685) | 0.082061 / 0.419271 (-0.337211) | 0.056469 / 0.043533 (0.012936) | 0.459567 / 0.255139 (0.204428) | 0.482578 / 0.283200 (0.199378) | 0.026363 / 0.141683 (-0.115320) | 1.742247 / 1.452155 (0.290092) | 1.807166 / 1.492716 (0.314450) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.330526 / 0.018006 (0.312520) | 0.511674 / 0.000490 (0.511184) | 0.040969 / 0.000200 (0.040769) | 0.000176 / 0.000054 (0.000121) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035492 / 0.037411 (-0.001920) | 0.104338 / 0.014526 (0.089813) | 0.116973 / 0.176557 (-0.059583) | 0.180218 / 0.737135 (-0.556917) | 0.118801 / 0.296338 (-0.177538) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.492196 / 0.215209 (0.276987) | 4.910271 / 2.077655 (2.832616) | 2.542562 / 1.504120 (1.038442) | 2.333516 / 1.541195 (0.792321) | 2.439682 / 1.468490 (0.971192) | 0.571966 / 4.584777 (-4.012811) | 4.089801 / 3.745712 (0.344089) | 3.732129 / 5.269862 (-1.537733) | 2.375887 / 4.565676 (-2.189789) | 0.067376 / 0.424275 (-0.356900) | 0.008350 / 0.007607 (0.000743) | 0.583942 / 0.226044 (0.357897) | 5.840002 / 2.268929 (3.571074) | 3.062520 / 55.444624 (-52.382104) | 2.722512 / 6.876477 (-4.153965) | 2.938307 / 2.142072 (0.796234) | 0.689459 / 4.805227 (-4.115769) | 0.155632 / 6.500664 (-6.345032) | 0.072387 / 0.075469 (-0.003082) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.595587 / 1.841788 (-0.246201) | 23.035478 / 8.074308 (14.961170) | 16.457675 / 10.191392 (6.266283) | 0.170819 / 0.680424 (-0.509605) | 0.022042 / 0.534201 (-0.512159) | 0.466824 / 0.579283 (-0.112459) | 0.486350 / 0.434364 (0.051986) | 0.574330 / 0.540337 (0.033993) | 0.764913 / 1.386936 (-0.622023) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#664a1cb72ea1e6ef7c47e671e2686ca4a35e8d63 \"CML watermark\")\n" ]

"2023-08-04T03:13:30Z"

"2023-08-16T10:13:02Z"

"2023-08-16T10:02:52Z"

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[ "Hi! `IterableDataset.from_generator` expects a generator function, not the object (to be consistent with `Dataset.from_generator`).\r\n\r\nYou can fix the above snippet as follows:\r\n```python\r\ntrain_dataset = IterableDataset.from_generator(line_generator, fn_kwargs={\"files\": model_training_files})\r\n```" ]

"2023-08-04T01:45:04Z"

"2023-08-17T17:58:27Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6117). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.012516 / 0.011353 (0.001163) | 0.004725 / 0.011008 (-0.006283) | 0.112245 / 0.038508 (0.073736) | 0.079146 / 0.023109 (0.056037) | 0.386415 / 0.275898 (0.110517) | 0.420441 / 0.323480 (0.096961) | 0.005682 / 0.007986 (-0.002304) | 0.004169 / 0.004328 (-0.000160) | 0.077847 / 0.004250 (0.073597) | 0.055763 / 0.037052 (0.018711) | 0.385529 / 0.258489 (0.127040) | 0.422711 / 0.293841 (0.128870) | 0.047212 / 0.128546 (-0.081334) | 0.013711 / 0.075646 (-0.061935) | 0.342856 / 0.419271 (-0.076416) | 0.066788 / 0.043533 (0.023255) | 0.380728 / 0.255139 (0.125589) | 0.416241 / 0.283200 (0.133041) | 0.034676 / 0.141683 (-0.107007) | 1.679661 / 1.452155 (0.227506) | 1.838014 / 1.492716 (0.345297) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.219556 / 0.018006 (0.201550) | 0.524728 / 0.000490 (0.524238) | 0.005045 / 0.000200 (0.004845) | 0.000124 / 0.000054 (0.000069) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025475 / 0.037411 (-0.011936) | 0.085937 / 0.014526 (0.071412) | 0.099245 / 0.176557 (-0.077311) | 0.158995 / 0.737135 (-0.578141) | 0.101504 / 0.296338 (-0.194835) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.582200 / 0.215209 (0.366991) | 5.794340 / 2.077655 (3.716685) | 2.473635 / 1.504120 (0.969515) | 2.168135 / 1.541195 (0.626941) | 2.215886 / 1.468490 (0.747396) | 0.855599 / 4.584777 (-3.729178) | 5.003067 / 3.745712 (1.257354) | 4.503566 / 5.269862 (-0.766295) | 2.912248 / 4.565676 (-1.653428) | 0.103267 / 0.424275 (-0.321008) | 0.012114 / 0.007607 (0.004507) | 0.712240 / 0.226044 (0.486196) | 7.131946 / 2.268929 (4.863017) | 3.280052 / 55.444624 (-52.164573) | 2.583472 / 6.876477 (-4.293004) | 2.820758 / 2.142072 (0.678686) | 1.132097 / 4.805227 (-3.673131) | 0.232191 / 6.500664 (-6.268473) | 0.082966 / 0.075469 (0.007497) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.581125 / 1.841788 (-0.260662) | 22.723878 / 8.074308 (14.649570) | 19.969347 / 10.191392 (9.777955) | 0.234365 / 0.680424 (-0.446059) | 0.030245 / 0.534201 (-0.503956) | 0.470843 / 0.579283 (-0.108440) | 0.558069 / 0.434364 (0.123705) | 0.534878 / 0.540337 (-0.005460) | 0.801025 / 1.386936 (-0.585911) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008524 / 0.011353 (-0.002829) | 0.005083 / 0.011008 (-0.005925) | 0.078054 / 0.038508 (0.039546) | 0.082025 / 0.023109 (0.058915) | 0.458027 / 0.275898 (0.182129) | 0.498232 / 0.323480 (0.174752) | 0.005938 / 0.007986 (-0.002048) | 0.003776 / 0.004328 (-0.000553) | 0.080413 / 0.004250 (0.076163) | 0.060485 / 0.037052 (0.023433) | 0.462816 / 0.258489 (0.204327) | 0.513970 / 0.293841 (0.220129) | 0.047574 / 0.128546 (-0.080973) | 0.013424 / 0.075646 (-0.062222) | 0.087707 / 0.419271 (-0.331565) | 0.065007 / 0.043533 (0.021474) | 0.465844 / 0.255139 (0.210705) | 0.498474 / 0.283200 (0.215274) | 0.033518 / 0.141683 (-0.108164) | 1.737507 / 1.452155 (0.285352) | 1.848291 / 1.492716 (0.355574) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.316710 / 0.018006 (0.298703) | 0.504415 / 0.000490 (0.503925) | 0.042128 / 0.000200 (0.041928) | 0.000171 / 0.000054 (0.000117) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032097 / 0.037411 (-0.005314) | 0.099371 / 0.014526 (0.084845) | 0.109311 / 0.176557 (-0.067246) | 0.177373 / 0.737135 (-0.559762) | 0.110753 / 0.296338 (-0.185585) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.688060 / 0.215209 (0.472851) | 6.255219 / 2.077655 (4.177564) | 2.696845 / 1.504120 (1.192725) | 2.395424 / 1.541195 (0.854230) | 2.414870 / 1.468490 (0.946380) | 0.865704 / 4.584777 (-3.719073) | 5.086828 / 3.745712 (1.341116) | 4.648107 / 5.269862 (-0.621754) | 3.091119 / 4.565676 (-1.474558) | 0.101787 / 0.424275 (-0.322489) | 0.008829 / 0.007607 (0.001222) | 0.772398 / 0.226044 (0.546354) | 7.700366 / 2.268929 (5.431438) | 3.608632 / 55.444624 (-51.835992) | 2.923309 / 6.876477 (-3.953168) | 2.952141 / 2.142072 (0.810069) | 1.093006 / 4.805227 (-3.712221) | 0.224363 / 6.500664 (-6.276301) | 0.074927 / 0.075469 (-0.000542) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.638414 / 1.841788 (-0.203374) | 23.486781 / 8.074308 (15.412473) | 21.129104 / 10.191392 (10.937712) | 0.259955 / 0.680424 (-0.420469) | 0.027305 / 0.534201 (-0.506895) | 0.464448 / 0.579283 (-0.114835) | 0.553737 / 0.434364 (0.119373) | 0.571318 / 0.540337 (0.030981) | 0.772917 / 1.386936 (-0.614019) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3ec5ee9e78b464364796651d995823c7ecb0f951 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009093 / 0.011353 (-0.002260) | 0.005283 / 0.011008 (-0.005725) | 0.112299 / 0.038508 (0.073791) | 0.081341 / 0.023109 (0.058232) | 0.363799 / 0.275898 (0.087901) | 0.409261 / 0.323480 (0.085781) | 0.006400 / 0.007986 (-0.001586) | 0.003965 / 0.004328 (-0.000363) | 0.074389 / 0.004250 (0.070139) | 0.060654 / 0.037052 (0.023602) | 0.391046 / 0.258489 (0.132557) | 0.430514 / 0.293841 (0.136673) | 0.054900 / 0.128546 (-0.073646) | 0.017972 / 0.075646 (-0.057675) | 0.410875 / 0.419271 (-0.008396) | 0.067405 / 0.043533 (0.023873) | 0.371468 / 0.255139 (0.116329) | 0.435061 / 0.283200 (0.151861) | 0.038063 / 0.141683 (-0.103620) | 1.733509 / 1.452155 (0.281354) | 1.833899 / 1.492716 (0.341182) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243230 / 0.018006 (0.225224) | 0.605636 / 0.000490 (0.605146) | 0.004890 / 0.000200 (0.004690) | 0.000098 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027624 / 0.037411 (-0.009787) | 0.084799 / 0.014526 (0.070273) | 0.104405 / 0.176557 (-0.072152) | 0.165383 / 0.737135 (-0.571752) | 0.102083 / 0.296338 (-0.194255) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.578334 / 0.215209 (0.363125) | 5.369520 / 2.077655 (3.291866) | 2.294174 / 1.504120 (0.790055) | 2.054195 / 1.541195 (0.513000) | 2.007304 / 1.468490 (0.538814) | 0.839283 / 4.584777 (-3.745494) | 5.262288 / 3.745712 (1.516576) | 4.363346 / 5.269862 (-0.906516) | 2.854903 / 4.565676 (-1.710773) | 0.096975 / 0.424275 (-0.327300) | 0.008237 / 0.007607 (0.000630) | 0.646746 / 0.226044 (0.420702) | 6.250621 / 2.268929 (3.981693) | 2.900377 / 55.444624 (-52.544247) | 2.283238 / 6.876477 (-4.593239) | 2.443785 / 2.142072 (0.301713) | 0.991719 / 4.805227 (-3.813508) | 0.189755 / 6.500664 (-6.310909) | 0.067906 / 0.075469 (-0.007563) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.515563 / 1.841788 (-0.326225) | 21.956499 / 8.074308 (13.882191) | 19.161750 / 10.191392 (8.970358) | 0.238199 / 0.680424 (-0.442225) | 0.026771 / 0.534201 (-0.507430) | 0.450195 / 0.579283 (-0.129088) | 0.585168 / 0.434364 (0.150804) | 0.522945 / 0.540337 (-0.017393) | 0.776244 / 1.386936 (-0.610693) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007997 / 0.011353 (-0.003356) | 0.005021 / 0.011008 (-0.005988) | 0.087308 / 0.038508 (0.048800) | 0.077760 / 0.023109 (0.054650) | 0.425313 / 0.275898 (0.149415) | 0.451470 / 0.323480 (0.127990) | 0.006848 / 0.007986 (-0.001137) | 0.004812 / 0.004328 (0.000484) | 0.071198 / 0.004250 (0.066947) | 0.058325 / 0.037052 (0.021273) | 0.427411 / 0.258489 (0.168922) | 0.466069 / 0.293841 (0.172228) | 0.048686 / 0.128546 (-0.079861) | 0.011841 / 0.075646 (-0.063806) | 0.086225 / 0.419271 (-0.333047) | 0.060500 / 0.043533 (0.016967) | 0.435580 / 0.255139 (0.180441) | 0.456919 / 0.283200 (0.173719) | 0.035094 / 0.141683 (-0.106588) | 1.582805 / 1.452155 (0.130650) | 1.717838 / 1.492716 (0.225122) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.283967 / 0.018006 (0.265960) | 0.517496 / 0.000490 (0.517006) | 0.014747 / 0.000200 (0.014547) | 0.000099 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027870 / 0.037411 (-0.009541) | 0.083835 / 0.014526 (0.069309) | 0.099157 / 0.176557 (-0.077400) | 0.173210 / 0.737135 (-0.563925) | 0.094212 / 0.296338 (-0.202127) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.535720 / 0.215209 (0.320511) | 5.273730 / 2.077655 (3.196075) | 2.422560 / 1.504120 (0.918440) | 2.131416 / 1.541195 (0.590222) | 2.192000 / 1.468490 (0.723510) | 0.708469 / 4.584777 (-3.876308) | 4.758092 / 3.745712 (1.012380) | 3.940729 / 5.269862 (-1.329133) | 2.553093 / 4.565676 (-2.012583) | 0.084895 / 0.424275 (-0.339380) | 0.008730 / 0.007607 (0.001123) | 0.646975 / 0.226044 (0.420930) | 6.294811 / 2.268929 (4.025883) | 3.293964 / 55.444624 (-52.150660) | 2.568985 / 6.876477 (-4.307492) | 2.743786 / 2.142072 (0.601713) | 0.899733 / 4.805227 (-3.905494) | 0.193484 / 6.500664 (-6.307181) | 0.070012 / 0.075469 (-0.005457) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.502255 / 1.841788 (-0.339532) | 20.690234 / 8.074308 (12.615926) | 18.375791 / 10.191392 (8.184399) | 0.200135 / 0.680424 (-0.480289) | 0.029434 / 0.534201 (-0.504767) | 0.477267 / 0.579283 (-0.102016) | 0.566869 / 0.434364 (0.132505) | 0.543756 / 0.540337 (0.003418) | 0.700476 / 1.386936 (-0.686460) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ef17d9fd6c648bb41d43ba301c3de4d7b6f833d8 \"CML watermark\")\n" ]

"2023-08-03T14:46:04Z"

"2023-08-03T14:56:59Z"

"2023-08-03T14:46:18Z"

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[]

[ "Great idea, feel free to open a PR! :)" ]

"2023-08-03T13:45:10Z"

"2023-08-16T10:02:53Z"

"2023-08-16T10:02:53Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007578 / 0.011353 (-0.003775) | 0.004271 / 0.011008 (-0.006738) | 0.086607 / 0.038508 (0.048098) | 0.063209 / 0.023109 (0.040099) | 0.351724 / 0.275898 (0.075826) | 0.399261 / 0.323480 (0.075781) | 0.004767 / 0.007986 (-0.003219) | 0.003487 / 0.004328 (-0.000842) | 0.071483 / 0.004250 (0.067233) | 0.051281 / 0.037052 (0.014229) | 0.387726 / 0.258489 (0.129237) | 0.408446 / 0.293841 (0.114605) | 0.041189 / 0.128546 (-0.087357) | 0.012446 / 0.075646 (-0.063200) | 0.331147 / 0.419271 (-0.088124) | 0.056721 / 0.043533 (0.013188) | 0.361306 / 0.255139 (0.106167) | 0.409651 / 0.283200 (0.126451) | 0.035485 / 0.141683 (-0.106198) | 1.461391 / 1.452155 (0.009236) | 1.554820 / 1.492716 (0.062104) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237119 / 0.018006 (0.219113) | 0.518731 / 0.000490 (0.518241) | 0.004192 / 0.000200 (0.003992) | 0.000114 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024912 / 0.037411 (-0.012499) | 0.089420 / 0.014526 (0.074894) | 0.091209 / 0.176557 (-0.085347) | 0.152580 / 0.737135 (-0.584555) | 0.089660 / 0.296338 (-0.206678) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.515223 / 0.215209 (0.300014) | 5.328359 / 2.077655 (3.250705) | 1.974326 / 1.504120 (0.470206) | 1.665216 / 1.541195 (0.124021) | 1.736040 / 1.468490 (0.267550) | 0.734746 / 4.584777 (-3.850031) | 4.186613 / 3.745712 (0.440901) | 3.535760 / 5.269862 (-1.734102) | 2.333247 / 4.565676 (-2.232429) | 0.071845 / 0.424275 (-0.352430) | 0.006147 / 0.007607 (-0.001460) | 0.546649 / 0.226044 (0.320605) | 5.452281 / 2.268929 (3.183353) | 2.512984 / 55.444624 (-52.931640) | 2.104210 / 6.876477 (-4.772267) | 2.409251 / 2.142072 (0.267178) | 0.822797 / 4.805227 (-3.982430) | 0.166648 / 6.500664 (-6.334016) | 0.056350 / 0.075469 (-0.019119) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.397798 / 1.841788 (-0.443989) | 20.549399 / 8.074308 (12.475091) | 19.118168 / 10.191392 (8.926776) | 0.216361 / 0.680424 (-0.464063) | 0.027064 / 0.534201 (-0.507136) | 0.410762 / 0.579283 (-0.168521) | 0.559225 / 0.434364 (0.124861) | 0.468028 / 0.540337 (-0.072309) | 0.691520 / 1.386936 (-0.695416) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006463 / 0.011353 (-0.004890) | 0.003879 / 0.011008 (-0.007130) | 0.058723 / 0.038508 (0.020215) | 0.057202 / 0.023109 (0.034092) | 0.344397 / 0.275898 (0.068499) | 0.360388 / 0.323480 (0.036908) | 0.005502 / 0.007986 (-0.002483) | 0.004101 / 0.004328 (-0.000227) | 0.058168 / 0.004250 (0.053917) | 0.059112 / 0.037052 (0.022060) | 0.362206 / 0.258489 (0.103717) | 0.386444 / 0.293841 (0.092603) | 0.036613 / 0.128546 (-0.091934) | 0.010482 / 0.075646 (-0.065165) | 0.065850 / 0.419271 (-0.353421) | 0.046528 / 0.043533 (0.002995) | 0.349568 / 0.255139 (0.094429) | 0.360181 / 0.283200 (0.076981) | 0.029030 / 0.141683 (-0.112653) | 1.314569 / 1.452155 (-0.137586) | 1.422393 / 1.492716 (-0.070324) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.281554 / 0.018006 (0.263548) | 0.608018 / 0.000490 (0.607528) | 0.004568 / 0.000200 (0.004368) | 0.000182 / 0.000054 (0.000127) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023515 / 0.037411 (-0.013896) | 0.072994 / 0.014526 (0.058468) | 0.080688 / 0.176557 (-0.095868) | 0.125904 / 0.737135 (-0.611232) | 0.085457 / 0.296338 (-0.210882) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.471530 / 0.215209 (0.256321) | 4.796197 / 2.077655 (2.718542) | 2.189181 / 1.504120 (0.685061) | 1.886649 / 1.541195 (0.345454) | 1.871067 / 1.468490 (0.402577) | 0.661043 / 4.584777 (-3.923734) | 4.344027 / 3.745712 (0.598315) | 3.656967 / 5.269862 (-1.612895) | 2.286033 / 4.565676 (-2.279644) | 0.079146 / 0.424275 (-0.345129) | 0.006840 / 0.007607 (-0.000767) | 0.588750 / 0.226044 (0.362706) | 6.301286 / 2.268929 (4.032357) | 3.074702 / 55.444624 (-52.369923) | 2.398739 / 6.876477 (-4.477738) | 2.555057 / 2.142072 (0.412985) | 0.874189 / 4.805227 (-3.931038) | 0.191423 / 6.500664 (-6.309241) | 0.061227 / 0.075469 (-0.014242) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.472763 / 1.841788 (-0.369024) | 19.441304 / 8.074308 (11.366996) | 15.974276 / 10.191392 (5.782884) | 0.172503 / 0.680424 (-0.507921) | 0.027016 / 0.534201 (-0.507185) | 0.356085 / 0.579283 (-0.223198) | 0.473251 / 0.434364 (0.038887) | 0.427949 / 0.540337 (-0.112388) | 0.588924 / 1.386936 (-0.798013) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0973da6e60ac7c1d24229ba6aa6881747b21858a \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006166 / 0.011353 (-0.005187) | 0.003558 / 0.011008 (-0.007450) | 0.080576 / 0.038508 (0.042068) | 0.066542 / 0.023109 (0.043432) | 0.323997 / 0.275898 (0.048099) | 0.369828 / 0.323480 (0.046348) | 0.004896 / 0.007986 (-0.003090) | 0.002909 / 0.004328 (-0.001419) | 0.062553 / 0.004250 (0.058302) | 0.049795 / 0.037052 (0.012742) | 0.321369 / 0.258489 (0.062880) | 0.422860 / 0.293841 (0.129019) | 0.027394 / 0.128546 (-0.101152) | 0.007954 / 0.075646 (-0.067693) | 0.264122 / 0.419271 (-0.155149) | 0.044881 / 0.043533 (0.001349) | 0.316702 / 0.255139 (0.061563) | 0.374718 / 0.283200 (0.091518) | 0.021728 / 0.141683 (-0.119955) | 1.394456 / 1.452155 (-0.057699) | 1.474936 / 1.492716 (-0.017780) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.191902 / 0.018006 (0.173896) | 0.430468 / 0.000490 (0.429979) | 0.003790 / 0.000200 (0.003590) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024974 / 0.037411 (-0.012438) | 0.073053 / 0.014526 (0.058527) | 0.083801 / 0.176557 (-0.092756) | 0.143457 / 0.737135 (-0.593678) | 0.085099 / 0.296338 (-0.211240) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.428411 / 0.215209 (0.213202) | 4.278077 / 2.077655 (2.200422) | 2.230039 / 1.504120 (0.725919) | 2.057191 / 1.541195 (0.515996) | 2.120109 / 1.468490 (0.651619) | 0.495242 / 4.584777 (-4.089535) | 3.031299 / 3.745712 (-0.714413) | 2.802685 / 5.269862 (-2.467176) | 1.839828 / 4.565676 (-2.725849) | 0.056875 / 0.424275 (-0.367401) | 0.006446 / 0.007607 (-0.001161) | 0.498958 / 0.226044 (0.272913) | 4.980440 / 2.268929 (2.711511) | 2.659659 / 55.444624 (-52.784965) | 2.315174 / 6.876477 (-4.561303) | 2.475920 / 2.142072 (0.333848) | 0.586946 / 4.805227 (-4.218282) | 0.124291 / 6.500664 (-6.376373) | 0.060701 / 0.075469 (-0.014768) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.245062 / 1.841788 (-0.596725) | 18.201444 / 8.074308 (10.127136) | 13.723271 / 10.191392 (3.531879) | 0.130203 / 0.680424 (-0.550221) | 0.016773 / 0.534201 (-0.517428) | 0.332909 / 0.579283 (-0.246374) | 0.347469 / 0.434364 (-0.086895) | 0.381364 / 0.540337 (-0.158973) | 0.541723 / 1.386936 (-0.845213) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005934 / 0.011353 (-0.005419) | 0.003573 / 0.011008 (-0.007435) | 0.062195 / 0.038508 (0.023687) | 0.059026 / 0.023109 (0.035917) | 0.413993 / 0.275898 (0.138095) | 0.459552 / 0.323480 (0.136072) | 0.004610 / 0.007986 (-0.003376) | 0.002907 / 0.004328 (-0.001421) | 0.062983 / 0.004250 (0.058733) | 0.047797 / 0.037052 (0.010745) | 0.415461 / 0.258489 (0.156972) | 0.417424 / 0.293841 (0.123583) | 0.027098 / 0.128546 (-0.101449) | 0.008106 / 0.075646 (-0.067540) | 0.067600 / 0.419271 (-0.351672) | 0.041432 / 0.043533 (-0.002101) | 0.407861 / 0.255139 (0.152722) | 0.430774 / 0.283200 (0.147575) | 0.020738 / 0.141683 (-0.120945) | 1.435127 / 1.452155 (-0.017028) | 1.486961 / 1.492716 (-0.005755) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231174 / 0.018006 (0.213168) | 0.421208 / 0.000490 (0.420718) | 0.005411 / 0.000200 (0.005211) | 0.000078 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025362 / 0.037411 (-0.012049) | 0.078534 / 0.014526 (0.064008) | 0.085304 / 0.176557 (-0.091252) | 0.139048 / 0.737135 (-0.598087) | 0.087015 / 0.296338 (-0.209323) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.448506 / 0.215209 (0.233297) | 4.486694 / 2.077655 (2.409039) | 2.488022 / 1.504120 (0.983902) | 2.325321 / 1.541195 (0.784126) | 2.381311 / 1.468490 (0.912821) | 0.502102 / 4.584777 (-4.082675) | 3.018326 / 3.745712 (-0.727386) | 2.824922 / 5.269862 (-2.444940) | 1.857414 / 4.565676 (-2.708263) | 0.057514 / 0.424275 (-0.366761) | 0.006829 / 0.007607 (-0.000779) | 0.521939 / 0.226044 (0.295895) | 5.224393 / 2.268929 (2.955465) | 2.933132 / 55.444624 (-52.511492) | 2.661187 / 6.876477 (-4.215290) | 2.781950 / 2.142072 (0.639878) | 0.592927 / 4.805227 (-4.212300) | 0.126685 / 6.500664 (-6.373979) | 0.064188 / 0.075469 (-0.011281) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.351107 / 1.841788 (-0.490681) | 18.344453 / 8.074308 (10.270145) | 13.838788 / 10.191392 (3.647396) | 0.157881 / 0.680424 (-0.522543) | 0.016636 / 0.534201 (-0.517565) | 0.331597 / 0.579283 (-0.247686) | 0.345573 / 0.434364 (-0.088791) | 0.397361 / 0.540337 (-0.142976) | 0.534289 / 1.386936 (-0.852647) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#582e722a76534904c0f3038d32ebb8db88ce9128 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006399 / 0.011353 (-0.004954) | 0.003872 / 0.011008 (-0.007136) | 0.083722 / 0.038508 (0.045214) | 0.068845 / 0.023109 (0.045736) | 0.329112 / 0.275898 (0.053214) | 0.343295 / 0.323480 (0.019815) | 0.005137 / 0.007986 (-0.002849) | 0.003303 / 0.004328 (-0.001026) | 0.064495 / 0.004250 (0.060245) | 0.051448 / 0.037052 (0.014395) | 0.322554 / 0.258489 (0.064065) | 0.361934 / 0.293841 (0.068093) | 0.030821 / 0.128546 (-0.097726) | 0.008482 / 0.075646 (-0.067164) | 0.288136 / 0.419271 (-0.131135) | 0.051935 / 0.043533 (0.008402) | 0.308283 / 0.255139 (0.053144) | 0.343421 / 0.283200 (0.060221) | 0.023639 / 0.141683 (-0.118044) | 1.485442 / 1.452155 (0.033288) | 1.533282 / 1.492716 (0.040565) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218163 / 0.018006 (0.200157) | 0.464473 / 0.000490 (0.463983) | 0.003097 / 0.000200 (0.002897) | 0.000081 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028650 / 0.037411 (-0.008761) | 0.083295 / 0.014526 (0.068769) | 0.096468 / 0.176557 (-0.080088) | 0.152086 / 0.737135 (-0.585050) | 0.102586 / 0.296338 (-0.193752) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.393038 / 0.215209 (0.177829) | 3.925514 / 2.077655 (1.847859) | 1.938419 / 1.504120 (0.434300) | 1.760265 / 1.541195 (0.219071) | 1.810024 / 1.468490 (0.341534) | 0.486232 / 4.584777 (-4.098545) | 3.618747 / 3.745712 (-0.126965) | 3.206950 / 5.269862 (-2.062912) | 1.999240 / 4.565676 (-2.566436) | 0.056986 / 0.424275 (-0.367289) | 0.007193 / 0.007607 (-0.000415) | 0.469313 / 0.226044 (0.243269) | 4.688670 / 2.268929 (2.419741) | 2.400332 / 55.444624 (-53.044292) | 2.074197 / 6.876477 (-4.802279) | 2.290823 / 2.142072 (0.148751) | 0.582339 / 4.805227 (-4.222888) | 0.134127 / 6.500664 (-6.366537) | 0.061061 / 0.075469 (-0.014408) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.272782 / 1.841788 (-0.569006) | 19.463375 / 8.074308 (11.389067) | 14.306819 / 10.191392 (4.115427) | 0.164608 / 0.680424 (-0.515816) | 0.018626 / 0.534201 (-0.515575) | 0.395225 / 0.579283 (-0.184058) | 0.408984 / 0.434364 (-0.025380) | 0.463364 / 0.540337 (-0.076974) | 0.630425 / 1.386936 (-0.756511) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006465 / 0.011353 (-0.004888) | 0.003975 / 0.011008 (-0.007033) | 0.063643 / 0.038508 (0.025134) | 0.075214 / 0.023109 (0.052105) | 0.361734 / 0.275898 (0.085836) | 0.396664 / 0.323480 (0.073184) | 0.005251 / 0.007986 (-0.002735) | 0.003249 / 0.004328 (-0.001080) | 0.063841 / 0.004250 (0.059591) | 0.054504 / 0.037052 (0.017451) | 0.374791 / 0.258489 (0.116302) | 0.399205 / 0.293841 (0.105364) | 0.031355 / 0.128546 (-0.097192) | 0.008483 / 0.075646 (-0.067163) | 0.070234 / 0.419271 (-0.349037) | 0.048336 / 0.043533 (0.004803) | 0.373484 / 0.255139 (0.118345) | 0.382174 / 0.283200 (0.098974) | 0.022560 / 0.141683 (-0.119123) | 1.449799 / 1.452155 (-0.002355) | 1.525255 / 1.492716 (0.032539) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228350 / 0.018006 (0.210343) | 0.444344 / 0.000490 (0.443855) | 0.003699 / 0.000200 (0.003499) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030681 / 0.037411 (-0.006731) | 0.087340 / 0.014526 (0.072814) | 0.098636 / 0.176557 (-0.077920) | 0.151665 / 0.737135 (-0.585471) | 0.100840 / 0.296338 (-0.195498) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.417857 / 0.215209 (0.202648) | 4.168407 / 2.077655 (2.090752) | 2.201758 / 1.504120 (0.697638) | 1.997834 / 1.541195 (0.456639) | 2.127693 / 1.468490 (0.659202) | 0.486429 / 4.584777 (-4.098348) | 3.676335 / 3.745712 (-0.069378) | 3.226268 / 5.269862 (-2.043594) | 2.027255 / 4.565676 (-2.538422) | 0.056759 / 0.424275 (-0.367516) | 0.007628 / 0.007607 (0.000021) | 0.500482 / 0.226044 (0.274438) | 4.996236 / 2.268929 (2.727307) | 2.628884 / 55.444624 (-52.815740) | 2.347611 / 6.876477 (-4.528866) | 2.551328 / 2.142072 (0.409255) | 0.582449 / 4.805227 (-4.222778) | 0.132844 / 6.500664 (-6.367821) | 0.061791 / 0.075469 (-0.013678) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.373718 / 1.841788 (-0.468070) | 19.921217 / 8.074308 (11.846909) | 14.209642 / 10.191392 (4.018250) | 0.185334 / 0.680424 (-0.495090) | 0.018228 / 0.534201 (-0.515973) | 0.395549 / 0.579283 (-0.183734) | 0.404446 / 0.434364 (-0.029918) | 0.472456 / 0.540337 (-0.067882) | 0.622739 / 1.386936 (-0.764197) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#33f736eafa0f77de03aa6894ea4a6c923702e5d1 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006007 / 0.011353 (-0.005346) | 0.003588 / 0.011008 (-0.007420) | 0.080334 / 0.038508 (0.041826) | 0.058932 / 0.023109 (0.035823) | 0.404613 / 0.275898 (0.128715) | 0.438377 / 0.323480 (0.114897) | 0.003468 / 0.007986 (-0.004518) | 0.003702 / 0.004328 (-0.000627) | 0.062936 / 0.004250 (0.058686) | 0.047987 / 0.037052 (0.010934) | 0.411409 / 0.258489 (0.152920) | 0.450244 / 0.293841 (0.156403) | 0.027007 / 0.128546 (-0.101539) | 0.007932 / 0.075646 (-0.067714) | 0.261390 / 0.419271 (-0.157882) | 0.044992 / 0.043533 (0.001459) | 0.409730 / 0.255139 (0.154591) | 0.433331 / 0.283200 (0.150131) | 0.020446 / 0.141683 (-0.121237) | 1.425418 / 1.452155 (-0.026736) | 1.479242 / 1.492716 (-0.013475) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.187375 / 0.018006 (0.169368) | 0.428532 / 0.000490 (0.428043) | 0.003406 / 0.000200 (0.003206) | 0.000072 / 0.000054 (0.000018) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024390 / 0.037411 (-0.013022) | 0.072571 / 0.014526 (0.058045) | 0.083513 / 0.176557 (-0.093044) | 0.144395 / 0.737135 (-0.592741) | 0.084813 / 0.296338 (-0.211526) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.409176 / 0.215209 (0.193967) | 4.078082 / 2.077655 (2.000428) | 1.913596 / 1.504120 (0.409476) | 1.718470 / 1.541195 (0.177275) | 1.753106 / 1.468490 (0.284616) | 0.494167 / 4.584777 (-4.090610) | 3.029531 / 3.745712 (-0.716181) | 2.807331 / 5.269862 (-2.462531) | 1.839471 / 4.565676 (-2.726206) | 0.057169 / 0.424275 (-0.367106) | 0.006433 / 0.007607 (-0.001175) | 0.482666 / 0.226044 (0.256621) | 4.817601 / 2.268929 (2.548673) | 2.449967 / 55.444624 (-52.994658) | 2.113891 / 6.876477 (-4.762586) | 2.399293 / 2.142072 (0.257221) | 0.578903 / 4.805227 (-4.226324) | 0.124306 / 6.500664 (-6.376358) | 0.061572 / 0.075469 (-0.013897) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.254692 / 1.841788 (-0.587096) | 18.414049 / 8.074308 (10.339741) | 13.992059 / 10.191392 (3.800667) | 0.146671 / 0.680424 (-0.533753) | 0.016925 / 0.534201 (-0.517275) | 0.333124 / 0.579283 (-0.246159) | 0.348007 / 0.434364 (-0.086357) | 0.378519 / 0.540337 (-0.161819) | 0.532540 / 1.386936 (-0.854396) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006050 / 0.011353 (-0.005303) | 0.003614 / 0.011008 (-0.007394) | 0.061707 / 0.038508 (0.023199) | 0.062874 / 0.023109 (0.039765) | 0.364760 / 0.275898 (0.088862) | 0.398136 / 0.323480 (0.074656) | 0.005598 / 0.007986 (-0.002388) | 0.002836 / 0.004328 (-0.001493) | 0.061880 / 0.004250 (0.057630) | 0.048165 / 0.037052 (0.011113) | 0.372656 / 0.258489 (0.114167) | 0.403967 / 0.293841 (0.110126) | 0.027046 / 0.128546 (-0.101501) | 0.008091 / 0.075646 (-0.067555) | 0.066783 / 0.419271 (-0.352489) | 0.041186 / 0.043533 (-0.002347) | 0.376009 / 0.255139 (0.120870) | 0.391769 / 0.283200 (0.108569) | 0.021020 / 0.141683 (-0.120663) | 1.514593 / 1.452155 (0.062438) | 1.548506 / 1.492716 (0.055790) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237610 / 0.018006 (0.219604) | 0.434274 / 0.000490 (0.433784) | 0.009720 / 0.000200 (0.009520) | 0.000098 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025605 / 0.037411 (-0.011807) | 0.078971 / 0.014526 (0.064445) | 0.088154 / 0.176557 (-0.088403) | 0.139112 / 0.737135 (-0.598023) | 0.088890 / 0.296338 (-0.207449) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420027 / 0.215209 (0.204818) | 4.189493 / 2.077655 (2.111838) | 2.143907 / 1.504120 (0.639787) | 1.967032 / 1.541195 (0.425837) | 2.011845 / 1.468490 (0.543355) | 0.496692 / 4.584777 (-4.088085) | 3.025456 / 3.745712 (-0.720256) | 2.828436 / 5.269862 (-2.441426) | 1.860673 / 4.565676 (-2.705003) | 0.057199 / 0.424275 (-0.367076) | 0.006770 / 0.007607 (-0.000838) | 0.491281 / 0.226044 (0.265236) | 4.918065 / 2.268929 (2.649136) | 2.593172 / 55.444624 (-52.851452) | 2.250750 / 6.876477 (-4.625727) | 2.406235 / 2.142072 (0.264162) | 0.588648 / 4.805227 (-4.216579) | 0.125635 / 6.500664 (-6.375029) | 0.061697 / 0.075469 (-0.013773) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.374065 / 1.841788 (-0.467722) | 18.439315 / 8.074308 (10.365007) | 14.031660 / 10.191392 (3.840268) | 0.153665 / 0.680424 (-0.526759) | 0.016980 / 0.534201 (-0.517221) | 0.331799 / 0.579283 (-0.247484) | 0.343201 / 0.434364 (-0.091163) | 0.392445 / 0.540337 (-0.147892) | 0.530387 / 1.386936 (-0.856549) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#33f736eafa0f77de03aa6894ea4a6c923702e5d1 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008189 / 0.011353 (-0.003164) | 0.004598 / 0.011008 (-0.006410) | 0.102199 / 0.038508 (0.063691) | 0.077961 / 0.023109 (0.054852) | 0.364936 / 0.275898 (0.089038) | 0.402606 / 0.323480 (0.079126) | 0.005522 / 0.007986 (-0.002464) | 0.004007 / 0.004328 (-0.000322) | 0.071560 / 0.004250 (0.067310) | 0.055818 / 0.037052 (0.018765) | 0.378394 / 0.258489 (0.119905) | 0.428990 / 0.293841 (0.135149) | 0.043142 / 0.128546 (-0.085404) | 0.013254 / 0.075646 (-0.062392) | 0.331102 / 0.419271 (-0.088170) | 0.061407 / 0.043533 (0.017875) | 0.387397 / 0.255139 (0.132258) | 0.416062 / 0.283200 (0.132862) | 0.036330 / 0.141683 (-0.105353) | 1.735352 / 1.452155 (0.283198) | 1.773329 / 1.492716 (0.280613) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.188587 / 0.018006 (0.170581) | 0.519506 / 0.000490 (0.519016) | 0.004702 / 0.000200 (0.004502) | 0.000097 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027152 / 0.037411 (-0.010260) | 0.094296 / 0.014526 (0.079770) | 0.098155 / 0.176557 (-0.078402) | 0.162541 / 0.737135 (-0.574595) | 0.112092 / 0.296338 (-0.184246) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.537555 / 0.215209 (0.322346) | 5.486821 / 2.077655 (3.409166) | 2.377127 / 1.504120 (0.873008) | 2.073205 / 1.541195 (0.532011) | 2.075130 / 1.468490 (0.606640) | 0.783779 / 4.584777 (-3.800998) | 5.029524 / 3.745712 (1.283812) | 4.382724 / 5.269862 (-0.887138) | 2.836180 / 4.565676 (-1.729496) | 0.108840 / 0.424275 (-0.315435) | 0.008123 / 0.007607 (0.000516) | 0.673460 / 0.226044 (0.447416) | 6.674030 / 2.268929 (4.405102) | 3.208922 / 55.444624 (-52.235702) | 2.464908 / 6.876477 (-4.411568) | 2.661929 / 2.142072 (0.519856) | 0.962529 / 4.805227 (-3.842698) | 0.197974 / 6.500664 (-6.302690) | 0.066656 / 0.075469 (-0.008813) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.430373 / 1.841788 (-0.411415) | 21.180540 / 8.074308 (13.106232) | 19.027491 / 10.191392 (8.836099) | 0.217520 / 0.680424 (-0.462904) | 0.028038 / 0.534201 (-0.506163) | 0.435266 / 0.579283 (-0.144017) | 0.529510 / 0.434364 (0.095147) | 0.511011 / 0.540337 (-0.029327) | 0.728940 / 1.386936 (-0.657996) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007883 / 0.011353 (-0.003470) | 0.004448 / 0.011008 (-0.006560) | 0.071350 / 0.038508 (0.032842) | 0.075269 / 0.023109 (0.052160) | 0.396705 / 0.275898 (0.120807) | 0.457809 / 0.323480 (0.134329) | 0.005193 / 0.007986 (-0.002792) | 0.003695 / 0.004328 (-0.000633) | 0.078087 / 0.004250 (0.073836) | 0.054276 / 0.037052 (0.017224) | 0.412184 / 0.258489 (0.153695) | 0.452400 / 0.293841 (0.158559) | 0.049762 / 0.128546 (-0.078784) | 0.013206 / 0.075646 (-0.062440) | 0.085985 / 0.419271 (-0.333287) | 0.058837 / 0.043533 (0.015304) | 0.432481 / 0.255139 (0.177342) | 0.433260 / 0.283200 (0.150060) | 0.031190 / 0.141683 (-0.110493) | 1.582707 / 1.452155 (0.130552) | 1.664457 / 1.492716 (0.171741) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223639 / 0.018006 (0.205633) | 0.524388 / 0.000490 (0.523899) | 0.005489 / 0.000200 (0.005289) | 0.000099 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030182 / 0.037411 (-0.007230) | 0.089309 / 0.014526 (0.074783) | 0.103306 / 0.176557 (-0.073250) | 0.162624 / 0.737135 (-0.574511) | 0.108957 / 0.296338 (-0.187381) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.577423 / 0.215209 (0.362214) | 5.900154 / 2.077655 (3.822500) | 2.687369 / 1.504120 (1.183249) | 2.513061 / 1.541195 (0.971866) | 2.506453 / 1.468490 (1.037963) | 0.830838 / 4.584777 (-3.753939) | 5.032195 / 3.745712 (1.286483) | 4.396827 / 5.269862 (-0.873035) | 2.884230 / 4.565676 (-1.681447) | 0.102239 / 0.424275 (-0.322036) | 0.008178 / 0.007607 (0.000571) | 0.710027 / 0.226044 (0.483983) | 7.149626 / 2.268929 (4.880698) | 3.403605 / 55.444624 (-52.041019) | 2.661970 / 6.876477 (-4.214506) | 2.760227 / 2.142072 (0.618154) | 1.043981 / 4.805227 (-3.761246) | 0.195028 / 6.500664 (-6.305636) | 0.065211 / 0.075469 (-0.010258) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.581265 / 1.841788 (-0.260522) | 21.640230 / 8.074308 (13.565922) | 19.031860 / 10.191392 (8.840468) | 0.196903 / 0.680424 (-0.483520) | 0.027061 / 0.534201 (-0.507140) | 0.444995 / 0.579283 (-0.134288) | 0.528195 / 0.434364 (0.093831) | 0.521540 / 0.540337 (-0.018797) | 0.730204 / 1.386936 (-0.656732) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#33f736eafa0f77de03aa6894ea4a6c923702e5d1 \"CML watermark\")\n" ]

"2023-08-03T10:18:32Z"

"2023-08-03T15:08:02Z"

"2023-08-03T10:24:57Z"

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[ "You can avoid this by using the `revision` parameter in `load_dataset` to always force downloading a specific commit (if not specified it defaults to HEAD, hence the redownload).", "Thanks @mariosasko this works well, looks like I should have read the documentation a bit more carefully. \r\n\r\nIt is still a bit confusing which hash I should provide: passing `revision = c8fd66e85f086e3abb11eeee55b1737a3d1e8487` from https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0/commits/main caused the cached version at `~/.cache/huggingface/datasets/mozilla-foundation___common_voice_8_0/en/8.0.0/b2f8b72f8f30b2e98c41ccf855954d9e35a5fa498c43332df198534ff9797a4a` to be loaded, so I had to know that it was the previous commit unless I've missed something else." ]

"2023-08-02T23:18:11Z"

"2023-08-18T23:59:00Z"

"2023-08-18T23:59:00Z"

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[ "Hi! This should be fixed in the latest (patch) release (run `pip install -U datasets` to install it). This behavior was due to a bug in our authentication logic." ]

"2023-08-02T20:20:26Z"

"2023-08-21T18:18:27Z"

"2023-08-21T18:18:27Z"

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[ "Thanks for reporting! This is a bug in converting the `ArrayXD` types to YAML. It will be fixed soon." ]

"2023-08-02T18:21:21Z"

"2023-08-17T16:53:24Z"

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[ "any idea?", "This should work: `load_dataset(\"path/to/downloaded_repo\")`\r\n\r\n`load_from_disk` is intended to be used on directories created with `Dataset.save_to_disk` or `DatasetDict.save_to_disk`" ]

"2023-08-02T09:17:29Z"

"2023-08-17T14:06:02Z"

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[ "This is expected behavior. You must provide `cache_file_name` when performing `.map` on an in-memory dataset for the result to be cached." ]

"2023-08-01T11:58:58Z"

"2023-08-17T14:03:01Z"

"2023-08-17T14:03:00Z"

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[ "Thanks for reporting, @610v4nn1.\r\n\r\nIndeed, the source data files are no longer available. We have contacted the authors of the dataset and they report that Amazon has decided to stop distributing the multilingual reviews dataset.\r\n\r\nWe are adding a notification about this issue to the dataset card.\r\n\r\nSee: https://huggingface.co/datasets/amazon_reviews_multi/discussions/4#64c3898db63057f1fd3ce1a0 " ]

"2023-08-01T08:38:29Z"

"2023-08-02T07:12:07Z"

"2023-08-02T07:12:07Z"

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[ "Yesterday I waited for more than 12 hours to make sure it was really **stuck** instead of proceeding too slow.", "I've had similar weird issues with `load_dataset` as well. Not multiple files, but dataset is quite big, about 50G.", "We use a generic multiprocessing code, so there is little we can do about this - unfortunately, turning off multiprocessing seems to be the only solution. Multithreading would make our code easier to maintain and (most likely) avoid issues such as this one, but we cannot use it until the GIL is dropped (no-GIL Python should be released in 2024, so we can start exploring this then)" ]

"2023-08-01T02:28:06Z"

"2023-08-17T17:36:45Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007678 / 0.011353 (-0.003675) | 0.004233 / 0.011008 (-0.006776) | 0.095934 / 0.038508 (0.057426) | 0.064201 / 0.023109 (0.041092) | 0.345765 / 0.275898 (0.069867) | 0.383089 / 0.323480 (0.059609) | 0.004084 / 0.007986 (-0.003902) | 0.003311 / 0.004328 (-0.001017) | 0.072367 / 0.004250 (0.068117) | 0.048252 / 0.037052 (0.011200) | 0.338340 / 0.258489 (0.079851) | 0.391627 / 0.293841 (0.097786) | 0.045203 / 0.128546 (-0.083343) | 0.013494 / 0.075646 (-0.062153) | 0.314097 / 0.419271 (-0.105174) | 0.058183 / 0.043533 (0.014650) | 0.353946 / 0.255139 (0.098807) | 0.385181 / 0.283200 (0.101981) | 0.033111 / 0.141683 (-0.108572) | 1.578489 / 1.452155 (0.126335) | 1.631660 / 1.492716 (0.138944) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202592 / 0.018006 (0.184586) | 0.506450 / 0.000490 (0.505961) | 0.004630 / 0.000200 (0.004430) | 0.000105 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024761 / 0.037411 (-0.012651) | 0.086295 / 0.014526 (0.071769) | 0.094063 / 0.176557 (-0.082494) | 0.154189 / 0.737135 (-0.582947) | 0.096273 / 0.296338 (-0.200065) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.581731 / 0.215209 (0.366522) | 5.552020 / 2.077655 (3.474365) | 2.430800 / 1.504120 (0.926680) | 2.130864 / 1.541195 (0.589669) | 2.092802 / 1.468490 (0.624312) | 0.833956 / 4.584777 (-3.750821) | 4.840859 / 3.745712 (1.095147) | 4.267812 / 5.269862 (-1.002050) | 2.663245 / 4.565676 (-1.902432) | 0.093195 / 0.424275 (-0.331080) | 0.007942 / 0.007607 (0.000335) | 0.651457 / 0.226044 (0.425413) | 6.782986 / 2.268929 (4.514058) | 3.103307 / 55.444624 (-52.341318) | 2.373933 / 6.876477 (-4.502544) | 2.571613 / 2.142072 (0.429540) | 0.981389 / 4.805227 (-3.823839) | 0.199019 / 6.500664 (-6.301645) | 0.065828 / 0.075469 (-0.009641) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.429778 / 1.841788 (-0.412009) | 20.967563 / 8.074308 (12.893255) | 19.329723 / 10.191392 (9.138331) | 0.222048 / 0.680424 (-0.458376) | 0.033507 / 0.534201 (-0.500694) | 0.436801 / 0.579283 (-0.142482) | 0.530197 / 0.434364 (0.095833) | 0.491532 / 0.540337 (-0.048805) | 0.718216 / 1.386936 (-0.668720) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007798 / 0.011353 (-0.003555) | 0.004748 / 0.011008 (-0.006260) | 0.070847 / 0.038508 (0.032339) | 0.069338 / 0.023109 (0.046229) | 0.400890 / 0.275898 (0.124992) | 0.429482 / 0.323480 (0.106002) | 0.006469 / 0.007986 (-0.001517) | 0.003514 / 0.004328 (-0.000814) | 0.069049 / 0.004250 (0.064798) | 0.059800 / 0.037052 (0.022748) | 0.415644 / 0.258489 (0.157155) | 0.432562 / 0.293841 (0.138721) | 0.043778 / 0.128546 (-0.084768) | 0.015141 / 0.075646 (-0.060506) | 0.081521 / 0.419271 (-0.337750) | 0.054692 / 0.043533 (0.011160) | 0.404497 / 0.255139 (0.149358) | 0.419783 / 0.283200 (0.136583) | 0.029588 / 0.141683 (-0.112094) | 1.593506 / 1.452155 (0.141351) | 1.615977 / 1.492716 (0.123261) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.270981 / 0.018006 (0.252975) | 0.522074 / 0.000490 (0.521584) | 0.026568 / 0.000200 (0.026368) | 0.000126 / 0.000054 (0.000072) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031551 / 0.037411 (-0.005861) | 0.086723 / 0.014526 (0.072197) | 0.103315 / 0.176557 (-0.073242) | 0.154692 / 0.737135 (-0.582443) | 0.099472 / 0.296338 (-0.196866) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.570238 / 0.215209 (0.355029) | 5.655963 / 2.077655 (3.578308) | 2.662670 / 1.504120 (1.158550) | 2.380903 / 1.541195 (0.839709) | 2.409467 / 1.468490 (0.940977) | 0.828055 / 4.584777 (-3.756722) | 4.964698 / 3.745712 (1.218986) | 4.299995 / 5.269862 (-0.969867) | 2.824162 / 4.565676 (-1.741514) | 0.095872 / 0.424275 (-0.328403) | 0.007907 / 0.007607 (0.000300) | 0.701595 / 0.226044 (0.475551) | 7.131965 / 2.268929 (4.863036) | 3.250554 / 55.444624 (-52.194070) | 2.531916 / 6.876477 (-4.344561) | 2.717908 / 2.142072 (0.575835) | 1.014479 / 4.805227 (-3.790748) | 0.223804 / 6.500664 (-6.276861) | 0.071893 / 0.075469 (-0.003576) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.541702 / 1.841788 (-0.300086) | 21.668219 / 8.074308 (13.593911) | 18.916032 / 10.191392 (8.724640) | 0.205915 / 0.680424 (-0.474508) | 0.026356 / 0.534201 (-0.507845) | 0.429122 / 0.579283 (-0.150161) | 0.506110 / 0.434364 (0.071746) | 0.510148 / 0.540337 (-0.030190) | 0.724699 / 1.386936 (-0.662237) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c4ca93ff86551b398c979862e7be7305725a240b \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006884 / 0.011353 (-0.004469) | 0.004492 / 0.011008 (-0.006516) | 0.085439 / 0.038508 (0.046931) | 0.083905 / 0.023109 (0.060796) | 0.313604 / 0.275898 (0.037706) | 0.354683 / 0.323480 (0.031203) | 0.006535 / 0.007986 (-0.001451) | 0.004318 / 0.004328 (-0.000011) | 0.066129 / 0.004250 (0.061879) | 0.057568 / 0.037052 (0.020516) | 0.317162 / 0.258489 (0.058672) | 0.372501 / 0.293841 (0.078660) | 0.031059 / 0.128546 (-0.097488) | 0.009013 / 0.075646 (-0.066634) | 0.288794 / 0.419271 (-0.130478) | 0.053326 / 0.043533 (0.009793) | 0.314318 / 0.255139 (0.059179) | 0.357505 / 0.283200 (0.074305) | 0.027020 / 0.141683 (-0.114663) | 1.530653 / 1.452155 (0.078498) | 1.599782 / 1.492716 (0.107066) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.278788 / 0.018006 (0.260782) | 0.626822 / 0.000490 (0.626333) | 0.003780 / 0.000200 (0.003580) | 0.000086 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031703 / 0.037411 (-0.005708) | 0.085654 / 0.014526 (0.071128) | 0.754858 / 0.176557 (0.578301) | 0.212251 / 0.737135 (-0.524885) | 0.171344 / 0.296338 (-0.124994) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382291 / 0.215209 (0.167082) | 3.825612 / 2.077655 (1.747958) | 1.874553 / 1.504120 (0.370433) | 1.712574 / 1.541195 (0.171379) | 1.791479 / 1.468490 (0.322989) | 0.481005 / 4.584777 (-4.103772) | 3.530559 / 3.745712 (-0.215153) | 3.395305 / 5.269862 (-1.874557) | 2.133747 / 4.565676 (-2.431930) | 0.056139 / 0.424275 (-0.368136) | 0.007424 / 0.007607 (-0.000183) | 0.458321 / 0.226044 (0.232277) | 4.577665 / 2.268929 (2.308736) | 2.380233 / 55.444624 (-53.064392) | 2.004060 / 6.876477 (-4.872417) | 2.290712 / 2.142072 (0.148639) | 0.570157 / 4.805227 (-4.235070) | 0.131670 / 6.500664 (-6.368994) | 0.060684 / 0.075469 (-0.014785) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.294929 / 1.841788 (-0.546858) | 21.386663 / 8.074308 (13.312355) | 14.389440 / 10.191392 (4.198048) | 0.171177 / 0.680424 (-0.509247) | 0.018660 / 0.534201 (-0.515541) | 0.394385 / 0.579283 (-0.184898) | 0.424942 / 0.434364 (-0.009422) | 0.463618 / 0.540337 (-0.076719) | 0.651499 / 1.386936 (-0.735437) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007079 / 0.011353 (-0.004274) | 0.004615 / 0.011008 (-0.006393) | 0.066300 / 0.038508 (0.027792) | 0.092636 / 0.023109 (0.069527) | 0.399080 / 0.275898 (0.123182) | 0.429873 / 0.323480 (0.106393) | 0.006689 / 0.007986 (-0.001297) | 0.004358 / 0.004328 (0.000029) | 0.067155 / 0.004250 (0.062905) | 0.064040 / 0.037052 (0.026988) | 0.399905 / 0.258489 (0.141416) | 0.448237 / 0.293841 (0.154397) | 0.031985 / 0.128546 (-0.096561) | 0.009053 / 0.075646 (-0.066593) | 0.071904 / 0.419271 (-0.347368) | 0.048759 / 0.043533 (0.005227) | 0.386797 / 0.255139 (0.131658) | 0.411240 / 0.283200 (0.128040) | 0.028568 / 0.141683 (-0.113115) | 1.501037 / 1.452155 (0.048882) | 1.594560 / 1.492716 (0.101844) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.300756 / 0.018006 (0.282750) | 0.631220 / 0.000490 (0.630730) | 0.010163 / 0.000200 (0.009963) | 0.000144 / 0.000054 (0.000089) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033716 / 0.037411 (-0.003695) | 0.093562 / 0.014526 (0.079037) | 0.106975 / 0.176557 (-0.069582) | 0.161919 / 0.737135 (-0.575216) | 0.113397 / 0.296338 (-0.182942) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.410392 / 0.215209 (0.195183) | 4.094411 / 2.077655 (2.016756) | 2.085868 / 1.504120 (0.581748) | 1.959589 / 1.541195 (0.418394) | 2.096683 / 1.468490 (0.628193) | 0.494593 / 4.584777 (-4.090184) | 3.854302 / 3.745712 (0.108590) | 3.742303 / 5.269862 (-1.527558) | 2.379983 / 4.565676 (-2.185693) | 0.058640 / 0.424275 (-0.365635) | 0.008092 / 0.007607 (0.000484) | 0.486957 / 0.226044 (0.260912) | 4.855784 / 2.268929 (2.586855) | 2.654029 / 55.444624 (-52.790595) | 2.237627 / 6.876477 (-4.638850) | 2.536955 / 2.142072 (0.394882) | 0.622398 / 4.805227 (-4.182829) | 0.139212 / 6.500664 (-6.361452) | 0.062805 / 0.075469 (-0.012664) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.374862 / 1.841788 (-0.466926) | 22.797015 / 8.074308 (14.722707) | 14.393995 / 10.191392 (4.202603) | 0.196603 / 0.680424 (-0.483821) | 0.018602 / 0.534201 (-0.515599) | 0.394568 / 0.579283 (-0.184715) | 0.408792 / 0.434364 (-0.025572) | 0.486706 / 0.540337 (-0.053631) | 0.652365 / 1.386936 (-0.734571) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5713299a88f527ea162a099c2bf2cbceada8fb86 \"CML watermark\")\n" ]

"2023-07-31T16:32:01Z"

"2023-08-03T10:13:32Z"

"2023-08-03T10:04:18Z"

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[]

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[ "Hi! We use PyArrow to read JSON files, and PyArrow doesn't allow different value types in the same column. #5776 should address this.\r\n\r\nIn the meantime, you can combine `Dataset.from_generator` with the above code to cast the values to the same type. ", "Thanks for your help!" ]

"2023-07-31T12:53:49Z"

"2023-08-18T01:46:35Z"

"2023-08-18T01:46:35Z"

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