Datasets:

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DanielPFlorian

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Transformers-Github-Issues

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=h1) Report\n> Merging [#7221](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/edbaad2c5c94b88cc21b349a403e886bd0b2f156?el=desc) will **decrease** coverage by `0.37%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7221 +/- ##\n==========================================\n- Coverage 79.05% 78.67% -0.38% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n- Hits 26148 26024 -124 \n- Misses 6929 7053 +124 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `24.53% <0.00%> (-63.81%)` | :arrow_down: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `25.24% <0.00%> (-55.76%)` | :arrow_down: |\n| [src/transformers/optimization.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb24ucHk=) | `34.28% <0.00%> (-48.00%)` | :arrow_down: |\n| [src/transformers/optimization\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb25fdGYucHk=) | `33.33% <0.00%> (-24.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `57.28% <0.00%> (-15.08%)` | :arrow_down: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `13.76% <0.00%> (-14.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `52.98% <0.00%> (-13.44%)` | :arrow_down: |\n| [src/transformers/modeling\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190cmFuc2ZvX3hsLnB5) | `67.04% <0.00%> (-12.69%)` | :arrow_down: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `70.47% <0.00%> (-11.91%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.70% <0.00%> (-3.01%)` | :arrow_down: |\n| ... and [13 more](https://codecov.io/gh/huggingface/transformers/pull/7221/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=footer). Last update [edbaad2...d875346](https://codecov.io/gh/huggingface/transformers/pull/7221?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=h1) Report\n> Merging [#7220](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/51c4adf54c4183f8eec25665b15456262a48f827?el=desc) will **increase** coverage by `0.55%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7220 +/- ##\n==========================================\n+ Coverage 78.57% 79.13% +0.55% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n+ Hits 25990 26174 +184 \n+ Misses 7087 6903 -184 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.32% <0.00%> (-73.63%)` | :arrow_down: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `25.24% <0.00%> (-55.76%)` | :arrow_down: |\n| [src/transformers/optimization.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb24ucHk=) | `34.28% <0.00%> (-48.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.38% <0.00%> (-29.59%)` | :arrow_down: |\n| [src/transformers/optimization\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb25fdGYucHk=) | `33.33% <0.00%> (-24.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `57.28% <0.00%> (-15.08%)` | :arrow_down: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `13.76% <0.00%> (-14.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `52.98% <0.00%> (-13.44%)` | :arrow_down: |\n| [src/transformers/modeling\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190cmFuc2ZvX3hsLnB5) | `67.04% <0.00%> (-12.69%)` | :arrow_down: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `70.47% <0.00%> (-11.91%)` | :arrow_down: |\n| ... and [20 more](https://codecov.io/gh/huggingface/transformers/pull/7220/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=footer). Last update [51c4adf...b2b0c1d](https://codecov.io/gh/huggingface/transformers/pull/7220?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=h1) Report\n> Merging [#7219](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7a88ed6c2a740c45cafb2009a124ba056506d6a1?el=desc) will **increase** coverage by `1.53%`.\n> The diff coverage is `89.06%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7219 +/- ##\n==========================================\n+ Coverage 78.00% 79.54% +1.53% \n==========================================\n Files 174 174 \n Lines 33452 33671 +219 \n==========================================\n+ Hits 26095 26784 +689 \n+ Misses 7357 6887 -470 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `81.17% <89.06%> (-15.92%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mdW5uZWwucHk=) | `18.53% <0.00%> (-75.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9seG1lcnQucHk=) | `22.14% <0.00%> (-72.41%)` | :arrow_down: |\n| [src/transformers/activations\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9uc190Zi5weQ==) | `54.16% <0.00%> (-20.84%)` | :arrow_down: |\n| [src/transformers/tokenization\\_dpr.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZHByLnB5) | `53.15% <0.00%> (-4.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG0ucHk=) | `88.77% <0.00%> (-2.55%)` | :arrow_down: |\n| [...rc/transformers/data/datasets/language\\_modeling.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFzZXRzL2xhbmd1YWdlX21vZGVsaW5nLnB5) | `94.11% <0.00%> (+1.17%)` | :arrow_up: |\n| [src/transformers/configuration\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2xvbmdmb3JtZXIucHk=) | `100.00% <0.00%> (+25.00%)` | :arrow_up: |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `71.60% <0.00%> (+51.89%)` | :arrow_up: |\n| ... and [4 more](https://codecov.io/gh/huggingface/transformers/pull/7219/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=footer). Last update [7a88ed6...dba9e29](https://codecov.io/gh/huggingface/transformers/pull/7219?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "- For the tests, I'm not sure what you had in mind. I could create a dumb file that I then compare to the lib.\r\n- It does not matter if this is run before or after `black`: if there is a very long model name, the script will detect differences as soon as black as indeed been run (so it may pass if run before black once but fail at the next CI). Running it after makes sure we don't catch trailing spaces or bad empty lines (empty lines with spaces) in the diff. But this all won't work for replacement of short model names to very long model names (so sadly, we can't have `BertForGenerationAndComputerVisionBoundingBoxesForVisualQuestionAnswering` in the lib).", "- Regarding the tests, I think it would be a requirement given that the script modifies the code when ran with `overwrite`. Testing to ensure it works correctly seems necessary.\r\n- I think it could work with a bit of plumbing: given that the script registers the name change `Bert->Roberta`, the script could change the copied file from `Roberta` to `Bert`, run `black` to correctly format, and check equivalence then. I haven't though much about edge cases but it seems robust enough to me. What do you think?\r\n", "This is great! Very much in favor of this PR :-)" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=h1) Report\n> Merging [#7218](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/51c4adf54c4183f8eec25665b15456262a48f827?el=desc) will **increase** coverage by `3.49%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7218 +/- ##\n==========================================\n+ Coverage 78.57% 82.07% +3.49% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n+ Hits 25990 27147 +1157 \n+ Misses 7087 5930 -1157 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `64.52% <0.00%> (-34.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `70.19% <0.00%> (-23.08%)` | :arrow_down: |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `72.31% <0.00%> (-14.52%)` | :arrow_down: |\n| [src/transformers/configuration\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2dwdDIucHk=) | `91.89% <0.00%> (-5.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG0ucHk=) | `88.37% <0.00%> (-4.87%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `84.17% <0.00%> (-3.06%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.91% <0.00%> (-0.14%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.44% <0.00%> (+0.16%)` | :arrow_up: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `93.18% <0.00%> (+0.35%)` | :arrow_up: |\n| ... and [10 more](https://codecov.io/gh/huggingface/transformers/pull/7218/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=footer). Last update [51c4adf...5b87296](https://codecov.io/gh/huggingface/transformers/pull/7218?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "Thank you for the heads up, @sshleifer \r\n\r\nI'm not able to reproduce those, but let's first thing first let's skip them so that CI is not affected. \r\nhttps://github.com/huggingface/transformers/pull/7220\r\nI will investigate and we can try to enable them again later.", "I've found some other tests failing with USE_CUDA=1, but which were fine on CI - so I will attend to those first.\r\n\r\nHope we could finalize this issue https://github.com/huggingface/transformers/issues/6349 and get USE_CUDA on by default." ]

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[ "@stefan-it might know what's up!", "Oh, I think this PR should fix it:\r\n\r\nhttps://github.com/huggingface/transformers/pull/6571\r\n\r\nI will resolve some merge conflicts, then it should be ready to merge!", "Updated, it should work now :+1: \r\n\r\n@Santosh-Gupta Please try to use the new urls for the GermEval dataset in your Colab :)", "The links have been updated, thanks @stefan-it " ]

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[ "Too bad you didn't get an answer on SO. I think you would multiply your chances of getting a good answer if you asked it over at https://discuss.huggingface.co!", "Sure, I will ask there. Thank you!", "I use weight decay and not use weight and surprisingly find that they are the same, why?" ]

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[ "Hello,\r\n\r\nThank you for solution.\r\n\r\nI just think the change will only return the cross-attention scores for the first layer of the decoder, since len(layer_outputs) will be bigger than 5 only in that case, (because has_relative_attention_bias will be true for i=0 and length of layer_outputs will be 6.)\r\n\r\n if output_attentions:\r\n all_attentions = all_attentions + (layer_outputs[2],) # We keep only self-attention weights for now\r\n if len(layer_outputs) >= 5:\r\n all_attentions = all_attentions + (layer_outputs[2],) + (layer_outputs[4],)\r\n else:\r\n all_attentions = all_attentions + (layer_outputs[2],)\r\n\r\nFor the other layers of the decoder the len(layer_outputs) will be 4, so the cross-attention scores will be in 3rd index in those cases.\r\n\r\nSo I used the code like this, even I am not sure it's the nicest way to do this:\r\n\r\n if output_attentions:\r\n all_attentions = all_attentions + (layer_outputs[2],) # We keep only self-attention weights for now\r\n if self.is_decoder:\r\n if i==0:\r\n all_attentions = all_attentions + (layer_outputs[4],) # add cross-attention weights\r\n else:\r\n all_attentions = all_attentions + (layer_outputs[3],) # add cross-attention weights\r\n\r\n", "Thanks for catching that! With that fix we are able to get the cross-attention weights for each decoder layer.\r\n\r\nIt appears some tests need to be updated as well, but I'm not sure how best to do that.", "Hi, any updates on this issue? Or at least some recommended quick fixes to the code that I can make directly to the code to get the cross-attention? For the fix proposed by @mg9, what exactly did you add to modeling_tf.py? (Do you mind sharing your updated modeling_tf.py?) With @mg9's fix, will the following code return the cross-attention? Thanks for your help in advance.\r\n\r\n```\r\nfrom transformers import T5Tokenizer, T5ForConditionalGeneration\r\ntokenizer = T5Tokenizer.from_pretrained('t5-small')\r\ninput_ids = tokenizer(\"summarize: studies have shown that owning a dog is good for you \", return_tensors=\"pt\").input_ids\r\ndecoder_input_ids = tokenizer(\"<pad>\", add_special_tokens=False, return_tensors=\"pt\").input_ids\r\nmodel = T5ForConditionalGeneration.from_pretrained('t5-small', return_dict=True)\r\noutputs = model(input_ids=input_ids, decoder_input_ids=decoder_input_ids, output_attentions=True)\r\noutputs.encoder_attentions\r\n```", "This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=h1) Report\n> Merging [#7212](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e643a297228c8cb2c189fe4c93e11125f938d20b?el=desc) will **increase** coverage by `0.29%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7212 +/- ##\n==========================================\n+ Coverage 81.47% 81.77% +0.29% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n+ Hits 26949 27048 +99 \n+ Misses 6128 6029 -99 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.32% <0.00%> (-73.63%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `69.10% <0.00%> (-29.80%)` | :arrow_down: |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `79.03% <0.00%> (-7.80%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `86.87% <0.00%> (-0.36%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.01% <0.00%> (-0.33%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.46% <0.00%> (-0.26%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `83.08% <0.00%> (+0.24%)` | :arrow_up: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.20% <0.00%> (+0.27%)` | :arrow_up: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `93.18% <0.00%> (+0.35%)` | :arrow_up: |\n| ... and [8 more](https://codecov.io/gh/huggingface/transformers/pull/7212/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=footer). Last update [e643a29...9da9d68](https://codecov.io/gh/huggingface/transformers/pull/7212?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=h1) Report\n> Merging [#7210](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e643a297228c8cb2c189fe4c93e11125f938d20b?el=desc) will **decrease** coverage by `0.81%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7210 +/- ##\n==========================================\n- Coverage 81.47% 80.65% -0.82% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n- Hits 26949 26679 -270 \n- Misses 6128 6398 +270 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mdW5uZWwucHk=) | `18.53% <0.00%> (-75.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `62.15% <0.00%> (-36.75%)` | :arrow_down: |\n| [src/transformers/activations\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9uc190Zi5weQ==) | `54.16% <0.00%> (-20.84%)` | :arrow_down: |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `79.03% <0.00%> (-7.80%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `84.17% <0.00%> (-3.06%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.36% <0.00%> (-0.98%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.46% <0.00%> (-0.26%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `83.08% <0.00%> (+0.24%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.04% <0.00%> (+0.40%)` | :arrow_up: |\n| ... and [6 more](https://codecov.io/gh/huggingface/transformers/pull/7210/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=footer). Last update [e643a29...63d2ea4](https://codecov.io/gh/huggingface/transformers/pull/7210?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=h1) Report\n> Merging [#7209](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e643a297228c8cb2c189fe4c93e11125f938d20b?el=desc) will **increase** coverage by `0.45%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7209 +/- ##\n==========================================\n+ Coverage 81.47% 81.92% +0.45% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n+ Hits 26949 27099 +150 \n+ Misses 6128 5978 -150 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `64.52% <0.00%> (-34.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `72.31% <0.00%> (-14.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `87.67% <0.00%> (-10.96%)` | :arrow_down: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `82.25% <0.00%> (-9.68%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `86.87% <0.00%> (-6.77%)` | :arrow_down: |\n| [src/transformers/configuration\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2dwdDIucHk=) | `91.89% <0.00%> (-5.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `84.17% <0.00%> (-3.06%)` | :arrow_down: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `82.57% <0.00%> (-1.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_fast.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfZmFzdC5weQ==) | `92.85% <0.00%> (-1.43%)` | :arrow_down: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.00% <0.00%> (-0.67%)` | :arrow_down: |\n| ... and [10 more](https://codecov.io/gh/huggingface/transformers/pull/7209/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=footer). Last update [e643a29...5701aee](https://codecov.io/gh/huggingface/transformers/pull/7209?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "Addressed in https://github.com/huggingface/model_card/pull/3 so closing this one." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=h1) Report\n> Merging [#7207](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0fe6e435b6890a5993047e13a3a38a2e5e6e4dde?el=desc) will **increase** coverage by `1.86%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7207 +/- ##\n==========================================\n+ Coverage 79.74% 81.60% +1.86% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n+ Hits 26376 26994 +618 \n+ Misses 6701 6083 -618 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_fsmt.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19mc210LnB5) | `93.58% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.32% <0.00%> (-73.63%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `62.15% <0.00%> (-36.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.03% <0.00%> (-1.30%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.20% <0.00%> (+0.27%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.45% <0.00%> (+1.50%)` | :arrow_up: |\n| [src/transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19jdHJsLnB5) | `97.58% <0.00%> (+2.41%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `86.87% <0.00%> (+2.69%)` | :arrow_up: |\n| ... and [5 more](https://codecov.io/gh/huggingface/transformers/pull/7207/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=footer). Last update [0fe6e43...13a097a](https://codecov.io/gh/huggingface/transformers/pull/7207?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "Unstale - would be great to have some of these resolved.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=h1) Report\n> Merging [#7204](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0fe6e435b6890a5993047e13a3a38a2e5e6e4dde?el=desc) will **decrease** coverage by `1.14%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7204 +/- ##\n==========================================\n- Coverage 79.74% 78.59% -1.15% \n==========================================\n Files 172 172 \n Lines 33077 33077 \n==========================================\n- Hits 26376 25996 -380 \n- Misses 6701 7081 +380 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `20.38% <0.00%> (-67.72%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `33.57% <0.00%> (-65.72%)` | :arrow_down: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `25.24% <0.00%> (-55.76%)` | :arrow_down: |\n| [src/transformers/optimization.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb24ucHk=) | `34.28% <0.00%> (-48.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.38% <0.00%> (-29.59%)` | :arrow_down: |\n| [src/transformers/optimization\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb25fdGYucHk=) | `33.33% <0.00%> (-24.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `57.28% <0.00%> (-15.08%)` | :arrow_down: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `13.76% <0.00%> (-14.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `70.47% <0.00%> (-11.91%)` | :arrow_down: |\n| ... and [17 more](https://codecov.io/gh/huggingface/transformers/pull/7204/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=footer). Last update [0fe6e43...43ae8f0](https://codecov.io/gh/huggingface/transformers/pull/7204?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=h1) Report\n> Merging [#7202](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0203ad43bcd0b29423dec6ca1a58ed58300f0d61?el=desc) will **decrease** coverage by `2.45%`.\n> The diff coverage is `71.42%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7202 +/- ##\n==========================================\n- Coverage 80.86% 78.41% -2.46% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26114 25322 -792 \n- Misses 6179 6971 +792 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `82.29% <ø> (ø)` | |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `94.44% <ø> (+0.67%)` | :arrow_up: |\n| [src/transformers/modeling\\_dpr.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kcHIucHk=) | `97.83% <ø> (ø)` | |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <ø> (-10.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hbGJlcnQucHk=) | `90.92% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `72.36% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.90% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.33% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `92.25% <ø> (ø)` | |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `87.23% <0.00%> (ø)` | |\n| ... and [26 more](https://codecov.io/gh/huggingface/transformers/pull/7202/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=footer). Last update [0203ad4...da63e64](https://codecov.io/gh/huggingface/transformers/pull/7202?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=h1) Report\n> Merging [#7201](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/45b0b1ff2f28d83c734b7505e1705b799ce2ff84?el=desc) will **increase** coverage by `2.45%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7201 +/- ##\n==========================================\n+ Coverage 78.41% 80.87% +2.45% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n+ Hits 25323 26116 +793 \n+ Misses 6970 6177 -793 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mdW5uZWwucHk=) | `18.53% <0.00%> (-75.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/activations\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9uc190Zi5weQ==) | `54.16% <0.00%> (-20.84%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9ucy5weQ==) | `85.00% <0.00%> (-5.00%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `93.77% <0.00%> (-0.68%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `93.18% <0.00%> (-0.36%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.77% <0.00%> (-0.28%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.20% <0.00%> (+0.27%)` | :arrow_up: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `82.25% <0.00%> (+10.00%)` | :arrow_up: |\n| ... and [5 more](https://codecov.io/gh/huggingface/transformers/pull/7201/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=footer). Last update [45b0b1f...6a1e8df](https://codecov.io/gh/huggingface/transformers/pull/7201?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "Hi! That's a very detailed issue, very cool! Thanks for providing so much information. I believe you have a misconception about how to use `add_special_tokens` and how the special token mask is created.\r\n\r\n## Adding special tokens\r\n\r\nFirstly, if you use the `add_special_tokens=True` flag, that means you expect the tokenizer to handle the special tokens on its own: you should not provide your special tokens. As you've shown in the example, if you encode a sequence with this flag, you'll get the encoded sequence surrounded by the `<bos>` and `<eos>` tokens:\r\n\r\n```py\r\n>>> from transformers import RobertaTokenizer\r\n>>> tokenizer = RobertaTokenizer.from_pretrained(\"roberta-base\")\r\n>>> input_ids_single_sequence = tokenizer.encode(\"This is a sequence\", add_special_tokens=True)\r\n>>> tokenizer.decode(input_ids_single_sequence)\r\n\"<s>This is a sequence</s>\"\r\n```\r\n\r\nIn your case, you're actually using a `<sep>` token as you're encoding two sequences. You can use the tokenizer to do the same, by passing two sequences to it:\r\n\r\n```py\r\n>>> input_ids_sequence_pair = tokenizer.encode(\"This is a sequence\", \"This is another\", add_special_tokens=True)\r\n>>> tokenizer.decode(input_ids_sequence_pair)\r\n'<s>This is a sequence</s></s>This is another</s>'\r\n```\r\n\r\n⚠️ : Please note that the RoBERTa tokenizer is built using only `<s>` (the BOS token) and `</s>` (the SEP token), with two `</s></s>` as the separator.\r\n\r\n## Special token mask\r\n\r\nIf you try generating the special token mask here, you'll see that it has no issue generating it, __as long as you use the `already_has_special_tokens=True` flag__. You've already built the sequences with special tokens, so you should set this flag to `True`.\r\n\r\n```py\r\n>>> tokenizer.get_special_tokens_mask(input_ids_single_sequence, already_has_special_tokens=True)\r\n[1, 0, 0, 0, 0, 1]\r\n>>> tokenizer.get_special_tokens_mask(input_ids_sequence_pair, already_has_special_tokens=True)\r\n[1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1]\r\n```\r\n\r\n## Custom special tokens\r\n\r\nIn your case you want to use different special tokens than what is done with the original RoBERTa implementation. That's okay, but then you should specify it to your tokenizer:\r\n\r\n```py\r\n>>> tokenizer.add_special_tokens({'sep_token': '<i>'})\r\n1 # Returns the number of added tokens\r\n```\r\n\r\nWhen calling the `encode` method, you'll now correctly have the specified separator token where it should be:\r\n\r\n```py\r\n>>> input_ids_sequence_pair = tokenizer.encode(\"This is a sequence\", \"This is another\", add_special_tokens=True)\r\n>>> tokenizer.decode(input_ids_sequence_pair)\r\n'<s>This is a sequence <i> <i> This is another <i>'\r\n```\r\n\r\n## Setting a custom encoding behavior\r\n\r\nIn your use-case you show different behavior than the original RoBERTa tokenizer implementation, where you want your sequences encoded as:\r\n\r\n`<s> [SEQ_A] <i> [SEQ_B] </s>`\r\n\r\nIf you still want to rely on the `add_special_tokens=True` flag in `encode` and the accurate special tokens mask even without respecting the original behavior, you can do so by subclassing the `RobertaTokenizer` (or the fast version) and overriding the following methods `build_inputs_with_special_tokens`, `get_special_tokens_mask`, `create_token_type_ids_from_sequences`:\r\n\r\n```py\r\nclass MyRobertaTokenizer(RobertaTokenizer):\r\n def build_inputs_with_special_tokens(\r\n self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None\r\n ) -> List[int]:\r\n if token_ids_1 is None:\r\n return [self.cls_token_id] + token_ids_0 + [self.eos_token_id]\r\n cls = [self.cls_token_id]\r\n sep = [self.sep_token_id]\r\n eos = [self.eos_token_id]\r\n return cls + token_ids_0 + sep + token_ids_1 + eos\r\n\r\n def get_special_tokens_mask(\r\n self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False\r\n ) -> List[int]:\r\n if already_has_special_tokens:\r\n if token_ids_1 is not None:\r\n raise ValueError(\r\n \"You should not supply a second sequence if the provided sequence of \"\r\n \"ids is already formatted with special tokens for the model.\"\r\n )\r\n return list(map(lambda x: 1 if x in [self.sep_token_id, self.cls_token_id] else 0, token_ids_0))\r\n\r\n if token_ids_1 is None:\r\n return [1] + ([0] * len(token_ids_0)) + [1]\r\n return [1] + ([0] * len(token_ids_0)) + [1] + ([0] * len(token_ids_1)) + [1]\r\n\r\n def create_token_type_ids_from_sequences(\r\n self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None\r\n ) -> List[int]:\r\n sep = [self.sep_token_id]\r\n cls = [self.cls_token_id]\r\n eos = [self.eos_token_id]\r\n\r\n if token_ids_1 is None:\r\n return len(cls + token_ids_0 + eos) * [0]\r\n return len(cls + token_ids_0 + sep + token_ids_1 + eos) * [0]\r\n```\r\n\r\nThis will then correctly encode your methods (given you initialize the correct special token as is done in the following snippet):\r\n\r\n```py\r\ntokenizer = MyRobertaTokenizer.from_pretrained(\"roberta-base\")\r\ntokenizer.add_special_tokens({'cls_token': '<s>', 'sep_token': '<i>', 'eos_token': '</s>'})\r\n\r\nprint(tokenizer.decode(tokenizer.encode(\"This is a sequence\", add_special_tokens=True)))\r\n# <s>This is a sequence</s>\r\n\r\nprint(tokenizer.decode(tokenizer.encode(\"This is a sequence\", \"This is another\", add_special_tokens=True)))\r\n# <s>This is a sequence <i> This is another</s>\r\n```\r\n\r\n## Conclusion\r\n\r\nI hope this helps you! If you need a better understanding of what's happening, I encourage you to read the following documentation pages:\r\n- [RobertaTokenizer](https://huggingface.co/transformers/model_doc/roberta.html#transformers.RobertaTokenizer)\r\n- [Tokenizer main class](https://huggingface.co/transformers/main_classes/tokenizer.html)", "Thanks a lot for the extremely detailed answer! That cleared up a lot of doubts. I worked with some of the code you provided and got to the conclusion that RoBERTa as it is right now is probably not the best fit for my problem, so I'll have to work around that. ", "What a wonderful question and answer!" ]

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[ "Hi there, you have to pass the checkpoint path to the method `Trainer.train` to resume training:\r\n```\r\ntrainer.train(\"checkpoint-9500\")\r\n```\r\nIf you set your logging verbosity to the INFO level (`transformers.logging.set_verbosity_info()`) you should then see information about the training resuming and the number of steps skipped.", "Great, thanks a lot for your help Sylvain.\r\n\r\nWorks perfect.\r\n", "Hey, @fumpe which version of transformers were you using here? Please do let me know.", "> Hi there, you have to pass the checkpoint path to the method `Trainer.train` to resume training:\r\n> \r\n> ```\r\n> trainer.train(\"checkpoint-9500\")\r\n> ```\r\n> \r\n> If you set your logging verbosity to the INFO level (`transformers.logging.set_verbosity_info()`) you should then see information about the training resuming and the number of steps skipped.\r\n\r\n@sgugger if training is over, `num_train_epochs`, is reached, how do you load the checkpoint and train say for the next n epochs? when I load the checkpoint, it only trains until that epoch is over \r\n\r\n```\r\ntrainer.num_train_epochs = trainer.num_train_epochs + 5\r\ntrainer.train(\"checkpoint-9500\")\r\n```\r\n", "`Trainer` does not have a `num_train_epochs` attribute that is used, you need to set `trainer.args.num_train_epochs`. To be sure everything is updated, you probably need to re-instantiate the `Trainer` with the new `TrainingArguments` though.", "@sgugger: I wanted to fine tune a language model using ```--resume_from_checkpoint``` since I had sharded the text file into multiple pieces. I noticed that the ```_save()``` in Trainer doesn't save the optimizer & the scheduler state dicts and so I added a couple of lines to save the state dicts. \r\nAnd I printed the learning rate from scheduler using ```lr_scheduler.get_last_lr()``` in ```_load_optimizer_and_scheduler()``` right after this [line](https://github.com/huggingface/transformers/blob/ac12a5ae47b352458694194ae7c8b971310015ee/src/transformers/trainer.py#L1678). It always prints 0 (as the last learning rate) although I initialize the learning rate with a non-zero value during the first run and I am also leaving the warmup args as default (which is 0). Here's the command I am using to run the script: \r\n\r\n```\r\nCUDA_VISIBLE_DEVICES=2 python lm_scripts/lm_wwm.py --model_name_or_path \"./output_dir/demo1/\" --train_file \\\r\n\"input_data_part2.csv\" --validation_file \"validation.csv\" --logging_dir \"./output_dir/demo_log2\" --logging_steps 1000 \\\r\n--save_steps 1000 --save_total_limit 2 --seed 42 --output_dir \"./output_dir/demo2\" --evaluation_strategy \"epoch\" \\\r\n--per_device_train_batch_size 5 --per_device_eval_batch_size 10 --do_train --do_eval --resume_from_checkpoint True \\\r\n--ignore_data_skip --num_train_epochs 2\r\n``` \r\n\r\nHere's the [gist](https://gist.github.com/adithya8/7823d111efec9f3ff5313f2438068c2e) of the changes I made to the trainer code (Lines 904, 905, 1602, 1603). It would be super helpful if you could point me in the right direction to fix this?", "@adithya8 The optimizer, learning rate scheduler, state of the scalers and all the RNGs are saved when doing a checkpoint, you should check the list of files you have in your `checkpoint-xxx` folder.", "Gotcha! Thanks", "When I resume training from a checkpoint, I use a new batch size different from the previous training and it seems that the number of the skipped epoch is wrong.\r\n\r\nFor example, I trained a model for 10 epochs with `per_device_train_batch_size=10` and generate a checkpoint. Then I resume training from this checkpoint with `per_device_train_batch_size=10`, the trainer will skip 12 epochs.\r\n\r\nWhat should I do if I want to resume training with a different batch size?", "That feature is not supported, you should resume training with the exact same hyperparameters or start a new training if you want to change them.", "I have trained a model and saved the checkpoint，Now I want to increase the number of epochs to continue training, but I have a problem.My training loss is not able to match the previous training, there is a very big difference（First up, then down, but not down to the original level）.I increased the number of epochs from 20 to 30.\r\n`training_args = TrainingArguments( \r\n output_dir= models_path + '/' + chain + '_' + modeltype + 'bert/two/log',\r\n save_total_limit=5,\r\n do_train=True,\r\n do_eval=True,\r\n evaluation_strategy='epoch',\r\n #eval_steps=1,\r\n overwrite_output_dir=True,\r\n num_train_epochs=30,\r\n per_device_train_batch_size=128,\r\n learning_rate=9.282980634054497e-05,\r\n weight_decay=0.1531103573951345,\r\n warmup_ratio=0.05549995455206759,\r\n logging_first_step=True,\r\n ignore_data_skip=True,\r\n save_steps=100,\r\n logging_dir = models_path + '/' + chain + '_' + modeltype + 'bert/two/runs/' + datetime.datetime.strftime(datetime.datetime.now(),'%Y-%m-%d_%H:%M:%S'),\r\n logging_steps=10,\r\n seed = 19930606\r\n )`\r\n`trainer = Trainer(\r\n model=model,\r\n args=training_args,\r\n data_collator=data_collator,\r\n train_dataset=train_dataset,\r\n eval_dataset = eva_dataset\r\n )`\r\n` trainer.train(resume_from_checkpoint=True)`\r\nThanks a lot for the help.", "> have trained a model and saved the checkpoint，Now I want to increase the number of epochs to continue training, but I have a problem.My training loss is not able to match the previous training, there is a very big difference（First up, then down, but not down to the original level）.I increased the number of epochs\r\n\r\n\r\n\r\n> That feature is not supported, you should resume training with the exact same hyperparameters or start a new training if you want to change them.\r\n\r\nFor example i want to freeze some layers in the checkpointed model. Is it possible?", "I have two bin files like pytorch_model-00001-of-00002.bin and pytorch_model-00002-of-00002.bin in the checkpoint-1000 folder but it won't load! It still says that \"ValueError: Can't find a valid checkpoint at checkpoint-1000.\"", "Make sure you are using a source install of Transformers. This is a bug that was recently fixed @oscar-eaglewatch ", "How do I differentiate between,\r\n\r\n1. continue pre-training from a checkpoint with the previous optimizer/scheduler state\r\n2. continue pre-training from a checkpoint but reset the optimizer and the scheduler \r\n\r\n", "@sgugger I have been changing my hyperparameters and got `Can't find a valid checkpoint`. Now it seems I cannot find the original hyperparameter settings (esp. `for` `per_device_train_batch_size`, `gradient_accumulation_steps`, and `max_steps`). I did find the `max_steps` in some json file in the checkpoint, but not the other hyperparameter settings. How can I find out the settings I should pick?", "Hi, there, I got same error with deepspeed. training noramlly and resume got `Can't find a valid checkpoint`\r\n\r\nfirst I try resume_from_checkpoint with `out/lora-Vicuna-chat` (output_path) got `Can't find a valid checkpoint`\r\nthen I send `out/lora-Vicuna-chat/checkpoint-6000` I can not load the lora weights........\r\n\r\n```\r\n\"base_model.model.model.layers.31.self_attn.k_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.self_attn.v_proj.weight\", \"base_model.model.model.layers.31.self_attn.v_proj.lora_A.default.weight\", \r\n\"base_model.model.model.layers.31.self_attn.v_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.self_attn.o_proj.weight\", \"base_model.model.model.layers.31.self_attn.o_proj.lora_A.default.weight\", \r\n\"base_model.model.model.layers.31.self_attn.o_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.self_attn.rotary_emb.inv_freq\", \"base_model.model.model.layers.31.mlp.gate_proj.weight\", \r\n\"base_model.model.model.layers.31.mlp.gate_proj.lora_A.default.weight\", \"base_model.model.model.layers.31.mlp.gate_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.mlp.down_proj.weight\", \r\n\"base_model.model.model.layers.31.mlp.down_proj.lora_A.default.weight\", \"base_model.model.model.layers.31.mlp.down_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.mlp.up_proj.weight\", \r\n\"base_model.model.model.layers.31.mlp.up_proj.lora_A.default.weight\", \"base_model.model.model.layers.31.mlp.up_proj.lora_B.default.weight\", \"base_model.model.model.layers.31.input_layernorm.weight\", \r\n Unexpected key(s) in state_dict:\"base_model.model.model.layers.31.self_attn.q_proj.lora_A.weight\", \"base_model.model.model.layers.31.self_attn.q_proj.lora_B.weight\", \"base_model.model.model.layers.31.self_attn.k_proj.lora_A.weight\", \r\n\"base_model.model.model.layers.31.self_attn.k_proj.lora_B.weight\", \"base_model.model.model.layers.31.self_attn.v_proj.lora_A.weight\", \"base_model.model.model.layers.31.self_attn.v_proj.lora_B.weight\", \r\n\"base_model.model.model.layers.31.self_attn.o_proj.lora_A.weight\", \"base_model.model.model.layers.31.self_attn.o_proj.lora_B.weight\", \"base_model.model.model.layers.31.mlp.gate_proj.lora_A.weight\", \r\n\"base_model.model.model.layers.31.mlp.gate_proj.lora_B.weight\", \"base_model.model.model.layers.31.mlp.down_proj.lora_A.weight\", \"base_model.model.model.layers.31.mlp.down_proj.lora_B.weight\", \r\n```\r\n\r\nthe model with some suffix `default`, but samed model didn't have......\r\n\r\nI am confused so much", "Transformers have been a few years old, I thought that it should be mature by now, atleast 1 core version that works flawlessly all the way. \r\n\r\nBut man, basic and simple issues like saving checkpoints, weight reload, resume, skip dataset etc... with pure transformers or deepspeed...still bumping around, real pain in the b** :( ... I must say that I admired Yolov5 most in the way they described things, annoucing news, bugs fixed. My 2 cents for this great repo, it deserves much more than this.", "Falling back to 4.28.1 :((", "I am having the same problem with Deepspeed, it seems that a different format of checkpoint is expected for Deepspeed. Did you manage to resolve the issue? @lucasjinreal lucasjinreal " ]

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "As the error says, `get_shape` does not exist in PyTorch parameters. Use `[...].shape` instead of `[...].get_shape()`." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=h1) Report\n> Merging [#7194](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4f6e52574248636352a746cfe6cc0b13cf3eb7f9?el=desc) will **increase** coverage by `2.14%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7194 +/- ##\n==========================================\n+ Coverage 78.63% 80.78% +2.14% \n==========================================\n Files 174 174 \n Lines 33446 33446 \n==========================================\n+ Hits 26300 27018 +718 \n+ Misses 7146 6428 -718 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mdW5uZWwucHk=) | `18.53% <0.00%> (-75.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `69.10% <0.00%> (-29.80%)` | :arrow_down: |\n| [src/transformers/activations\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9uc190Zi5weQ==) | `54.16% <0.00%> (-20.84%)` | :arrow_down: |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `79.03% <0.00%> (-7.80%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `86.87% <0.00%> (-0.36%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `94.27% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <0.00%> (ø)` | |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.04% <0.00%> (+0.13%)` | :arrow_up: |\n| ... and [10 more](https://codecov.io/gh/huggingface/transformers/pull/7194/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=footer). Last update [4f6e525...2c2aa9e](https://codecov.io/gh/huggingface/transformers/pull/7194?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Have you tested invoking run_eval.py/finetune.py from examples/seq2seq? \r\n\r\nThat is the workflow documented in `seq2seq/README.md`\r\n\r\nThis command is cheap and if it starts running you know you are fine:\r\n\r\nhttps://discuss.huggingface.co/t/good-command-to-test-examples-seq2seq-refactors/982", "Ah, we need tests that aren't tests too :) \r\n\r\nGood catch!\r\n```\r\ncd examples/seq2seq/\r\npython ./run_eval.py -h\r\nTraceback (most recent call last):\r\n File \"./run_eval.py\", line 15, in <module>\r\n from .utils import calculate_bleu, calculate_rouge, parse_numeric_n_bool_cl_kwargs, use_task_specific_params\r\nImportError: attempted relative import with no known parent package\r\n```\r\n\r\nback to the drawing board.\r\n\r\nThanks for your vigilance, @sshleifer ", "OK, so while `conftest.py` worked for tests, it left the scripts broken. So in the 2nd attempt I replaced `conftest.py` with `__init__.py` that does the same and works for both types. \r\n\r\n@sshleifer, @LysandreJik \r\n\r\n\r\n#### Header added by sam because what is below is tangentially related to this PR :)\r\n\r\np.s. it looks like importing a local module from a script is a very controversial thing from reading SO. If using the retry approach, it's still probably more readable to do:\r\n\r\n```\r\nif __name__ == '__main__':\r\n from mymodule import aaa\r\nelse:\r\n from .mymodule import aaa\r\n```\r\nwhich is more telling.\r\n", "> This command is cheap and if it starts running you know you are fine:\r\n\r\nMuch faster to test is to:\r\n```\r\npython finetune.py -h\r\n```", "Pycharm users who develop on seq2seq a lot (I can think of 0 others haha) may need to change Preferences/Project Structure/Content Root to accommodate this. I posted [instructions](https://discuss.huggingface.co/t/pycharm-project-structure-seq2seq/1206) on the forums that I'll delete if this doesn't get merged: .", "Merging this with the idea that there is a 10% chance we will have to revert because of some unforeseen dealbreaking issue." ]

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "sadly I think `pytest.param` was needed or each entry needs to be a list or something:\r\n\r\nhttps://circle-production-customer-artifacts.s3.amazonaws.com/picard/forks/5bdabdd888af1f000130874a/278214696/5f62bdadb33de21283aa7519-0-build/artifacts/test_output.txt?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200917T014628Z&X-Amz-SignedHeaders=host&X-Amz-Expires=59&X-Amz-Credential=AKIAJR3Q6CR467H7Z55A%2F20200917%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=4ec6c5af819aab91ed8103865ad61af3617a43c8ffa34fe5192a45e3067e3cc0\r\n\r\n\r\n```\r\n__________ ERROR collecting examples/seq2seq/test_seq2seq_examples.py __________\r\nexamples/seq2seq/test_seq2seq_examples.py::test_finetune: in \"parametrize\" the number of names (1):\r\n ['model']\r\nmust be equal to the number of values (31):\r\n patrickvonplaten/t5-tiny-random\r\n__________ ERROR collecting examples/seq2seq/test_seq2seq_examples.py __________\r\n```", "> sadly I think `pytest.param` was needed or each entry needs to be a list or something:\r\nright I didn't run all tests, didn't see the other entries used an inefficient use of `parametrize`.\r\n\r\nInstead of:\r\n```\r\[email protected](\"model\", [BART_TINY, MBART_TINY])\r\n```\r\nThey were using:\r\n```\r\[email protected]([\"model\"], ...\r\n```\r\nnotice the argument names are normally a string and not a list. Since it was made into the list, that's why all the extra code.\r\n\r\na recent addition: https://huggingface.co/transformers/master/testing.html#parametrization\r\n\r\nBTW, if we switch to `parametrized` (which is now part of the dependencies for `dev`) it works identically with `unittest` and `pytest` tests - same API.\r\n\r\nI fixed it and now:\r\n\r\n```\r\npytest --disable-warnings examples/seq2seq/test_seq2seq_examples.py --collect-only -q\r\n[...]\r\nexamples/seq2seq/test_seq2seq_examples.py::test_run_eval_slow[sshleifer/bart-tiny-random]\r\nexamples/seq2seq/test_seq2seq_examples.py::test_run_eval\r\nexamples/seq2seq/test_seq2seq_examples.py::test_run_eval_slow[sshleifer/tiny-mbart]\r\n[...]\r\n```\r\n", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=h1) Report\n> Merging [#7192](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/45b0b1ff2f28d83c734b7505e1705b799ce2ff84?el=desc) will **increase** coverage by `1.08%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7192 +/- ##\n==========================================\n+ Coverage 78.41% 79.50% +1.08% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n+ Hits 25323 25673 +350 \n+ Misses 6970 6620 -350 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.83% <0.00%> (-0.72%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.91% <0.00%> (-0.14%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `88.34% <0.00%> (+63.80%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG0ucHk=) | `93.23% <0.00%> (+74.20%)` | :arrow_up: |\n| ... and [2 more](https://codecov.io/gh/huggingface/transformers/pull/7192/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=footer). Last update [45b0b1f...d329cf2](https://codecov.io/gh/huggingface/transformers/pull/7192?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=h1) Report\n> Merging [#7191](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.45%`.\n> The diff coverage is `70.83%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7191 +/- ##\n==========================================\n- Coverage 80.86% 79.41% -1.46% \n==========================================\n Files 169 169 \n Lines 32293 32322 +29 \n==========================================\n- Hits 26115 25668 -447 \n- Misses 6178 6654 +476 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/trainer\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyX3V0aWxzLnB5) | `58.88% <56.52%> (-1.41%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `55.72% <80.00%> (+0.25%)` | :arrow_up: |\n| [src/transformers/training\\_args.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmluZ19hcmdzLnB5) | `91.74% <100.00%> (+0.07%)` | :arrow_up: |\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| ... and [13 more](https://codecov.io/gh/huggingface/transformers/pull/7191/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=footer). Last update [3babef8...29ce623](https://codecov.io/gh/huggingface/transformers/pull/7191?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=h1) Report\n> Merging [#7190](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0203ad43bcd0b29423dec6ca1a58ed58300f0d61?el=desc) will **decrease** coverage by `2.21%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7190 +/- ##\n==========================================\n- Coverage 80.86% 78.65% -2.22% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26114 25399 -715 \n- Misses 6179 6894 +715 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtLnB5) | `16.26% <0.00%> (-66.67%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `33.57% <0.00%> (-65.72%)` | :arrow_down: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `25.85% <0.00%> (-55.15%)` | :arrow_down: |\n| [src/transformers/tokenization\\_mbart.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWJhcnQucHk=) | `57.14% <0.00%> (-39.69%)` | :arrow_down: |\n| [src/transformers/tokenization\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZnVubmVsLnB5) | `62.79% <0.00%> (-34.89%)` | :arrow_down: |\n| [src/transformers/optimization\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb25fdGYucHk=) | `33.33% <0.00%> (-24.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `57.28% <0.00%> (-15.08%)` | :arrow_down: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `13.76% <0.00%> (-14.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `52.98% <0.00%> (-13.44%)` | :arrow_down: |\n| ... and [19 more](https://codecov.io/gh/huggingface/transformers/pull/7190/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=footer). Last update [0203ad4...dd95009](https://codecov.io/gh/huggingface/transformers/pull/7190?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "I'm going to add it here https://github.com/huggingface/transformers/pull/7153 where it really belongs" ]

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[ "The base models for all architectures are not usable with `Trainer` since they don't have a training objective. You need to pick the model class adapted to your task.", "> The base models for all architectures are not usable with `Trainer` since they don't have a training objective. You need to pick the model class adapted to your task.\r\n\r\nThank you!\r\nI replaced the model class \"LongformerModel\" with the \"LongformerForSequenceClassification\".\r\nand got an error. \r\nValueError: Expected input batch_size (2) to match target batch_size (256).\r\nWhich class of Longformer model is suitable for me (if any)?\r\nActually I'd like to perform a multi-classification task with my dataset.\r\n\r\n```\r\nValueError Traceback (most recent call last)\r\n<ipython-input-76-0c647bc3a8b8> in <module>()\r\n----> 1 get_ipython().run_cell_magic('time', '', 'trainer.train()')\r\n\r\n11 frames\r\n<decorator-gen-60> in time(self, line, cell, local_ns)\r\n\r\n<timed eval> in <module>()\r\n\r\n/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in nll_loss(input, target, weight, size_average, ignore_index, reduce, reduction)\r\n 2214 if input.size(0) != target.size(0):\r\n 2215 raise ValueError('Expected input batch_size ({}) to match target batch_size ({}).'\r\n-> 2216 .format(input.size(0), target.size(0)))\r\n 2217 if dim == 2:\r\n 2218 ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)\r\n\r\nValueError: Expected input batch_size (2) to match target batch_size (256).\r\n```", "You can't use a `DataCollatorForLanguageModeling` for a classification task, this data collator prepares the data for language modeling (with masking since you set that option to `True`).", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "Hello, thank you for the review!\r\n\r\nNow the PR passes all the tests, but I think I messed up many commits by using a wrong version of style libraries.\r\n\r\nWould it be okay to close and resubmit this PR? (https://github.com/huggingface/transformers/pull/7202)", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=h1) Report\n> Merging [#7188](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0203ad43bcd0b29423dec6ca1a58ed58300f0d61?el=desc) will **increase** coverage by `0.46%`.\n> The diff coverage is `71.42%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7188 +/- ##\n==========================================\n+ Coverage 80.86% 81.33% +0.46% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n+ Hits 26114 26264 +150 \n+ Misses 6179 6029 -150 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `82.29% <ø> (ø)` | |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `94.44% <ø> (+0.67%)` | :arrow_up: |\n| [src/transformers/modeling\\_dpr.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kcHIucHk=) | `97.83% <ø> (ø)` | |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `82.25% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hbGJlcnQucHk=) | `90.92% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `72.36% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.90% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.33% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `92.25% <ø> (ø)` | |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `87.23% <0.00%> (ø)` | |\n| ... and [22 more](https://codecov.io/gh/huggingface/transformers/pull/7188/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=footer). Last update [0203ad4...4bc0e5f](https://codecov.io/gh/huggingface/transformers/pull/7188?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "cc @stas00 " ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=h1) Report\n> Merging [#7185](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.43%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7185 +/- ##\n==========================================\n- Coverage 80.86% 79.43% -1.44% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 25653 -462 \n- Misses 6178 6640 +462 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `80.70% <0.00%> (-5.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| ... and [9 more](https://codecov.io/gh/huggingface/transformers/pull/7185/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=footer). Last update [3babef8...57bf96a](https://codecov.io/gh/huggingface/transformers/pull/7185?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=h1) Report\n> Merging [#7184](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.08%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7184 +/- ##\n==========================================\n- Coverage 80.86% 79.78% -1.09% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 25764 -351 \n- Misses 6178 6529 +351 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9sb25nZm9ybWVyLnB5) | `16.37% <0.00%> (-82.31%)` | :arrow_down: |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `19.71% <0.00%> (-72.34%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bert\\_generation.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydF9nZW5lcmF0aW9uLnB5) | `39.28% <0.00%> (-55.36%)` | :arrow_down: |\n| [src/transformers/tokenization\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdDUucHk=) | `60.39% <0.00%> (-34.66%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `67.79% <0.00%> (-31.36%)` | :arrow_down: |\n| [src/transformers/configuration\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2xvbmdmb3JtZXIucHk=) | `75.00% <0.00%> (-25.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `75.91% <0.00%> (-21.17%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `88.17% <0.00%> (-5.02%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.45% <0.00%> (-3.01%)` | :arrow_down: |\n| ... and [11 more](https://codecov.io/gh/huggingface/transformers/pull/7184/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=footer). Last update [3babef8...a932393](https://codecov.io/gh/huggingface/transformers/pull/7184?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=h1) Report\n> Merging [#7183](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.41%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7183 +/- ##\n==========================================\n- Coverage 80.86% 79.45% -1.42% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 25657 -458 \n- Misses 6178 6636 +458 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `81.70% <0.00%> (-4.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| ... and [8 more](https://codecov.io/gh/huggingface/transformers/pull/7183/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=footer). Last update [3babef8...bac886f](https://codecov.io/gh/huggingface/transformers/pull/7183?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=h1) Report\n> Merging [#7182](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `3.82%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7182 +/- ##\n==========================================\n- Coverage 80.86% 77.04% -3.83% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 24880 -1235 \n- Misses 6178 7413 +1235 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/configuration\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3JlZm9ybWVyLnB5) | `21.62% <0.00%> (-78.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yZWZvcm1lci5weQ==) | `16.87% <0.00%> (-77.64%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `42.10% <0.00%> (-57.90%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bert\\_generation.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydF9nZW5lcmF0aW9uLnB5) | `39.28% <0.00%> (-55.36%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `13.37% <0.00%> (-42.10%)` | :arrow_down: |\n| [src/transformers/tokenization\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZnVubmVsLnB5) | `62.79% <0.00%> (-34.89%)` | :arrow_down: |\n| [src/transformers/training\\_args.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmluZ19hcmdzLnB5) | `66.66% <0.00%> (-25.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `71.60% <0.00%> (-20.44%)` | :arrow_down: |\n| [src/transformers/tokenization\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcmVmb3JtZXIucHk=) | `81.66% <0.00%> (-13.34%)` | :arrow_down: |\n| [src/transformers/trainer\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyX3V0aWxzLnB5) | `47.05% <0.00%> (-13.24%)` | :arrow_down: |\n| ... and [9 more](https://codecov.io/gh/huggingface/transformers/pull/7182/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=footer). Last update [3babef8...9f70c36](https://codecov.io/gh/huggingface/transformers/pull/7182?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=h1) Report\n> Merging [#7181](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.42%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7181 +/- ##\n==========================================\n- Coverage 80.86% 79.44% -1.43% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 25656 -459 \n- Misses 6178 6637 +459 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `81.70% <0.00%> (-4.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| ... and [10 more](https://codecov.io/gh/huggingface/transformers/pull/7181/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=footer). Last update [3babef8...9d0a80a](https://codecov.io/gh/huggingface/transformers/pull/7181?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=h1) Report\n> Merging [#7180](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **increase** coverage by `1.04%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7180 +/- ##\n==========================================\n+ Coverage 80.86% 81.91% +1.04% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n+ Hits 26115 26453 +338 \n+ Misses 6178 5840 -338 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `70.19% <0.00%> (-23.08%)` | :arrow_down: |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `71.60% <0.00%> (-20.44%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `76.70% <0.00%> (-6.07%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `86.69% <0.00%> (-0.54%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `93.54% <0.00%> (+0.35%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.04% <0.00%> (+0.40%)` | :arrow_up: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `94.44% <0.00%> (+0.67%)` | :arrow_up: |\n| [...rc/transformers/data/datasets/language\\_modeling.py](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFzZXRzL2xhbmd1YWdlX21vZGVsaW5nLnB5) | `94.11% <0.00%> (+1.17%)` | :arrow_up: |\n| ... and [5 more](https://codecov.io/gh/huggingface/transformers/pull/7180/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=footer). Last update [3babef8...61fe03d](https://codecov.io/gh/huggingface/transformers/pull/7180?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=h1) Report\n> Merging [#7179](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3babef815c5372d039202b2247a4ed6afb2a410a?el=desc) will **decrease** coverage by `1.42%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7179 +/- ##\n==========================================\n- Coverage 80.86% 79.44% -1.43% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26115 25656 -459 \n- Misses 6178 6637 +459 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `81.70% <0.00%> (-4.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| ... and [9 more](https://codecov.io/gh/huggingface/transformers/pull/7179/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=footer). Last update [3babef8...c5157d5](https://codecov.io/gh/huggingface/transformers/pull/7179?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks for sharing – Next time please open just one PR it will be easier to fix things!" ]

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[ "Found solution:\r\n --per_gpu_train_batch_size=1 \\\r\nI will be closing this issue now, thank you so much!\r\nSorry for the trouble!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=h1) Report\n> Merging [#7175](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/df165065c37329880f490025972f81b4daa6e5bd?el=desc) will **increase** coverage by `0.27%`.\n> The diff coverage is `0.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7175 +/- ##\n==========================================\n+ Coverage 80.71% 80.99% +0.27% \n==========================================\n Files 169 169 \n Lines 32293 32305 +12 \n==========================================\n+ Hits 26066 26165 +99 \n+ Misses 6227 6140 -87 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/trainer\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyX3RmLnB5) | `12.01% <0.00%> (-0.45%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9sb25nZm9ybWVyLnB5) | `16.37% <0.00%> (-82.31%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `77.73% <0.00%> (-19.35%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.83% <0.00%> (-0.72%)` | :arrow_down: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `80.75% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.04% <0.00%> (+0.27%)` | :arrow_up: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `94.27% <0.00%> (+0.33%)` | :arrow_up: |\n| [...rc/transformers/data/datasets/language\\_modeling.py](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFzZXRzL2xhbmd1YWdlX21vZGVsaW5nLnB5) | `94.11% <0.00%> (+1.17%)` | :arrow_up: |\n| ... and [6 more](https://codecov.io/gh/huggingface/transformers/pull/7175/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=footer). Last update [df16506...b72f0d9](https://codecov.io/gh/huggingface/transformers/pull/7175?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Nice catch!! LGTM.", "@LysandreJik I fully agree on adding tests for the trainer. I put this immediately on top of my todo list.", "> \r\n> \r\n> @LysandreJik I fully agree on adding tests for the trainer. I put this immediately on top of my todo list.\r\n\r\n@LysandreJik @jplu If you agree, may I help to build tests for the TFTrainer? If so, probably I need to discuss with @jplu how to proceed though.", "@chiapas I will definitely be glad to have your help on this! Can you send me an email (it is displayed on my Github profile) please, and I will let you know how we can proceed.", "If you could copy and adapt the tests in trainer (so that they run quickly) on a regression problem, it would be awesome!", "> \r\n> \r\n> If you could copy and adapt the tests in trainer (so that they run quickly) on a regression problem, it would be awesome!\r\n\r\nWe are going to build the tests for TFTrainer soon. But the HF team can decide if to merge this PR now or after the tests are built.", "LGTM for merge, what do you think @sgugger?", "Yes, good to merge. Thanks @chiapas!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=h1) Report\n> Merging [#7174](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/df165065c37329880f490025972f81b4daa6e5bd?el=desc) will **decrease** coverage by `0.40%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7174 +/- ##\n==========================================\n- Coverage 80.71% 80.31% -0.41% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26066 25936 -130 \n- Misses 6227 6357 +130 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `99.15% <100.00%> (ø)` | |\n| [src/transformers/tokenization\\_mbart.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWJhcnQucHk=) | `96.82% <100.00%> (ø)` | |\n| [src/transformers/tokenization\\_pegasus.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcGVnYXN1cy5weQ==) | `95.23% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.32% <0.00%> (-73.63%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.83% <0.00%> (-0.72%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.01% <0.00%> (-0.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `93.77% <0.00%> (-0.17%)` | :arrow_down: |\n| [src/transformers/tokenization\\_dpr.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZHByLnB5) | `57.65% <0.00%> (+4.50%)` | :arrow_up: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `89.45% <0.00%> (+10.24%)` | :arrow_up: |\n| ... and [2 more](https://codecov.io/gh/huggingface/transformers/pull/7174/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=footer). Last update [df16506...e73ba1f](https://codecov.io/gh/huggingface/transformers/pull/7174?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=h1) Report\n> Merging [#7173](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/df165065c37329880f490025972f81b4daa6e5bd?el=desc) will **decrease** coverage by `0.21%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7173 +/- ##\n==========================================\n- Coverage 80.71% 80.50% -0.22% \n==========================================\n Files 169 169 \n Lines 32293 32291 -2 \n==========================================\n- Hits 26066 25996 -70 \n- Misses 6227 6295 +68 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `99.13% <ø> (-0.02%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `13.37% <0.00%> (-42.10%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `69.10% <0.00%> (-29.80%)` | :arrow_down: |\n| [src/transformers/training\\_args.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmluZ19hcmdzLnB5) | `66.66% <0.00%> (-25.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/trainer\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyX3V0aWxzLnB5) | `47.05% <0.00%> (-13.24%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/data/datasets/glue.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFzZXRzL2dsdWUucHk=) | `83.58% <0.00%> (-2.99%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| ... and [8 more](https://codecov.io/gh/huggingface/transformers/pull/7173/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=footer). Last update [df16506...66eb6ea](https://codecov.io/gh/huggingface/transformers/pull/7173?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "I have the same problem, if you have solved, cound you tell me how? thx!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=h1) Report\n> Merging [#7171](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/df165065c37329880f490025972f81b4daa6e5bd?el=desc) will **decrease** coverage by `1.25%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7171 +/- ##\n==========================================\n- Coverage 80.71% 79.46% -1.26% \n==========================================\n Files 169 169 \n Lines 32293 32293 \n==========================================\n- Hits 26066 25661 -405 \n- Misses 6227 6632 +405 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `20.85% <0.00%> (-71.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.59% <0.00%> (-23.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `88.17% <0.00%> (-5.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.92% <0.00%> (-0.28%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| ... and [9 more](https://codecov.io/gh/huggingface/transformers/pull/7171/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=footer). Last update [df16506...fc2d6ab](https://codecov.io/gh/huggingface/transformers/pull/7171?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "It works on a branch, will cleanup+share shortly!", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

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[ "Haven’t we fixed a memory leak on master recently?", "Yes we did, though this might be a different problem.\r\n\r\nTo make sure, can you please check if you have the bug with an install from source?", "@sgugger yeah, I'm installing from source (not sure why the script yielded 3.0.2)", "I encountered the problem, too, especially using NSP objective, the memory usage much higher than MLM.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "I encounter this problem too when I try to train on multi-nodes and multi GPUs. \r\nAnd my transformers version is 4.15.0, so does this issue have the answer?\r\n@choidongyeon @julien-c @sgugger " ]

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[ "The [PAD] tokens are not used for loss calculation if I remembered correctly, and therefore its predictions has no meaning. You should just ignore the [PAD] tokens results.\r\n\r\nPut [PAD] tokens into loss calculation will make the model biased toward [PAD] tokens, which is undesirable." ]

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[ "Hi @raphael0202 , we converted the fairseq checkpoints using [this script](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_roberta_original_pytorch_checkpoint_to_pytorch.py), maybe the language model head was not transfered during the conversion. \r\nYou can either use the model in fairseq as per [our website](https://camembert-model.fr/) or try to understand if and why the LM head hasn't transfered from fairseq to transformers.", "Check this tutorial as well for huggingface: https://huggingface.co/camembert-base", "After a bit of search I found out the warning comes from the way the decoder bias is defined in the code, the same warning is issued when loading the roberta model (see issue 6193). I checked that the LM head decoder bias is the same as the one in the original pytorch checkpoint.\r\nThank you for your help!", "Ok perfect, thanks for fixing this." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=h1) Report\n> Merging [#7166](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/85ffda96fcadf70d2558ba0a59c84b9f5a2d6f0f?el=desc) will **increase** coverage by `0.98%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7166 +/- ##\n==========================================\n+ Coverage 78.44% 79.42% +0.98% \n==========================================\n Files 168 168 \n Lines 32309 32309 \n==========================================\n+ Hits 25346 25663 +317 \n+ Misses 6963 6646 -317 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `21.12% <0.00%> (-71.05%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `80.70% <0.00%> (-5.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.04% <0.00%> (+0.13%)` | :arrow_up: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.44% <0.00%> (+0.16%)` | :arrow_up: |\n| ... and [5 more](https://codecov.io/gh/huggingface/transformers/pull/7166/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=footer). Last update [b00cafb...8fe976a](https://codecov.io/gh/huggingface/transformers/pull/7166?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Can you add a language tag? `fr` I guess or `fr-BE` if you want to use BCP 47 (cc @yjernite 😛) which we are thinking of supporting", "Sure! I'm not sure exactly where to add it, could you enlighten me?", "see https://huggingface.co/docs#what-metadata-can-i-add-to-my-model-card and let me know if it's not clear!", "I guess in that case the BCP-47 code would still just be `fr` since the text it's trained on isn't specifically Belgian afaiu :) (Unless I'm missing something @antoiloui )", "Yes you're right @yjernite, I put the `fr`tag :)" ]

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[ "Do you have a link to the colab?", "I was following the tutorial by Joey S and tried to include my own dataset instead. This is the notebook that he has provided:\r\nhttps://colab.research.google.com/drive/1odn0VHb4SmQnUqtOwK6XQTLpoTSbneCf?usp=sharing\r\n\r\nThe notebook he provided already has the error.\r\nThank you so much for taking a look!", "The error seems to not be here anymore when doing `!pip3 install git+https://github.com/huggingface/transformers` instead of `pip3 install transformers` and resetting to factory settings before doing the run.", "Thank you so much! It's working now!", "Glad I could help!" ]

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[ "I tried the resolution in #3627, but the output shape changed from 13088 to 768", "@jplu might be interested in this.", "I cannot really test because I don't have your `trans_model` but as far as I can say it is not working because you are using the high level API (with Keras) to create a saved_model. For models with custom layers it is recommended to use the low level way, like this:\r\n\r\n```\r\nfrom transformers import TFOpenAIGPTLMHeadModel\r\nimport tensorflow as tf\r\n\r\ntf_model = TFOpenAIGPTLMHeadModel.from_pretrained('openai-gpt')\r\nmax_len = None\r\n\r\ninput_ids = tf.keras.layers.Input(shape=(max_len,), name='input_ids_layer', dtype='int32')\r\ntoken_type_ids = tf.keras.layers.Input(shape=(max_len,), name='token_type_ids_layer', dtype='int32')\r\nkeras_input = [input_ids, token_type_ids]\r\n\r\nqa_output = tf_model(input_ids, token_type_ids=token_type_ids)[0]\r\nkeras_model = tf.keras.Model(inputs= keras_input, outputs = qa_output)\r\nkeras_model.summary()\r\ntf.saved_model.save(\"./saved_model\")\r\nprint('**************************')\r\nmodel = tf.saved_model.load(\"./saved_model\")\r\n```\r\n\r\nFor me this works well.", "> tf.saved_model.save(\"./saved_model\")\r\n\r\nyou mean `tf.saved_model.save(keras_model, \"./saved_model\")` ?\r\nI try it\r\n```python\r\ntf.saved_model.save(\"./saved_model\")\r\nprint('**************************')\r\nmodel = tf.saved_model.load(\"./saved_model\")\r\ntf_logits = model.predict([tf_input_ids, tf_token_type_ids])\r\n```\r\nand the error:\r\n\r\n```bash\r\ntf_logits = model.predict([tf_input_ids, tf_token_type_ids])\r\nAttributeError: '_UserObject' object has no attribute 'predict'\r\n```", "> you mean tf.saved_model.save(keras_model, \"./saved_model\")\r\n\r\nYes sorry.\r\n\r\nThe error you get is normal because you are not loading a Keras model, but a Tensorflow model. To get a prediction you have to do something like:\r\n```\r\nmodel([tf_input_ids, None, tf_token_type_ids])\r\n```\r\n", "I changed the code as following:\r\n```python\r\ntf_logits = model([tf_input_ids, tf_token_type_ids])\r\n```\r\nand the error:\r\n```bash\r\nValueError: Could not find matching function to call loaded from the SavedModel. Got:\r\n Positional arguments (3 total):\r\n * [<tf.Tensor 'inputs:0' shape=(1, 5) dtype=int64>, <tf.Tensor 'inputs_1:0' shape=(1, 5) dtype=int64>]\r\n * False\r\n * None\r\n Keyword arguments: {}\r\n\r\nExpected these arguments to match one of the following 4 option(s):\r\n\r\nOption 1:\r\n Positional arguments (3 total):\r\n * [TensorSpec(shape=(None, None), dtype=tf.int32, name='input_ids_layer'), TensorSpec(shape=(None, None), dtype=tf.int32, name='token_type_ids_layer')]\r\n * False\r\n * None\r\n Keyword arguments: {}\r\n\r\nOption 2:\r\n Positional arguments (3 total):\r\n * [TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs/0'), TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs/1')]\r\n * True\r\n * None\r\n Keyword arguments: {}\r\n\r\nOption 3:\r\n Positional arguments (3 total):\r\n * [TensorSpec(shape=(None, None), dtype=tf.int32, name='input_ids_layer'), TensorSpec(shape=(None, None), dtype=tf.int32, name='token_type_ids_layer')]\r\n * True\r\n * None\r\n Keyword arguments: {}\r\n\r\nOption 4:\r\n Positional arguments (3 total):\r\n * [TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs/0'), TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs/1')]\r\n * False\r\n * None\r\n Keyword arguments: {}\r\n```", "Can you try:\r\n```\r\nmodel([tf_input_ids, tf_token_type_ids], False, None)\r\n```", "I try it, and the same error.\r\n\r\nMore information: In face, my ultimate objective is to use the savedmodel for tfserving. But I get the error when querying the serving:\r\n```bash\r\nInput to reshape is a tensor with 3840 values, but the requested shape has 768\\n\\t [[{{node functional_1/tf_open_aigptlm_head_model/transformer/Reshape_3}}]]\\n\\t [[StatefulPartitionedCall/StatefulPartitionedCall]]'}\r\n```\r\nIt means getting 3840(768*5) values instead of 768.\r\nAnd considering the original error:\r\n```bash\r\nFirst structure: type=TensorSpec str=TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs')\r\n\r\nSecond structure: type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='input_ids')}\r\n\r\nMore specifically: Substructure \"type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='input_ids')}\" is a sequence, while substructure \"type=TensorSpec str=TensorSpec(shape=(None, None), dtype=tf.int32, name='inputs')\" is not\r\nEntire first structure:\r\n.\r\nEntire second structure:\r\n{'input_ids': .}\r\n```\r\nDoes it mean the input is replicated 5 times? And where the shape (None, 5) come from?", "5 is the default input when a None input shape is given.\r\n\r\nIt means there is certainly a bug with handling Keras symbolic Tensors. In order to be sure can you run:\r\n\r\n```\r\nsaved_model_cli show --dir ./saved_model --tag_set serve --signature_def serving_default\r\n```", "```bash\r\nsaved_model_cli show --dir ./saved_model --tag_set serve --signature_def serving_default\r\n\r\nThe given SavedModel SignatureDef contains the following input(s):\r\n inputs['input_ids_layer'] tensor_info:\r\n dtype: DT_INT32\r\n shape: (-1, -1)\r\n name: serving_default_input_ids_layer:0\r\n inputs['token_type_ids_layer'] tensor_info:\r\n dtype: DT_INT32\r\n shape: (-1, -1)\r\n name: serving_default_token_type_ids_layer:0\r\nThe given SavedModel SignatureDef contains the following output(s):\r\n outputs['tf_open_aigptlm_head_model'] tensor_info:\r\n dtype: DT_FLOAT\r\n shape: (-1, -1, 13088)\r\n name: StatefulPartitionedCall:0\r\nMethod name is: tensorflow/serving/predict\r\n```\r\nIn the code\r\n```python\r\nkeras_model = tf.keras.Model(inputs= keras_input, outputs = qa_output)\r\nkeras_model.summary()\r\nkeras_model.save(\"./saved_model\")\r\nprint('**************************')\r\nmodel = tf.keras.models.load_model(\"./saved_model\")\r\n```\r\nWhen I use the `keras_model` directly, it works perfectly in a dialogue task. But after saving it to savedmodel, everything collapse.", "Ok, the first thing I see is that the names doesn't correspond to the name we use internally, it might be one of the cause that brings the issue.", "Sorry, which names do you mean? Is it a `transformers` library bug or my code mistake?", "> Sorry, which names do you mean? Is it a transformers library bug or my code mistake?\r\n\r\nIn the lib.\r\n\r\nAlso by name I mean that you are using `input_ids_layer` and `token_type_ids_layer` while internally they are `input_ids` and `token_type_ids`.", "So what should I do? Remove the `_layer` string?", "It won't solve your problem. For now there is not a \"practical\" solution to get a saved model unless you set everything yourself:\r\n```\r\nfrom transformers import TFOpenAIGPTLMHeadModel, OpenAIGPTTokenizer\r\nimport tensorflow as tf\r\n\r\ntokenizer = OpenAIGPTTokenizer.from_pretrained(\"openai-gpt\")\r\nmodel = TFOpenAIGPTLMHeadModel.from_pretrained(\"openai-gpt\")\r\ninputs = tokenizer(\"Put a sentence here\", return_tensors=\"tf\")\r\nmodel._saved_model_inputs_spec = None\r\nmodel._set_save_spec(dict(inputs))\r\ntf.saved_model.save(model, \"./saved_model\")\r\n``` \r\n\r\nAnd then using it normally with TF serving. This solution has a big constraint, you have to set manually the size of your input sequence. This is for now the only solution I can give you because we haven't make the TF models fully TF Serving compliant yet. This is planed for a future release.", "Thanks! Looking forward to the new release.", "Or this should do the trick:\r\n\r\n```\r\ntf_model = TFOpenAIGPTLMHeadModel.from_pretrained('openai-gpt')\r\ninput_ids = tf.keras.layers.Input(shape=(128,), name='input_ids', dtype='int32')\r\ntoken_type_ids = tf.keras.layers.Input(shape=(128,), name='token_type_ids', dtype='int32')\r\nkeras_input = [input_ids, token_type_ids]\r\n\r\nqa_output = tf_model(input_ids, token_type_ids=token_type_ids)[0]\r\nkeras_model = tf.keras.Model(inputs= keras_input, outputs = [qa_output])\r\nkeras_model.trainable = False\r\nkeras_model.summary()\r\nkeras_model.save(\"./saved_model\", save_format=\"tf\")\r\n```\r\nWith this I can run the saved_model inside the TF serving Docker image, but for all the cases you have to set yourself your sequence length.", "Sorry, I need a dynamic input length for the dialogue task.", "As a temporary solution you can set the size of your inputs to the max length of the tokenizer. As you won't be able to get bigger sequences from the tokenizer you can be safe.", "I use the following code:\r\n\r\n```python\r\ntf_model = TFOpenAIGPTLMHeadModel.from_pretrained('./trans_model', from_pt=True)\r\nmax_len = 128\r\ninput_ids = tf.keras.layers.Input(shape=(max_len,), name='input_ids', dtype='int32')\r\ntoken_type_ids = tf.keras.layers.Input(shape=(max_len,), name='token_type_ids', dtype='int32')\r\nkeras_input = [input_ids, token_type_ids]\r\n\r\nqa_output = tf_model(input_ids, token_type_ids=token_type_ids)[0]\r\nkeras_model = tf.keras.Model(inputs= keras_input, outputs = qa_output)\r\nkeras_model.trainable = False\r\nkeras_model.summary()\r\nkeras_model.save(\"./saved_model\", save_format=\"tf\")\r\n```\r\nI use `keras_model` directly to predict.\r\nThe strange thing is the first 2 predicting always worked fine, while the third predicting collapse (the model always uses the previous sequence to predict the next put, so the input shape will plus 1 each time).\r\n```bash\r\n>>> 你现在做什么工作呢\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 12).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 12).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 12).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 12).\r\nlogits shape: (1, 12, 13088)\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 13).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 13).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 13).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 13).\r\nlogits shape: (1, 13, 13088)\r\nTraceback (most recent call last):\r\n File \"interact_test.py\", line 233, in <module>\r\n run()\r\n File \"interact_test.py\", line 225, in run\r\n out_ids = sample_sequence(history, tokenizer, keras_model, args)\r\n File \"interact_test.py\", line 121, in sample_sequence\r\n tf_logits = model.predict([tf_input_ids, tf_token_type_ids])\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\", line 130, in _method_wrapper\r\n return method(self, *args, **kwargs)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\", line 1599, in predict\r\n tmp_batch_outputs = predict_function(iterator)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py\", line 780, in __call__\r\n result = self._call(*args, **kwds)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py\", line 814, in _call\r\n results = self._stateful_fn(*args, **kwds)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 2829, in __call__\r\n return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 1848, in _filtered_call\r\n cancellation_manager=cancellation_manager)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 1924, in _call_flat\r\n ctx, args, cancellation_manager=cancellation_manager))\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 550, in call\r\n ctx=ctx)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/execute.py\", line 60, in quick_execute\r\n inputs, attrs, num_outputs)\r\ntensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 14 values, but the requested shape requires a multiple of 128\r\n [[node functional_1/tf_open_aigptlm_head_model/transformer/Reshape_2 (defined at /home/t9kuser/.local/lib/python3.6/site-packages/transformers/modeling_tf_openai.py:342) ]] [Op:__inference_predict_function_15804]\r\n\r\nErrors may have originated from an input operation.\r\nInput Source operations connected to node functional_1/tf_open_aigptlm_head_model/transformer/Reshape_2:\r\n functional_1/Cast_1 (defined at interact_test.py:121)\r\n\r\nFunction call stack:\r\npredict_function\r\n```\r\n\r\n```bash\r\n>>> 你好\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 5).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 5).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 5).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 5).\r\nlogits shape: (1, 5, 13088)\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 6).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"input_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 6).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 6).\r\nWARNING:tensorflow:Model was constructed with shape (None, 128) for input Tensor(\"token_type_ids:0\", shape=(None, 128), dtype=int32), but it was called on an input with incompatible shape (None, 6).\r\nlogits shape: (1, 6, 13088)\r\nTraceback (most recent call last):\r\n File \"interact_test.py\", line 233, in <module>\r\n run()\r\n File \"interact_test.py\", line 225, in run\r\n out_ids = sample_sequence(history, tokenizer, keras_model, args)\r\n File \"interact_test.py\", line 121, in sample_sequence\r\n tf_logits = model.predict([tf_input_ids, tf_token_type_ids])\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\", line 130, in _method_wrapper\r\n return method(self, *args, **kwargs)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\", line 1599, in predict\r\n tmp_batch_outputs = predict_function(iterator)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py\", line 780, in __call__\r\n result = self._call(*args, **kwds)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py\", line 814, in _call\r\n results = self._stateful_fn(*args, **kwds)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 2829, in __call__\r\n return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 1848, in _filtered_call\r\n cancellation_manager=cancellation_manager)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 1924, in _call_flat\r\n ctx, args, cancellation_manager=cancellation_manager))\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py\", line 550, in call\r\n ctx=ctx)\r\n File \"/home/t9kuser/.local/lib/python3.6/site-packages/tensorflow/python/eager/execute.py\", line 60, in quick_execute\r\n inputs, attrs, num_outputs)\r\ntensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 7 values, but the requested shape requires a multiple of 128\r\n [[node functional_1/tf_open_aigptlm_head_model/transformer/Reshape_2 (defined at /home/t9kuser/.local/lib/python3.6/site-packages/transformers/modeling_tf_openai.py:342) ]] [Op:__inference_predict_function_15804]\r\n\r\nErrors may have originated from an input operation.\r\nInput Source operations connected to node functional_1/tf_open_aigptlm_head_model/transformer/Reshape_2:\r\n functional_1/Cast_1 (defined at interact_test.py:121)\r\n\r\nFunction call stack:\r\npredict_function\r\n```", "And the savedmodel error:\r\n\r\n```bash\r\n{'error': '{{function_node __inference__wrapped_model_10271}} {{function_node __inference__wrapped_model_10271}} Incompatible shapes: [1,128,768] vs. [1,5,768]\\n\\t [[{{node functional_1/tf_open_aigptlm_head_model/transformer/add}}]]\\n\\t [[StatefulPartitionedCall/StatefulPartitionedCall]]'}\r\n```", "The pretrained model can be downloaded here: https://drive.google.com/file/d/1Wyr-fD4KuF0gWMtZ7STF09O2Ebtly-yq/view?usp=sharing\r\nThis is my source code:\r\nYou can reproduce the error, thanks a lot!\r\n```python\r\n# # Copyright (c) 2019-present, HuggingFace Inc.\r\n# All rights reserved.\r\n# This source code is licensed under the BSD-style license found in the\r\n# LICENSE file in the root directory of this source tree.\r\nimport os\r\nimport logging\r\nimport random\r\nfrom itertools import chain\r\nfrom argparse import ArgumentParser\r\nfrom pprint import pformat\r\nimport torch\r\nimport tensorflow as tf\r\nimport torch.nn.functional as F\r\nimport sys\r\nimport numpy as np\r\n\r\nfrom transformers import OpenAIGPTLMHeadModel, GPT2LMHeadModel, BertTokenizer, TFOpenAIGPTLMHeadModel\r\n\r\nSPECIAL_TOKENS = [\"[CLS]\", \"[SEP]\", \"[PAD]\", \"[speaker1]\", \"[speaker2]\"]\r\n\r\n\r\ndef top_filtering(logits, top_k=0, top_p=0.0, threshold=-float('Inf'), filter_value=-float('Inf')):\r\n \"\"\" Filter a distribution of logits using top-k, top-p (nucleus) and/or threshold filtering\r\n Args:\r\n logits: logits distribution shape (vocabulary size)\r\n top_k: <=0: no filtering, >0: keep only top k tokens with highest probability.\r\n top_p: <=0.0: no filtering, >0.0: keep only a subset S of candidates, where S is the smallest subset\r\n whose total probability mass is greater than or equal to the threshold top_p.\r\n In practice, we select the highest probability tokens whose cumulative probability mass exceeds\r\n the threshold top_p.\r\n threshold: a minimal threshold to keep logits\r\n \"\"\"\r\n assert logits.dim() == 1 # Only work for batch size 1 for now - could update but it would obfuscate a bit the code\r\n top_k = min(top_k, logits.size(-1))\r\n if top_k > 0:\r\n # Remove all tokens with a probability less than the last token in the top-k tokens\r\n indices_to_remove = logits < torch.topk(logits, top_k)[0][..., -1, None]\r\n logits[indices_to_remove] = filter_value\r\n\r\n if top_p > 0.0:\r\n # Compute cumulative probabilities of sorted tokens\r\n sorted_logits, sorted_indices = torch.sort(logits, descending=True)\r\n cumulative_probabilities = torch.cumsum(F.softmax(sorted_logits, dim=-1), dim=-1)\r\n\r\n # Remove tokens with cumulative probability above the threshold\r\n sorted_indices_to_remove = cumulative_probabilities > top_p\r\n # Shift the indices to the right to keep also the first token above the threshold\r\n sorted_indices_to_remove[..., 1:] = sorted_indices_to_remove[..., :-1].clone()\r\n sorted_indices_to_remove[..., 0] = 0\r\n\r\n # Back to unsorted indices and set them to -infinity\r\n indices_to_remove = sorted_indices[sorted_indices_to_remove]\r\n logits[indices_to_remove] = filter_value\r\n\r\n indices_to_remove = logits < threshold\r\n logits[indices_to_remove] = filter_value\r\n\r\n return logits\r\n\r\n\r\ndef build_input_from_segments(history, reply, tokenizer, with_eos=True):\r\n \"\"\" Build a sequence of input from 3 segments: persona, history and last reply \"\"\"\r\n bos, eos, pad, speaker1, speaker2 = tokenizer.convert_tokens_to_ids(SPECIAL_TOKENS)\r\n sequence = [[bos]] + history + [reply + ([eos] if with_eos else [])]\r\n# print('sequence 1', sequence)\r\n sequence = [sequence[0]] + [[speaker2 if i % 2 else speaker1] + s for i, s in enumerate(sequence[1:])]\r\n# print('sequence 2', sequence)\r\n instance = {}\r\n instance[\"input_ids\"] = list(chain(*sequence))\r\n instance[\"token_type_ids\"] = [bos] + [speaker2 if i % 2 else speaker1 for i, s in enumerate(sequence[1:])\r\n for _ in s]\r\n return instance, sequence\r\n\r\n\r\ndef sample_sequence(history, tokenizer, model, args, current_output=None):\r\n special_tokens_ids = tokenizer.convert_tokens_to_ids(SPECIAL_TOKENS)\r\n# print(special_tokens_ids)\r\n if current_output is None:\r\n current_output = []\r\n\r\n for i in range(args.max_length):\r\n instance, sequence = build_input_from_segments(history, current_output, tokenizer, with_eos=False)\r\n input_ids = torch.tensor(instance[\"input_ids\"], dtype=torch.long, device=args.device).unsqueeze(0)\r\n token_type_ids = torch.tensor(instance[\"token_type_ids\"], dtype=torch.long, device=args.device).unsqueeze(0)\r\n# print(type(input_ids))\r\n# print(input_ids.shape)\r\n# print('input_ids', input_ids)\r\n# print('token_type_ids', token_type_ids)\r\n# logits, *_ = model(input_ids, token_type_ids=token_type_ids)\r\n# print(type(logits))\r\n# print(logits.shape)\r\n# print(logits)\r\n tf_input_ids = input_ids.numpy()\r\n tf_token_type_ids = token_type_ids.numpy()\r\n# tf_input_ids_pad = np.pad(tf_input_ids, ((0, 0), (0, 128 - tf_input_ids.shape[1])), 'constant')\r\n# print(tf_input_ids_pad.shape)\r\n# print(tf_input_ids_pad)\r\n tf_logits = model.predict([tf_input_ids, tf_token_type_ids])\r\n logits = torch.from_numpy(tf_logits)\r\n\r\n# tf_logits, *_ = model(tf_input_ids, token_type_ids=tf.constant(tf_token_type_ids))\r\n# logits = torch.from_numpy(tf_logits.numpy())\r\n# print(type(tf_logits))\r\n print('logits shape: ', tf_logits.shape)\r\n# print(tf_logits)\r\n \r\n logits = logits[0, -1, :] / args.temperature\r\n print('logits tmp shape: ', logits.shape)\r\n logits = top_filtering(logits, top_k=args.top_k, top_p=args.top_p)\r\n print('logits filter shape: ', logits.shape)\r\n probs = F.softmax(logits, dim=-1)\r\n print('probs shape: ', probs.shape)\r\n\r\n prev = torch.topk(probs, 1)[1] if args.no_sample else torch.multinomial(probs, 1)\r\n print('prev: ', prev)\r\n if i < args.min_length and prev.item() in special_tokens_ids:\r\n while prev.item() in special_tokens_ids:\r\n prev = torch.multinomial(probs, num_samples=1)\r\n\r\n if prev.item() in special_tokens_ids:\r\n break\r\n current_output.append(prev.item())\r\n\r\n return current_output\r\n\r\n\r\ndef run():\r\n parser = ArgumentParser()\r\n parser.add_argument('--gpt2', action='store_true', help=\"use gpt2\")\r\n parser.add_argument(\"--model_checkpoint\", type=str, default=\"./LCCD_GPT\", help=\"Path, url or short name of the model\")\r\n parser.add_argument(\"--max_history\", type=int, default=2, help=\"Number of previous utterances to keep in history\")\r\n parser.add_argument(\"--device\", type=str, default=\"cpu\",\r\n help=\"Device (cuda or cpu)\")\r\n\r\n parser.add_argument(\"--no_sample\", action='store_true', help=\"Set to use greedy decoding instead of sampling\")\r\n parser.add_argument(\"--max_length\", type=int, default=30, help=\"Maximum length of the output utterances\")\r\n parser.add_argument(\"--min_length\", type=int, default=1, help=\"Minimum length of the output utterances\")\r\n parser.add_argument(\"--seed\", type=int, default=42, help=\"Seed\")\r\n parser.add_argument(\"--temperature\", type=int, default=0.7, help=\"Sampling softmax temperature\")\r\n parser.add_argument(\"--top_k\", type=int, default=0, help=\"Filter top-k tokens before sampling (<=0: no filtering)\")\r\n parser.add_argument(\"--top_p\", type=float, default=0.9,\r\n help=\"Nucleus filtering (top-p) before sampling (<=0.0: no filtering)\")\r\n args = parser.parse_args()\r\n\r\n logging.basicConfig(level=logging.INFO)\r\n logger = logging.getLogger(__file__)\r\n logger.info(pformat(args))\r\n\r\n if args.model_checkpoint == \"\":\r\n logging.error(\"Checkpoint needed!\")\r\n return\r\n\r\n random.seed(args.seed)\r\n torch.random.manual_seed(args.seed)\r\n torch.cuda.manual_seed(args.seed)\r\n\r\n logger.info(\"Get pretrained model and tokenizer\")\r\n tokenizer_class = BertTokenizer\r\n tokenizer = tokenizer_class.from_pretrained(args.model_checkpoint, do_lower_case=True)\r\n tf_model = TFOpenAIGPTLMHeadModel.from_pretrained('./trans_model', from_pt=True)\r\n max_len = 128\r\n\r\n input_ids = tf.keras.layers.Input(shape=(max_len,), name='input_ids', dtype='int32')\r\n token_type_ids = tf.keras.layers.Input(shape=(max_len,), name='token_type_ids', dtype='int32')\r\n keras_input = [input_ids, token_type_ids]\r\n\r\n qa_output = tf_model(input_ids, token_type_ids=token_type_ids)[0]\r\n print('**************************')\r\n print(type(qa_output))\r\n print(qa_output)\r\n keras_model = tf.keras.Model(inputs= keras_input, outputs = [qa_output])\r\n keras_model.trainable = False\r\n keras_model.summary()\r\n# keras_model.save(\"./saved_model\", save_format=\"tf\")\r\n# tf.saved_model.save(keras_model, \"./saved_model\")\r\n# model = tf.saved_model.load(\"./saved_model\")\r\n# keras_model.save(\"./saved_model\")\r\n# print('**************************')\r\n# model = tf.keras.models.load_model(\"./saved_model\")\r\n\r\n def tokenize(obj):\r\n if isinstance(obj, str):\r\n return tokenizer.convert_tokens_to_ids(tokenizer.tokenize(obj))\r\n if isinstance(obj, dict):\r\n return dict((n, tokenize(o)) for n, o in obj.items())\r\n return list(tokenize(o) for o in obj)\r\n\r\n history = []\r\n while True:\r\n raw_text = input(\">>> \")\r\n while not raw_text:\r\n print('Prompt should not be empty!')\r\n raw_text = input(\">>> \")\r\n sys.stdout.flush()\r\n# print(raw_text)\r\n raw_text = \" \".join(list(raw_text.replace(\" \", \"\")))\r\n# print(raw_text)\r\n sys.stdout.flush()\r\n history.append(tokenize(raw_text))\r\n# print('history', history)\r\n with torch.no_grad():\r\n out_ids = sample_sequence(history, tokenizer, keras_model, args)\r\n history.append(out_ids)\r\n history = history[-(2 * args.max_history + 1):]\r\n out_text = tokenizer.decode(out_ids, skip_special_tokens=True)\r\n print(out_text)\r\n\r\n\r\nif __name__ == \"__main__\":\r\n run()\r\n\r\n```", "For now I don't really have time to check this, but as far as I can see, the issue is that you are not giving a sequence of 128, your sequences have to be padded to 128. If at each step you get one more element to your sequence, you can remove one padding everytime. Example:\r\n\r\n1st iteration, shape [1, 128, 13088]:\r\n[[\r\n [embed char 1],\r\n [embed char 2],\r\n [embed char 3],\r\n [embed char 4],\r\n [embed char 5],\r\n [embed padding],\r\n [embed padding],\r\n [embed padding],\r\n ...\r\n [embed padding]\r\n]]\r\n\r\n2nd iteration, shape [1, 128, 13088]:\r\n[[\r\n [embed char 1],\r\n [embed char 2],\r\n [embed char 3],\r\n [embed char 4],\r\n [embed char 5],\r\n [embed char 6],\r\n [embed padding],\r\n [embed padding],\r\n ...\r\n [embed padding]\r\n]]\r\n\r\nAnd so on.\r\n", "Yes, I tried this before. But the performance declined a lot. Thanks for your patience!", "Same Issue in Electra.\r\n\r\ni think, the TensorSpec below seems to be a dummy input for building TF2 model in transformers library.\r\n\r\n`{'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='input_ids')}`\r\n\r\nbut, i don't know why, that dummy is alive after saving and loading.", "All the models are initialized with this input. If you want to change it you have to recompile it with your own input as I shown in my previous posts.", "@wulikai1993 \r\n> Yes, I tried this before. But the performance declined a lot. Thanks for your patience!\r\n\r\nIndeed the perf will decline, but you still get the same issue?", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "@jplu any updates? Default exporting or dynamic shapes are still failing for me", "@jplu Even by using your approach, still get the error on XLM models (max_len set to 192 in the `Input`):\r\n```\r\nValueError: The two structures don't have the same nested structure.\r\n\r\nFirst structure: type=TensorSpec str=TensorSpec(shape=(None, 192), dtype=tf.int32, name='inputs')\r\n\r\nSecond structure: type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='input_ids')}\r\n\r\nMore specifically: Substructure \"type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='input_ids')}\" is a sequence, while substructure \"type=TensorSpec str=TensorSpec(shape=(None, 192), dtype=tf.int32, name='inputs')\" is not\r\n```\r\n\r\nHere is the model template, which works perfectly before exporting and trying to load it again:\r\n```\r\ndef get_model(transformer, num_classes=1, max_len=512):\r\n input_word_ids = Input(shape=(192,), dtype=tf.int32, name=\"input_word_ids\")\r\n sequence_output = transformer(input_word_ids)[0]\r\n cls_token = sequence_output[:, 0, :]\r\n out = Dense(num_classes, activation='sigmoid')(cls_token)\r\n \r\n model = Model(inputs=input_word_ids, outputs=out)\r\n model.compile(Adam(lr=1e-5), loss='binary_crossentropy', metrics=['accuracy'])\r\n \r\n return model\r\n```" ]

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[ "Seems to be a problem with the 'google/pegasus-arxiv' model, when you use 'google/pegasus-xsum' you get:\r\n`Harry Potter and the Philosopher’s Stone is the seventh and final book in JK Rowling’s Harry Potter series.`\r\nas output", "Yes I tried different pegasus models (including alot of other models) and pegasus-large e.G. outputs this (which I think is really good1):\r\n_In this sequel to the phenomenally popular Harry Potter and the Sorcerer’s Stone, Harry returns to Hogwarts School of Witchcraft and Wizardry for his second year after a miserable summer with his Muggle (nonmagical) relatives. Rowling clearly hit on a winning formula with the first Harry Potter book; the second book — though still great fun — feels a tad, well, formulaic.'_\r\n\r\nwhile pegasus-multinews outputs pretty well generated texts, but unfortunately wrong in the content:\r\n_– The seventh and final book in the Harry Potter series, Harry Potter and the Sorcerer\\'s Stone, is out today. The sixth book in the series, Harry Potter and the Deathly Hallows, was released in the US in advance of tomorrow\\'s release in the UK. Here\\'s what critics are saying about the seventh and final book in the series: The plot is still compelling, but the book \"feels a tad, well, formulaic,\" writes James Poniewozik in Time. \"The atmosphere Rowling creates is unique; the story whizzes along; Harry is an unassuming and completely sympathetic hero. But, truth to tell, you may feel as if you\\'ve read it all before. Rowling clearly hit on a winning formula with the first Harry Potter book; the second book—though still great fun—feels a tad, well, formulaic.\"'_\r\n\r\nGigaword and billsum are both also outputting non useful texts. \r\n\r\nAlso another question, while pegasus-large and pegasus-cnn_dailymail both only return the most important sentences, pegasus-multinews generates even new text. I was hoping the same for the arxiv model, is there a reason that it differs in that way?", "`pegasus-arxiv` is trained on and expects scientific text.\r\n`pegasus-multinews` expects news I presume.\r\n\r\nIf you want to prove a bug, try running an evaluation on a public dataset from the datasets package, and posting the result #6844 .", "# Environment info\r\ntransformers version: 3.1.0\r\nPlatform: Windows - 10\r\nPython version: 3.7.6\r\nPyTorch version (GPU?): 1.5.0 (False)\r\nUsing GPU in script?: no\r\nUsing distributed or parallel set-up in script?: no\r\n\r\n\r\n## To Reproduce\r\n\r\nI found unexpected behaviour when using Pegasus-Pubmed on Pubmed document.\r\n\r\n```\r\nimport torch\r\nfrom transformers import PegasusForConditionalGeneration, PegasusTokenizer\r\n\r\nsrc_text =\"\"\"although the association is modest , it is important because of the increasing prevalence of metabolic syndrome and the effect that depression can have on the ability of patients to successfully make lifestyle changes and comply with medication required for hypertension and dyslipidemia . the association is demonstrated here in a general population to our knowledge for the first time , whereas earlier studies ( table 1 ) used subgroups of populations ( 813,17 ) . this distinction is important because many individuals with metabolic syndrome have diabetes , which itself is known to be associated with depression ( 5 ) . metabolic syndrome has been defined in several ways that involve quantitative anthropometric , clinical , and laboratory measurements ( 1,2 ) . for the primary assessment , we chose ncep atp iii ( 1 ) criteria , since these criteria were used in most of the previously reported studies ( 8,9,1113,17 ) .\"\"\"\r\n\r\nmodel_name = 'google/pegasus-pubmed'\r\ntorch_device = 'cuda' if torch.cuda.is_available() else 'cpu'\r\ntokenizer = PegasusTokenizer.from_pretrained(model_name)\r\nmodel = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)\r\n\r\nbatch = tokenizer.prepare_seq2seq_batch([src_text], truncation=True, padding='longest').to(torch_device)\r\ntranslated = model.generate(**batch)\r\ntgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)\r\nprint(tgt_text)\r\n```\r\n\r\n## Expected behaviour\r\nI expect a summary of the input but i received a longer (relative to the input) version of the text, input has length of 929 vs 1129 of predicted summary.\r\nIn particular Pegasus generate new knowledge (bold text) which isn't inside the input text.\r\n\r\nInput:\r\n\r\nalthough the association is modest , it is important because of the increasing prevalence of metabolic syndrome and the effect that depression can have on the ability of patients to successfully make lifestyle changes and comply with medication required for hypertension and dyslipidemia . the association is demonstrated here in a general population to our knowledge for the first time , whereas earlier studies ( table 1 ) used subgroups of populations ( 813,17 ) . this distinction is important because many individuals with metabolic syndrome have diabetes , which itself is known to be associated with depression ( 5 ) . metabolic syndrome has been defined in several ways that involve quantitative anthropometric , clinical , and laboratory measurements ( 1,2 ) . for the primary assessment , we chose ncep atp iii ( 1 ) criteria , since these criteria were used in most of the previously reported studies ( 8,9,1113,17 ) .\r\n\r\nOutput:\r\n\r\n['depression is known to be associated with metabolic syndrome, but its association with metabolic syndrome has not been studied in a general population. <n> we examined the association between depression and metabolic syndrome using ncep atp iii criteria in a population - based sample ( n = 3,018 ). <n> **metabolic syndrome was defined as having three or more of the following : body mass index 25 kg / m2, waist circumference 90 cm, and triglyceride 130 mg / dl.** <n> **depression was assessed using the center for epidemiologic studies depression scale ( cesds ).** <n> **multivariate logistic regression was used to estimate odds ratios ( ors ) and 95% confidence intervals ( cis ) for the association between depression and metabolic syndrome.** <n> we found a significant association between depression and metabolic syndrome in a general population. <n> **after adjustment for age, sex, race / ethnicity, education, smoking, physical activity, alcohol intake, and body mass index, metabolic syndrome was associated with increased odds of depression ( or = 1.16, 95% ci 1.041.32 ).** <n> **the association was stronger in women than in men.**']\r\n\r\nIs that behaviour correct?", "Output should be < 256 tokens (not characters).\r\nInput should probably be longer (closer to 1024 tokens).\r\nTry copying something from the leftmost column of the [dataset](https://huggingface.co/nlp/viewer/?dataset=scientific_papers&config=pubmed)", "We've now replicated that our pegasus port performs similarly well to the authors implementation on 11 datasets, including arxiv.\r\n\r\n\r\n\r\n\r\n[Link to Spreadsheet](\r\nhttps://docs.google.com/spreadsheets/d/1ODfoK-tXOV6TLXDMnujdGLtFhA8oVTy-Cv6Ib6qKgWk/edit#gid=0)", "\r\n\r\nhttps://docs.google.com/spreadsheets/d/1ODfoK-tXOV6TLXDMnujdGLtFhA8oVTy-Cv6Ib6qKgWk/edit#gid=0" ]

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[ "Pinging the summarization expert here @sshleifer ", "Can we move [here](https://discuss.huggingface.co/t/summarization-on-long-documents/920/5)\r\n\r\nI am super happy to help, but want to help everybody at the same time. @ibeltagy is working hard on summarizing longer docs, but besides his efforts we don't have what you are looking for.", "Thank you for posting, I will have a look at it." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=h1) Report\n> Merging [#7161](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/85ffda96fcadf70d2558ba0a59c84b9f5a2d6f0f?el=desc) will **increase** coverage by `2.43%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7161 +/- ##\n==========================================\n+ Coverage 78.44% 80.88% +2.43% \n==========================================\n Files 168 168 \n Lines 32309 32309 \n==========================================\n+ Hits 25346 26134 +788 \n+ Misses 6963 6175 -788 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `93.54% <100.00%> (+0.35%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mdW5uZWwucHk=) | `18.53% <0.00%> (-75.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9ucy5weQ==) | `85.00% <0.00%> (-5.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `93.93% <0.00%> (-0.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.38% <0.00%> (-0.36%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.64% <0.00%> (-0.28%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.44% <0.00%> (+0.16%)` | :arrow_up: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.20% <0.00%> (+0.27%)` | :arrow_up: |\n| ... and [7 more](https://codecov.io/gh/huggingface/transformers/pull/7161/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=footer). Last update [b00cafb...021caf3](https://codecov.io/gh/huggingface/transformers/pull/7161?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks, @LysandreJik!" ]

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[ "Hey @xixiaoyao,\r\n\r\nCould you please copy paste the command you used to run squad so that I can be 100% sure we are running the same command? How did you enable `gradient_checkpointing` ? Did you change the `run_squad.py` script? \r\n\r\nWould be great if you can copy-paste a runnable code snippet here :-) ", "Getting the same issue when using Reformer with pytorch-lightning's distributeddataparallel, although not using one of the official training scripts.", "I am also getting this exact same error with Reformer, but only when I wrap it with DDP and then train across multiple GPUs on the same box. I do not get this error with Longformer. If I don't use DDP with Reformer, then it works fine. Am doing vanilla AR language model training using a custom script. But my script works fine when used on a single GPU with no DDP. The error seems to indicate that there's something about Reformer which DDP does not yet support:\r\n\r\n\"RuntimeError: Expected to mark a variable ready only once. This error is caused by one of the following reasons: 1) Use of a module parameter outside the `forward` function. Please make sure model parameters are not shared across multiple concurrent forward-backward passes2) Reused parameters in multiple reentrant backward passes. For example, if you use multiple `checkpoint` functions to wrap the same part of your model, it would result in the same set of parameters been used by different reentrant backward passes multiple times, and hence marking a variable ready multiple times. DDP does not support such use cases yet.\"\r\n\r\nAm using transformers 3.5.1.", "> I am also getting this exact same error with Reformer, but only when I wrap it with DDP and then train across multiple GPUs on the same box. I do not get this error with Longformer. If I don't use DDP with Reformer, then it works fine. Am doing vanilla AR language model training using a custom script. But my script works fine when used on a single GPU with no DDP. The error seems to indicate that there's something about Reformer which DDP does not yet support:\r\n> \r\n> \"RuntimeError: Expected to mark a variable ready only once. This error is caused by one of the following reasons: 1) Use of a module parameter outside the `forward` function. Please make sure model parameters are not shared across multiple concurrent forward-backward passes2) Reused parameters in multiple reentrant backward passes. For example, if you use multiple `checkpoint` functions to wrap the same part of your model, it would result in the same set of parameters been used by different reentrant backward passes multiple times, and hence marking a variable ready multiple times. DDP does not support such use cases yet.\"\r\n> \r\n> Am using transformers 3.5.1.\r\n\r\nsame with @trias702 ", "This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread.", "> > I am also getting this exact same error with Reformer, but only when I wrap it with DDP and then train across multiple GPUs on the same box. I do not get this error with Longformer. If I don't use DDP with Reformer, then it works fine. Am doing vanilla AR language model training using a custom script. But my script works fine when used on a single GPU with no DDP. The error seems to indicate that there's something about Reformer which DDP does not yet support:\r\n> > \"RuntimeError: Expected to mark a variable ready only once. This error is caused by one of the following reasons: 1) Use of a module parameter outside the `forward` function. Please make sure model parameters are not shared across multiple concurrent forward-backward passes2) Reused parameters in multiple reentrant backward passes. For example, if you use multiple `checkpoint` functions to wrap the same part of your model, it would result in the same set of parameters been used by different reentrant backward passes multiple times, and hence marking a variable ready multiple times. DDP does not support such use cases yet.\"\r\n> > Am using transformers 3.5.1.\r\n> \r\n> same with @trias702\r\n\r\nsame with @trias702 @yuanenming \r\nany updates? @xixiaoyao " ]

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[ "Hey @xixiaoyao, the main gain is memory savings for longformer - so I'm not really surprised if you say that training speed does not change when halving the attention window...", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

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[ "We know there is a limitation on the size of dataset for evaluation/prediction because every tensors are concatenated together (this is necessary for distributed training). We plan to work on it using the work done in the `datasets` library to have the predictions cached in temporary files as the prediction loop go. However this is not going to be ready before a few weeks, so in the meantime, I encourage you to feed your dataset to predictions by small slices.", "Okay, thank you. \r\n\r\nCurrently i'm only debugging on my machine so the:\r\n` if logits is not None: preds = logits.argmax(-1) if preds is None else torch.cat((preds, logits.argmax(-1)), dim=0)`\r\n-hack does it for me. But yeah as soon as I train on multiple machines I will feed it in small slices.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "> We know there is a limitation on the size of dataset for evaluation/prediction because every tensors are concatenated together (this is necessary for distributed training). We plan to work on it using the work done in the `datasets` library to have the predictions cached in temporary files as the prediction loop go. However this is not going to be ready before a few weeks, so in the meantime, I encourage you to feed your dataset to predictions by small slices.\r\n\r\nHi, has this problem been solved :)" ]

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[ "I opened a wrong PR yesterday, please help me check this version, thanks!\r\n@JetRunner @patrickvonplaten ", "@qiweizhen - this looks great! Is this the complete PR? Can we close the \"old\" PR: https://github.com/huggingface/transformers/pull/6187 in favor of this one? ", "@qiweizhen the Integration tests look great! @JetRunner, I think we can take it from here :-) \r\n\r\nI saw that there are models, such \"xprophetnet-large-wiki100-cased-xglue-ntg\" that are both under microsoft and under weizhen - @qiweizhen are these models identical? ", "This PR is complete version, as I rebased this branch to the latest huggingface version with directions of @JetRunner .\r\n\r\nModels under Microsoft are what we actually used. Those under qiweizhen were used to debug. I will delete the models under qiweizhen.\r\n\r\nThank you for your helps @patrickvonplaten @JetRunner ", "> This PR is complete version, as I rebased this branch to the latest huggingface version with directions of @JetRunner .\r\n> \r\n> Models under Microsoft are what we actually used. Those under qiweizhen were used to debug. I will delete the models under qiweizhen.\r\n> \r\n> Thank you for your helps @patrickvonplaten @JetRunner\r\n\r\nAwesome! Thanks a million for your work! We will take it from here :-) ", "@patrickvonplaten Hi, may I ask when could ProphetNet be added into Transformers? Are there any jobs I can co-work to help it be integrated?", "Hey @qiweizhen ,\r\n\r\nSorry for the delay on this. Prophetnet is my no 1 priority next week. It should be merged by the end of next week. You have done your part - I might ping you for some further questions", "@qiweizhen - the integration tests are awesome! Thanks to that it should be quite straightforward to integrate the model", "@qiweizhen - would it be ok for you if we add a `ProphetNetModel` and a `XLMProphetNetModel`, each with their respective tokenizers. I think this would be cleaner and is also more in line with `Roberta` and `XLMRoberta` for example. I should be quite easy to do this. I can take care of it - would just be great to have your approval on it :-) ", "> @qiweizhen - would it be ok for you if we add a `ProphetNetModel` and a `XLMProphetNetModel`, each with their respective tokenizers. I think this would be cleaner and is also more in line with `Roberta` and `XLMRoberta` for example. I should be quite easy to do this. I can take care of it - would just be great to have your approval on it :-)\r\n\r\nSure! Thank you!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=h1) Report\n> Merging [#7156](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/85ffda96fcadf70d2558ba0a59c84b9f5a2d6f0f?el=desc) will **increase** coverage by `0.97%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #7156 +/- ##\n==========================================\n+ Coverage 78.44% 79.42% +0.97% \n==========================================\n Files 168 168 \n Lines 32309 32309 \n==========================================\n+ Hits 25346 25662 +316 \n+ Misses 6963 6647 -316 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [...c/transformers/modeling\\_tf\\_transfo\\_xl\\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsX3V0aWxpdGllcy5weQ==) | `10.00% <0.00%> (-76.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `21.12% <0.00%> (-71.05%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90cmFuc2ZvX3hsLnB5) | `19.85% <0.00%> (-68.29%)` | :arrow_down: |\n| [src/transformers/modeling\\_lxmert.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19seG1lcnQucHk=) | `70.01% <0.00%> (-20.75%)` | :arrow_down: |\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `79.21% <0.00%> (-10.25%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `80.70% <0.00%> (-5.77%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.68% <0.00%> (-0.65%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.84% <0.00%> (-0.25%)` | :arrow_down: |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.44% <0.00%> (+0.16%)` | :arrow_up: |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `92.04% <0.00%> (+20.43%)` | :arrow_up: |\n| ... and [4 more](https://codecov.io/gh/huggingface/transformers/pull/7156/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=footer). Last update [b00cafb...b347e1c](https://codecov.io/gh/huggingface/transformers/pull/7156?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]