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DanielPFlorian

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Transformers-Github-Issues

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=h1) Report\n> Merging [#4920](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5d63ca6c38cc0f583cdec4c3efcfce13c0a41fdc&el=desc) will **decrease** coverage by `0.04%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4920 +/- ##\n==========================================\n- Coverage 77.10% 77.05% -0.05% \n==========================================\n Files 128 128 \n Lines 21617 21618 +1 \n==========================================\n- Hits 16667 16657 -10 \n- Misses 4950 4961 +11 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/4920/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `95.16% <100.00%> (+0.89%)` | :arrow_up: |\n| [src/transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/4920/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG5ldC5weQ==) | `76.31% <0.00%> (-2.31%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4920/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4920?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/4920?src=pr&el=footer). Last update [5d63ca6...05e5aa7](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Very clean. LGTM!" ]

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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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[ "Thanks! The model checkpoints are available actually. [Check here](https://github.com/google-research/pegasus#install-library-and-dependencies) :)", "Hope to provide a pytorch version code ", "I might try the Huggingface's weight transfer code from tensorflow to pytorch in July if nobody's working on this post ", "Work has started on this, but we are still a few weeks out. ", "Just wanted to know when this model will be available", "We're a little behind schedule. I'd say 60% by August 1, 90% by Sept 1.", "this is awesome.", "Very cool! Can it also be evaluated with Bert-Score?", "Can't wait for this... ", "Converted torch checkpoints are now available on master if you build from source.\r\n[Here](https://huggingface.co/models?search=pegasus) is a list of available checkpoints.\r\nPR: #6340 \r\n\r\nUsage:\r\n\r\n```python\r\nfrom transformers import PegasusForConditionalGeneration, PegasusTokenizer\r\nsrc_text = [\r\n \"\"\" PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.\"\"\"\r\n]\r\n\r\nmodel_name = 'google/pegasus-xsum'\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\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\nassert tgt_text[0] == \"California's largest electricity provider has turned off power to tens of thousands of customers.\"\r\n```\r\n\r\nPlease make a **new issue** if you encounter a bug with the torch checkpoints and assign @sshleifer .\r\nFor conceptual/how to questions, ask on discuss.huggingface.co, (you can also tag @sshleifer. )\r\n\r\nStill TODO:\r\n- Tensorflow 2.0 implementation.\r\n- ROUGE score is slightly worse than the original paper because we don't implement length penalty the same way. If anyone wants to try it, see #6420 .\r\n- fp16 doesn't work for generation or finetuning\r\n- I have not tried finetuning yet, no guarantees on that working well or replicating the paper.", "I assume these checkpoints are based on Mixed & Stochastic models, as opposed to models trained exclusively on either C4 or HugeNews?", "Yes!", "@sshleifer I am trying this code on Colab but running into below error. Can you let me know what is the issue?\r\n\r\n`ImportError: cannot import name 'PegasusForConditionalGeneration'`", "I'm having the same issue as @chetanambi \r\n", "I think you need to install from source, it's not part of the latest release. (will be in the next release).", "@sshleifer :\r\n\r\nfor the following model:\r\nmodel_name = 'google/pegasus-cnn_dailymail';\r\n\r\nI encountered this error when running:\r\n`translated = model.generate(**batch)`\r\n'---------------------------------------------------------------------------\r\nIndexError Traceback (most recent call last)\r\n<ipython-input-42-635894de22cc> in <module>\r\n 1 batch = tokenizer.prepare_seq2seq_batch(src_text, truncation=True, padding='longest').to(torch_device)\r\n----> 2 translated = model.generate(**batch)\r\n 3 tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)\r\n 13 def decorate_context(*args, **kwargs):\r\n 14 with self:\r\n---> 15 return func(*args, **kwargs)\r\n 16 return decorate_context\r\n 17 \r\n\r\n~/projects/transformers/src/transformers/generation_utils.py in generate(self, input_ids, max_length, min_length, do_sample, early_stopping, num_beams, temperature, top_k, top_p, repetition_penalty, bad_words_ids, bos_token_id, pad_token_id, eos_token_id, length_penalty, no_repeat_ngram_size, num_return_sequences, attention_mask, decoder_start_token_id, use_cache, **model_specific_kwargs)\r\n 394 encoder = self.get_encoder()\r\n 395 \r\n--> 396 encoder_outputs: tuple = encoder(input_ids, attention_mask=attention_mask)\r\n 397 \r\n 398 # Expand input ids if num_beams > 1 or num_return_sequences > 1\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)\r\n 720 result = self._slow_forward(*input, **kwargs)\r\n 721 else:\r\n--> 722 result = self.forward(*input, **kwargs)\r\n 723 for hook in itertools.chain(\r\n 724 _global_forward_hooks.values(),\r\n\r\n~/projects/transformers/src/transformers/modeling_bart.py in forward(self, input_ids, attention_mask, output_attentions, output_hidden_states, return_dict)\r\n 328 \r\n 329 inputs_embeds = self.embed_tokens(input_ids) * self.embed_scale\r\n--> 330 embed_pos = self.embed_positions(input_ids)\r\n 331 x = inputs_embeds + embed_pos\r\n 332 x = self.layernorm_embedding(x)\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)\r\n 720 result = self._slow_forward(*input, **kwargs)\r\n 721 else:\r\n--> 722 result = self.forward(*input, **kwargs)\r\n 723 for hook in itertools.chain(\r\n 724 _global_forward_hooks.values(),\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)\r\n 13 def decorate_context(*args, **kwargs):\r\n 14 with self:\r\n---> 15 return func(*args, **kwargs)\r\n 16 return decorate_context\r\n 17 \r\n\r\n~/projects/transformers/src/transformers/modeling_bart.py in forward(self, input_ids, use_cache)\r\n 1337 # starts at 0, ends at 1-seq_len\r\n 1338 positions = torch.arange(seq_len, dtype=torch.long, device=self.weight.device)\r\n-> 1339 return super().forward(positions)\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/nn/modules/sparse.py in forward(self, input)\r\n 122 \r\n 123 def forward(self, input: Tensor) -> Tensor:\r\n--> 124 return F.embedding(\r\n 125 input, self.weight, self.padding_idx, self.max_norm,\r\n 126 self.norm_type, self.scale_grad_by_freq, self.sparse)\r\n\r\n~/anaconda3/envs/abstractive_summarizer/lib/python3.8/site-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)\r\n 1812 # remove once script supports set_grad_enabled\r\n 1813 _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)\r\n-> 1814 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)\r\n 1815 \r\n 1816 \r\n\r\nIndexError: index out of range in self'", "@yxyzzz can you make a new issue and follow the bug-report template. I can't reproduce based on what you've provided. Thanks!", "> I think you need to install from source, it's not part of the latest release. (will be in the next release).\r\n\r\nCould you please let me know how to do this. Thanks!!", "@chetanambi The instructions are provided [here](https://github.com/huggingface/transformers#from-source)", "@sshleifer\r\nI installed transformers from the source using the current `master` branch. \r\n\r\n```\r\nI experience the following issue. \r\n\r\n>>> from transformers import PegasusForConditionalGeneration, PegasusTokenizer\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/ubuntu/env5/lib/python3.6/site-packages/transformers/__init__.py\", line 21, in <module>\r\n from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig\r\n File \"/home/ubuntu/env5/lib/python3.6/site-packages/transformers/configuration_albert.py\", line 18, in <module>\r\n from .configuration_utils import PretrainedConfig\r\n File \"/home/ubuntu/env5/lib/python3.6/site-packages/transformers/configuration_utils.py\", line 24, in <module>\r\n from .file_utils import CONFIG_NAME, cached_path, hf_bucket_url, is_remote_url\r\n File \"/home/ubuntu/env5/lib/python3.6/site-packages/transformers/file_utils.py\", line 32, in <module>\r\n from .utils import logging\r\nModuleNotFoundError: No module named 'transformers.utils'\r\n```\r\n\r\n**question** It is the problem with the current `master`. How many commits do I need to rollback to sucsessuly run PEGASUS before September release? \r\n\r\nThank you in advance for the info!\r\n", "master fixed by #6754 .", "> master fixed by #6754 .\r\n\r\n@sshleifer \r\n\r\n**(1)** I confirm that `master` is working now. So I was able to successfully run PEGASUS.\r\n\r\n**(2)** Is there any way to control a length of a resulting summary made by PEGASUS? I would like to generate longer summaries.", "> **(2)** Is there any way to control a length of a resulting summary made by PEGASUS? I would like to generate longer summaries.\r\n\r\n@andrei-volkau \r\n\r\nYou can (1) fine-tune PEGASUS on a customised dataset which has longer summaries (2) tune the hyper-parameter `beam_alpha` which can lead to slightly longer/shorter summaries.\r\n", "`beam_alpha` is called \"length penalty\" in this repo.\r\n\r\nBe that `length_penalty` is named confusingly: (#4915)\r\n\r\n- Increasing `length_penalty` will result in longer generations. \r\n- Decreasing `length_penalty` will result in shorter generations.\r\n- the formula differs slightly from the pegasus paper (#6420)", "Is there a short finetuning example somewhere?", "Nothing short. Finetuning with `examples/seq2seq/finetune.py` https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune_pegasus_xsum.sh is almost ready (will be ready after #6654). To use that you should read the README.MD which covers how to format your data.", "> @chetanambi The instructions are provided [here](https://github.com/huggingface/transformers#from-source)\r\n\r\nI was able to run the models successfully. During the summarization I would like to run with different beam size. How can I do this?\r\n\r\nThanks!!", "Interesting, when I ran the example in the documentation (copied below). \r\n\r\nI got the output: `California's largest electricity provider has turned off power to hundreds of thousands of customers.`\r\n\r\nWhereas the assertion output was: `California's largest electricity provider has turned off power to tens of thousands of customers.`\r\n\r\nCould someone shine a light on why this might be the case and which one is the 'correct' output? I'm certain I didn't change anything. \r\n\r\n```\r\nfrom transformers import PegasusForConditionalGeneration, PegasusTokenizer\r\nimport torch\r\nsrc_text = [\r\n \"\"\" PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.\"\"\"\r\n]\r\n\r\nmodel_name = 'google/pegasus-xsum'\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\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\nassert tgt_text[0] == \"California's largest electricity provider has turned off power to tens of thousands of customers.\"\r\n```\r\n\r\n", "The docs are wrong, the code is right:\r\n#6526 (merged since documentation was written) affected output (in a good way).\r\n**Update**: I fixed the docs.", "@sshleifer I am trying to implement this in a machine that is not connected to internet. So, I will have to download the model (ex: reddit-tifu) and pass the location to from_pretrained. Could you please suggest what all the files I need to download. Apperciate your help. \r\n\r\n```\r\nfrom transformers import AutoTokenizer, AutoModelWithLMHead\r\ntokenizer = AutoTokenizer.from_pretrained(\"google/pegasus-reddit_tifu\")\r\nmodel = AutoModelWithLMHead.from_pretrained(\"google/pegasus-reddit_tifu\")\r\n```" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=h1) Report\n> Merging [#4917](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef2dcdccaa9a115aca44d81f31c6dc4d32bebb3f&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4917 +/- ##\n=======================================\n Coverage 77.12% 77.13% \n=======================================\n Files 128 128 \n Lines 21650 21650 \n=======================================\n+ Hits 16698 16700 +2 \n+ Misses 4952 4950 -2 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4917/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.09% <0.00%> (-0.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4917/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.61% <0.00%> (+0.11%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4917/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.57% <0.00%> (+0.31%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4917?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/4917?src=pr&el=footer). Last update [ef2dcdc...74e1e66](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "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/4916?src=pr&el=h1) Report\n> Merging [#4916](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef2dcdccaa9a115aca44d81f31c6dc4d32bebb3f&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4916 +/- ##\n=======================================\n Coverage 77.12% 77.13% \n=======================================\n Files 128 128 \n Lines 21650 21649 -1 \n=======================================\n+ Hits 16698 16699 +1 \n+ Misses 4952 4950 -2 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4916/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `74.19% <100.00%> (+0.69%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4916?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/4916?src=pr&el=footer). Last update [ef2dcdc...acb4cb4](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Oh, my bad! Not sure why I left it there", "No worries!" ]

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[ "Yes, I remember being confused about the name earlier as well...I would be in favor of keeping the code and renaming the variable, but I can't think of a good variable name (not a huge fan of `len_adjustment`, but can't really think of a better name - maybe `length_reward`?) ", "Sorry just catching up :) \r\n\r\nI'd go for changing the name, but `length_reward` feels a little too connoted (makes me think of RL)\r\n\r\nHow about `length_normalization`?", "I'm good with that. \r\nI propose:\r\n- rename the parameter from `length_penalty`-> `length_normalization_alpha`\r\n- if the user **OR** the config passes length_penalty, raise a `DeprecationWarning`.\r\n- Slowly update configs \r\n\r\nThis would eventually be a (very minor) breaking change @LysandreJik @thomwolf @julien-c .\r\n", "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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[ "requires unigram algo implemented on tokenizers\r\nhttps://github.com/huggingface/tokenizers/pull/292", "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", "PR merged, closing the issue", "Hi @pommedeterresautee, could you please refer me to how I can convert an existing Python tokenizer to a Fast tokenizer?\r\n\r\nSorry if I missed something, and thanks so much for your help!", "Maybe @SaulLu or @Narsil can comment and link to an example!", "Hi @varun-tandon ,\r\n\r\nThe code to change from slow to fast is included here: https://github.com/huggingface/transformers/blob/main/src/transformers/convert_slow_tokenizer.py\r\n\r\nAs you can see there are many variables, depending on the actual model and what you want to achieve.\r\n\r\nUsually it involves understanding how a model actually does the tokenization (and all the bits like CLS, SEP etc..) and using the compponents of `tokenizers` to assemble them to make the output similar to what the python code does:\r\nhttps://huggingface.co/docs/tokenizers/components\r\n\r\nSometimes we're missing a brick and we simply add it (although it becomes rarer with time)\r\n" ]

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[ "Great, thanks for your help! \r\nCould you also add the new model to [`all_model_classes`](https://github.com/huggingface/transformers/blob/master/tests/test_modeling_electra.py#L41) which would test the model a little bit more?", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=h1) Report\n> Merging [#4913](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5d63ca6c38cc0f583cdec4c3efcfce13c0a41fdc&el=desc) will **increase** coverage by `0.03%`.\n> The diff coverage is `93.93%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4913 +/- ##\n==========================================\n+ Coverage 77.10% 77.13% +0.03% \n==========================================\n Files 128 128 \n Lines 21617 21650 +33 \n==========================================\n+ Hits 16667 16699 +32 \n- Misses 4950 4951 +1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.13% <ø> (ø)` | |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `78.40% <ø> (ø)` | |\n| [src/transformers/modeling\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbGVjdHJhLnB5) | `78.16% <93.93%> (+2.07%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (+0.15%)` | :arrow_up: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4913/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.49% <0.00%> (+0.40%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4913?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/4913?src=pr&el=footer). Last update [5d63ca6...d8a5995](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "> Great, thanks for your help!\r\n> Could you also add the new model to [`all_model_classes`](https://github.com/huggingface/transformers/blob/master/tests/test_modeling_electra.py#L41) which would test the model a little bit more?\r\n\r\nSure", "Oh and before I forget, if you don't mind, could you add the new model in the docs as well in [this file](https://github.com/huggingface/transformers/blob/master/docs/source/model_doc/electra.rst) (between `ElectraForTokenClassification` and `TFElectraModel` ideally).", "@sgugger \r\nsome tests are failing, but I'm not sure if they are related to this model\r\n\r\nThe test for this qa model is passed.", "The failing tests are the test common for all models (that are applied to the one you're adding because of the change I made you do). One of the failure I see is linked to the `input_ids` not defaulting to `None` (for when you pass input embeddings instead). There is another one linked to the attentions, I pointed out the problems in comments.", "> The failing tests are the test common for all models (that are applied to the one you're adding because of the change I made you do). One of the failure I see is linked to the `input_ids` not defaulting to `None` (for when you pass input embeddings instead). There is another one linked to the attentions, I pointed out the problems in comments.\r\n\r\nThanks @sgugger !\r\nThe tests are happy now :)", "@sgugger this examples failure is related to `TestBartExamples.test_bart_summarization_dataset `", "Cool! All green 🤗" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=h1) Report\n> Merging [#4912](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **decrease** coverage by `0.94%`.\n> The diff coverage is `78.29%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4912 +/- ##\n==========================================\n- Coverage 77.28% 76.34% -0.95% \n==========================================\n Files 133 134 +1 \n Lines 22134 22369 +235 \n==========================================\n- Hits 17107 17078 -29 \n- Misses 5027 5291 +264 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/benchmark/benchmark\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX3V0aWxzLnB5) | `69.77% <68.51%> (-3.20%)` | :arrow_down: |\n| [src/transformers/benchmark/benchmark\\_args\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX2FyZ3NfdXRpbHMucHk=) | `89.13% <71.42%> (-7.75%)` | :arrow_down: |\n| [src/transformers/benchmark/benchmark.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrLnB5) | `79.13% <76.00%> (+9.70%)` | :arrow_up: |\n| [src/transformers/benchmark/benchmark\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX3RmLnB5) | `82.69% <82.69%> (ø)` | |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `76.80% <86.66%> (+1.40%)` | :arrow_up: |\n| [src/transformers/benchmark/benchmark\\_args\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX2FyZ3NfdGYucHk=) | `87.50% <87.50%> (ø)` | |\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.18% <100.00%> (+0.02%)` | :arrow_up: |\n| [src/transformers/benchmark/benchmark\\_args.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX2FyZ3MucHk=) | `86.04% <100.00%> (+0.68%)` | :arrow_up: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.57% <100.00%> (+0.18%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl90NS5weQ==) | `50.10% <0.00%> (-43.61%)` | :arrow_down: |\n| ... and [7 more](https://codecov.io/gh/huggingface/transformers/pull/4912/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4912?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/4912?src=pr&el=footer). Last update [355954f...8b71041](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "> This is great. I really like that you can import the benchmark if you want to use them during runtime, rather than the only option being to run a script.\r\n> \r\n> Some remarks after playing with it:\r\n> \r\n> * Maybe you should raise an error when no `model_names` are specified. Right now it crashes with `UnboundLocalError: local variable 'inference_summary' referenced before assignment` (pytorch version at least)\r\n> * There seems to be an error in the way the runtimes are computed. PyTorch using GPU, is slower than TensorFlow on CPU (10x times slower), while PyTorch on CPU is 150x slower than TensorFlow on CPU.\r\n> \r\n> Here are the results from my runs so far. The following is on CPU with TensorFlow (2ms per inference with `bert-base-cased`, seq len 8 and batch size 512 on a CPU??) I didn't test the memory usage so they're not in the results:\r\n> \r\n> ```\r\n> ==================== INFERENCE - SPEED - RESULT ====================\r\n> --------------------------------------------------------------------------------\r\n> Model Name Batch Size Seq Length Time in s \r\n> --------------------------------------------------------------------------------\r\n> bert-base-cased 8 8 0.001 \r\n> bert-base-cased 8 32 0.001 \r\n> bert-base-cased 8 128 0.001 \r\n> bert-base-cased 8 512 0.002 \r\n> --------------------------------------------------------------------------------\r\n> \r\n> ==================== ENVIRONMENT INFORMATION ====================\r\n> - transformers_version: 2.11.0\r\n> - framework: Tensorflow\r\n> - eager_mode: False\r\n> - use_xla: False\r\n> - framework_version: 2.2.0\r\n> - python_version: 3.6.10\r\n> - system: Linux\r\n> - cpu: \r\n> - architecture: 64bit\r\n> - date: 2020-06-18\r\n> - time: 11:57:18.595804\r\n> - fp16: False\r\n> - use_multiprocessing: True\r\n> - cpu_ram_mb: 64333\r\n> - use_gpu: False\r\n> - use_tpu: False\r\n> ```\r\n> \r\n> Here's the test with PyTorch on GPU:\r\n> \r\n> ```\r\n> ==================== INFERENCE - SPEED - RESULT ====================\r\n> --------------------------------------------------------------------------------\r\n> Model Name Batch Size Seq Length Time in s \r\n> --------------------------------------------------------------------------------\r\n> bert-base-cased 8 8 0.007 \r\n> bert-base-cased 8 32 0.007 \r\n> bert-base-cased 8 128 0.019 \r\n> bert-base-cased 8 512 0.074 \r\n> --------------------------------------------------------------------------------\r\n> \r\n> ==================== ENVIRONMENT INFORMATION ====================\r\n> - transformers_version: 2.11.0\r\n> - framework: PyTorch\r\n> - use_torchscript: False\r\n> - framework_version: 1.5.0\r\n> - python_version: 3.6.10\r\n> - system: Linux\r\n> - cpu: \r\n> - architecture: 64bit\r\n> - date: 2020-06-18\r\n> - time: 11:56:31.041360\r\n> - fp16: False\r\n> - use_multiprocessing: True\r\n> - cpu_ram_mb: 64333\r\n> - use_gpu: True\r\n> - num_gpus: 1\r\n> - gpu: N/A\r\n> - gpu_ram_mb: N/A\r\n> - gpu_power_watts: N/A\r\n> - gpu_performance_state: N/A\r\n> - use_tpu: False\r\n> ```\r\n> \r\n> I'm not sure that PyTorch on GPU is ~37x slower than TensorFlow on CPU I tried to debug but it's not easy to debug tf functions unfortunately\r\n\r\nThanks a lot for checking everything! Found the error :-) One just has to return a tensor out of the tf.function context so that it is actually computed. I guess before compilation TF compilation optimizes the function so that variables that are not used outside of the @tf.function scope are not computed.\r\n\r\nWill update the notebooks and should then getter more reasonable results :-) ", "And will definitely add a better error message", "The speed tests seem much more reasonable now, if you check the notebooks :-) @LysandreJik \r\nThere seems to be a problem with GPU memory in TF now :-/ Will check tomorrow again", "## GPU locally gives reasonable results of TF vs. PT.\r\n\r\nAll tests were run in this environment:\r\n\r\n```\r\n- transformers_version: 2.11.0\r\n- python_version: 3.6.10\r\n- system: Linux\r\n- cpu: x86_64\r\n- architecture: 64bit\r\n- date: 2020-06-19\r\n- time: 13:49:57.455208\r\n- use_multiprocessing: True\r\n- cpu_ram_mb: 32088\r\n- use_gpu: True\r\n- num_gpus: 1\r\n- gpu: TITAN RTX\r\n- gpu_ram_mb: 24217\r\n- gpu_power_watts: 280.0\r\n- gpu_performance_state: 2\r\n```\r\n\r\nfor TF 2.2 and Pytorch 1.4.0\r\n\r\n### PyTorch\r\n`python run_benchmark.py --models gpt2 bert-base-cased --no_env_print --no_memory` gives:\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\n gpt2 8 8 0.006 \r\n gpt2 8 32 0.007 \r\n gpt2 8 128 0.026 \r\n gpt2 8 512 0.104 \r\n bert-base-cased 8 8 0.006 \r\n bert-base-cased 8 32 0.006 \r\n bert-base-cased 8 128 0.021 \r\n bert-base-cased 8 512 0.094 \r\n--------------------------------------------------------------------------------\r\n\r\n", "### PyTorch FP16\r\n`python run_benchmark.py --models gpt2 bert-base-cased --no_env_print --no_memory --fp16`\r\n\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\n gpt2 8 8 0.006 \r\n gpt2 8 32 0.007 \r\n gpt2 8 128 0.009 \r\n gpt2 8 512 0.043 \r\n bert-base-cased 8 8 0.006 \r\n bert-base-cased 8 32 0.006 \r\n bert-base-cased 8 128 0.006 \r\n bert-base-cased 8 512 0.03 ", "### TF no eager modus\r\n\r\n```python run_benchmark_tf.py --models gpt2 bert-base-cased --no_env_print --no_memory```\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\n gpt2 8 8 0.005 \r\n gpt2 8 32 0.007 \r\n gpt2 8 128 0.029 \r\n gpt2 8 512 0.125 \r\n bert-base-cased 8 8 0.005 \r\n bert-base-cased 8 32 0.006 \r\n bert-base-cased 8 128 0.024 \r\n bert-base-cased 8 512 0.114 \r\n--------------------------------------------------------------------------------", "### TF XLA\r\n\r\n```python run_benchmark_tf.py --models gpt2 bert-base-cased --no_env_print --no_memory --use_xla```\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\n gpt2 8 8 0.002 \r\n gpt2 8 32 0.006 \r\n gpt2 8 128 0.021 \r\n gpt2 8 512 0.095 \r\n bert-base-cased 8 8 0.003 \r\n bert-base-cased 8 32 0.005 \r\n bert-base-cased 8 128 0.019 \r\n bert-base-cased 8 512 0.087 \r\n--------------------------------------------------------------------------------\r\n", "## Memory measurements \r\n\r\nThey also seem reasonable for forward pass:.\r\n\r\n### TF no eager mode (keeping in mind that nvidia-smi is not accurate here and TF always allocates more than it needs):\r\n\r\n```python run_benchmark_tf.py --models gpt2 bert-base-cased --no_env_print --no_speed```\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Memory in MB \r\n--------------------------------------------------------------------------------\r\n gpt2 64 8 1704 \r\n gpt2 64 32 1704 \r\n gpt2 64 128 2728 \r\n gpt2 64 512 8872 \r\n bert-base-cased 64 8 1192 \r\n bert-base-cased 64 32 1192 \r\n bert-base-cased 64 128 1704 \r\n bert-base-cased 64 512 4776 \r\n--------------------------------------------------------------------------------\r\n\r\n### PyTorch \r\n\r\n```python run_benchmark.py --models gpt2 bert-base-cased --no_env_print --no_speed```\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Memory in MB \r\n--------------------------------------------------------------------------------\r\n gpt2 64 8 1150 \r\n gpt2 64 32 1384 \r\n gpt2 64 128 2290 \r\n gpt2 64 512 5890 \r\n bert-base-cased 64 8 1016 \r\n bert-base-cased 64 32 1104 \r\n bert-base-cased 64 128 1448 \r\n bert-base-cased 64 512 3224 \r\n--------------------------------------------------------------------------------\r\n\r\n### PyTorch FP16\r\n\r\n```python run_benchmark.py --models gpt2 bert-base-cased --no_env_print --no_speed --fp16```\r\n\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Memory in MB \r\n--------------------------------------------------------------------------------\r\n gpt2 64 8 1170 \r\n gpt2 64 32 1164 \r\n gpt2 64 128 1596 \r\n gpt2 64 512 3420 \r\n bert-base-cased 64 8 1066 \r\n bert-base-cased 64 32 1060 \r\n bert-base-cased 64 128 1108 \r\n bert-base-cased 64 512 2118 \r\n--------------------------------------------------------------------------------\r\n" ]

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[ "Hi! Why would you prefer using pickle rather than `save_pretrained`/`from_pretrained` or `torch.save`/`torch.save`?", "HI @LysandreJik, pickle is mainly useful for parallel processing frameworks like `joblib` or `dask`. The use case is to parallelize some (embarassingly parallel) computation on multiple CPUs/GPUs. Usually, they use pickled objects to send to workers.", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4911?src=pr&el=h1) Report\n> Merging [#4911](https://codecov.io/gh/huggingface/transformers/pull/4911?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4911?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4911 +/- ##\n=======================================\n Coverage 76.99% 77.00% \n=======================================\n Files 128 128 \n Lines 21602 21607 +5 \n=======================================\n+ Hits 16633 16639 +6 \n+ Misses 4969 4968 -1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4911?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.51% <100.00%> (+0.25%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.49% <0.00%> (+0.40%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4911?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/4911?src=pr&el=footer). Last update [ac99217...dd7120b](https://codecov.io/gh/huggingface/transformers/pull/4911?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "This is cool! Could we also add it to the PyTorch models?", "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/4910?src=pr&el=h1) Report\n> Merging [#4910](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase** coverage by `0.09%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4910 +/- ##\n==========================================\n+ Coverage 76.99% 77.08% +0.09% \n==========================================\n Files 128 128 \n Lines 21602 21604 +2 \n==========================================\n+ Hits 16633 16654 +21 \n+ Misses 4969 4950 -19 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kaXN0aWxiZXJ0LnB5) | `97.50% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbGVjdHJhLnB5) | `76.09% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `93.01% <100.00%> (+0.01%)` | :arrow_up: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.76% <100.00%> (+0.02%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (+0.15%)` | :arrow_up: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.49% <0.00%> (+0.40%)` | :arrow_up: |\n| [src/transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/4910/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG5ldC5weQ==) | `78.61% <0.00%> (+2.96%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4910?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/4910?src=pr&el=footer). Last update [ac99217...9e50a38](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "LGTM!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=h1) Report\n> Merging [#4909](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase** coverage by `0.40%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4909 +/- ##\n==========================================\n+ Coverage 76.99% 77.40% +0.40% \n==========================================\n Files 128 128 \n Lines 21602 21602 \n==========================================\n+ Hits 16633 16720 +87 \n+ Misses 4969 4882 -87 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.37% <ø> (ø)` | |\n| [src/transformers/modeling\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hbGJlcnQucHk=) | `76.22% <ø> (ø)` | |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `96.40% <ø> (ø)` | |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.28% <ø> (ø)` | |\n| [src/transformers/modeling\\_camembert.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19jYW1lbWJlcnQucHk=) | `100.00% <ø> (ø)` | |\n| [src/transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19jdHJsLnB5) | `98.63% <ø> (ø)` | |\n| [src/transformers/modeling\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kaXN0aWxiZXJ0LnB5) | `97.50% <ø> (ø)` | |\n| [src/transformers/modeling\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbGVjdHJhLnB5) | `76.09% <ø> (ø)` | |\n| [src/transformers/modeling\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19mbGF1YmVydC5weQ==) | `84.00% <ø> (ø)` | |\n| [src/transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19ncHQyLnB5) | `85.43% <ø> (ø)` | |\n| ... and [27 more](https://codecov.io/gh/huggingface/transformers/pull/4909/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4909?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/4909?src=pr&el=footer). Last update [ac99217...58379b0](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "This is great! Thanks @patrickvonplaten " ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=h1) Report\n> Merging [#4908](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase** coverage by `0.03%`.\n> The diff coverage is `94.11%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4908 +/- ##\n==========================================\n+ Coverage 76.99% 77.02% +0.03% \n==========================================\n Files 128 128 \n Lines 21602 21635 +33 \n==========================================\n+ Hits 16633 16665 +32 \n- Misses 4969 4970 +1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.13% <ø> (ø)` | |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `96.26% <93.93%> (-0.15%)` | :arrow_down: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `78.40% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (+0.15%)` | :arrow_up: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.49% <0.00%> (+0.40%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4908?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/4908?src=pr&el=footer). Last update [ac99217...63eb191](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks for the contribution @patil-suraj !", "> Hi! Very cool @patil-suraj.\r\n> \r\n> Could you also add `BartForQuestionAnswering` to the `all_model_classes` in `test_modeling_bart.py`?\r\n\r\nHi, @LysandreJik \r\nAfter adding `BartForQuestionAnswering` in `all_model_classes` I also had to add `output_attention` parameter to `forward`.\r\n\r\nNow for some reason `test_attention_outputs` is failing, I am not sure why, could you help me fix it ?\r\nThanks !", "Awesome work @patil-suraj - I can help you with this test :-) ", "I see what the problem is...it's actually not related to your PR at all. Can we you for now just remove `BartForQuestionAnswering` from the all_models tuples in the tests. @LysandreJik @sshleifer I will open a new PR after this one to fix it :-) ", "> I see what the problem is...it's actually not related to your PR at all. Can we you for now just remove `BartForQuestionAnswering` from the all_models tuples in the tests. @LysandreJik @sshleifer I will open a new PR after this one to fix it :-)\r\n\r\nThank you @patrickvonplaten . I've removed it from `all_models` tuple for now" ]

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[ "Hello! Is `sacremoses` installed in your environment? Do you mind pasting the result of `pip list` in your environment?", "Here you go:\r\n\r\n`Package Version \r\n---------------------- -----------\r\nabsl-py 0.9.0 \r\nastunparse 1.6.3 \r\nbeautifulsoup4 4.9.1 \r\nbs4 0.0.1 \r\ncachetools 4.1.0 \r\ncertifi 2020.4.5.1 \r\nchardet 3.0.4 \r\nclick 7.1.2 \r\nfilelock 3.0.12 \r\nfuture 0.18.2 \r\ngast 0.3.3 \r\ngoogle-auth 1.16.1 \r\ngoogle-auth-oauthlib 0.4.1 \r\ngoogle-pasta 0.2.0 \r\ngrpcio 1.29.0 \r\nh5py 2.10.0 \r\nidna 2.9 \r\njoblib 0.15.1 \r\nKeras-Preprocessing 1.1.2 \r\nMarkdown 3.2.2 \r\nnumpy 1.18.5 \r\noauthlib 3.1.0 \r\nopt-einsum 3.2.1 \r\npackaging 20.4 \r\nPillow 7.1.2 \r\npip 20.0.2 \r\nprotobuf 3.12.2 \r\npyasn1 0.4.8 \r\npyasn1-modules 0.2.8 \r\npyparsing 2.4.7 \r\nregex 2020.6.8 \r\nrequests 2.23.0 \r\nrequests-oauthlib 1.3.0 \r\nrsa 4.0 \r\nsacremoses 0.0.43 \r\nscipy 1.4.1 \r\nsentencepiece 0.1.91 \r\nsetuptools 46.0.0 \r\nsix 1.15.0 \r\nsoupsieve 2.0.1 \r\ntensorboard 2.2.2 \r\ntensorboard-plugin-wit 1.6.0.post3\r\ntensorflow 2.2.0 \r\ntensorflow-estimator 2.2.0 \r\ntermcolor 1.1.0 \r\ntokenizers 0.7.0 \r\ntorch 1.5.0 \r\ntorchvision 0.6.0 \r\ntqdm 4.46.1 \r\ntransformers 2.11.0 \r\nurllib3 1.25.9 \r\nWerkzeug 1.0.1 \r\nwheel 0.34.2 \r\nwrapt 1.12.1 `", "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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[ "I just did this too and it seems to work :S ", "I looked into this and I believe the issue is that use_external_data_format is a recent [addition to PyTorch from the onnx team](https://github.com/pytorch/pytorch/commit/96989a2a114de9b77e7dd9495d62c4a8a549b40d). If you upgrade to torch>=1.5.0 it should work. Also I added a PR #5687 to make this issue more straightforward.", "i have torch==1.13.1+cu116 installed and got this error, but i'm using in conjunction with this: https://github.com/quic/aimet" ]

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[ "Hi @aretius, some (if not all) the tests failing are unrelated to your PR, and should have been solved by the recently merged #4903. Do you mind rebasing on `master` and force pushing so that we may see if all the tests pass?", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=h1) Report\n> Merging [#4904](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase** coverage by `0.01%`.\n> The diff coverage is `93.33%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4904 +/- ##\n==========================================\n+ Coverage 76.99% 77.01% +0.01% \n==========================================\n Files 128 128 \n Lines 21602 21615 +13 \n==========================================\n+ Hits 16633 16647 +14 \n+ Misses 4969 4968 -1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/4904/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19jdHJsLnB5) | `99.14% <93.33%> (+0.50%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4904?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/4904?src=pr&el=footer). Last update [ac99217...bf94b7e](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "@sshleifer do you want to take a look?" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=h1) Report\n> Merging [#4903](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0a375f5abdefcde1424639f712cf40247135cd64&el=desc) will **increase** coverage by `36.43%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4903 +/- ##\n===========================================\n+ Coverage 40.56% 76.99% +36.43% \n===========================================\n Files 128 128 \n Lines 21602 21602 \n===========================================\n+ Hits 8762 16633 +7871 \n+ Misses 12840 4969 -7871 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `28.66% <0.00%> (+0.63%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `89.69% <0.00%> (+0.93%)` | :arrow_up: |\n| [src/transformers/data/processors/utils.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvdXRpbHMucHk=) | `27.63% <0.00%> (+1.31%)` | :arrow_up: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.37% <0.00%> (+1.44%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (+1.70%)` | :arrow_up: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.09% <0.00%> (+5.22%)` | :arrow_up: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `92.79% <0.00%> (+6.30%)` | :arrow_up: |\n| [src/transformers/training\\_args.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmluZ19hcmdzLnB5) | `77.41% <0.00%> (+11.82%)` | :arrow_up: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `76.28% <0.00%> (+14.33%)` | :arrow_up: |\n| [src/transformers/data/processors/glue.py](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvZ2x1ZS5weQ==) | `49.44% <0.00%> (+17.34%)` | :arrow_up: |\n| ... and [44 more](https://codecov.io/gh/huggingface/transformers/pull/4903/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4903?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/4903?src=pr&el=footer). Last update [0a375f5...0c9840c](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "@sshleifer It would be beneficial to provide more context, apologies for the beginner question!\r\nWould be happy to pick it up :)", "Yeah sure. The high level goal is to reduce the amount of boilerplate code in the unittests.\r\n\r\nFor example, if you look at [T5ModelTester](https://github.com/huggingface/transformers/blob/master/tests/test_modeling_t5.py#L43), there are a few code quality issues:\r\n1) The class is defined inside `T5ModelTest` class and indented. It should be defined outside. \r\n2) The class inherits from `object`. It should not.\r\n3) the class has 18 lines of keyword arguments that are never used. They should be hardcoded. For example, instead of lines 47 (`batch_size=13`) and line 68, (`self.batch_size=batch_size`), we could simply set `self.batch_size = 13` in one line.\r\n\r\n\r\nThese 3 problems occurr in nearly all of the following files:\r\n\r\n```bash\r\ngit grep \"ModelTester(object)\"\r\n```\r\nResults:\r\n```bash\r\n\r\ntests/test_modeling_albert.py: class AlbertModelTester(object):\r\ntests/test_modeling_ctrl.py: class CTRLModelTester(object):\r\ntests/test_modeling_distilbert.py: class DistilBertModelTester(object):\r\ntests/test_modeling_electra.py: class ElectraModelTester(object):\r\ntests/test_modeling_flaubert.py: class FlaubertModelTester(object):\r\ntests/test_modeling_gpt2.py: class GPT2ModelTester(object):\r\ntests/test_modeling_longformer.py:class LongformerModelTester(object):\r\ntests/test_modeling_openai.py: class OpenAIGPTModelTester(object):\r\ntests/test_modeling_roberta.py: class RobertaModelTester(object):\r\ntests/test_modeling_t5.py: class T5ModelTester(object):\r\ntests/test_modeling_tf_albert.py: class TFAlbertModelTester(object):\r\ntests/test_modeling_tf_bert.py: class TFBertModelTester(object):\r\ntests/test_modeling_tf_ctrl.py: class TFCTRLModelTester(object):\r\ntests/test_modeling_tf_distilbert.py: class TFDistilBertModelTester(object):\r\ntests/test_modeling_tf_electra.py: class TFElectraModelTester(object):\r\ntests/test_modeling_tf_gpt2.py: class TFGPT2ModelTester(object):\r\ntests/test_modeling_tf_openai_gpt.py: class TFOpenAIGPTModelTester(object):\r\ntests/test_modeling_tf_roberta.py: class TFRobertaModelTester(object):\r\ntests/test_modeling_tf_t5.py: class TFT5ModelTester(object):\r\ntests/test_modeling_tf_transfo_xl.py: class TFTransfoXLModelTester(object):\r\ntests/test_modeling_tf_xlm.py: class TFXLMModelTester(object):\r\ntests/test_modeling_tf_xlnet.py: class TFXLNetModelTester(object):\r\ntests/test_modeling_transfo_xl.py: class TransfoXLModelTester(object):\r\ntests/test_modeling_xlm.py: class XLMModelTester(object):\r\ntests/test_modeling_xlnet.py: class XLNetModelTester(object):\r\n```\r\n\r\nOnce this is done, we can update the instructions in\r\n```bash\r\ntemplates/adding_a_new_model/tests/test_modeling_tf_xxx.py\r\ntemplates/adding_a_new_model/tests/test_modeling_xxx.py\r\n```", "Indeed, code quality could be improved here!" ]

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[ "Hi @vshampor, can you let me know when this is ready for review? Thanks!", "@LysandreJik it is quite impossible to make the CI pass for the check_code_quality stage since locally the `black` and the `isort` commands seem to produce opposite changes when applied at once with `make style` and therefore cancel out; meanwhile neither check is satisfied on the CI side since the checks for `black` and `isort` are done separately. \r\n\r\nOtherwise it's ok to review this now, I believe.", "Ah yes, this happens when you have conflicting versions of black/isort. It's painful because isort should be installed from a specific commit.\r\n\r\nDon't worry about it though, we'll fix that later on!", "Credit goes to @lonePatient, I am merely integrating this to transformers because we at [nncf_pytorch](https://github.com/openvinotoolkit/nncf_pytorch) leverage this excellent repo for compression experiments with NLP models and would like to try out MobileBERT as well.\r\n\r\nWill address the remarks and update the PR.\r\n", "> * Upload the checkpoints to S3. Seeing as there's a single checkpoint released by google, I guess it would be under the name `google/mobilebert-uncased` @julien-c ?\r\n\r\nYes! We can ping the authors and check that they're ok.", "@LysandreJik @julien-c so may I upload the model to S3 already or should we wait for @saberkun's approval for this?", "I think the conversion script lacks\r\n```py\r\nname = name.replace(\"bert\", \"mobilebert\")\r\n```\r\nin order to work\r\n\r\nI'd like to update this as well as the code quality, do you mind if I push directly on your fork?", "> I think the conversion script lacks\r\n> \r\n> ```python\r\n> name = name.replace(\"bert\", \"mobilebert\")\r\n> ```\r\n> \r\n> in order to work\r\n> \r\n> I'd like to update this as well as the code quality, do you mind if I push directly on your fork?\r\n\r\nSure.", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4901?src=pr&el=h1) Report\n> Merging [#4901](https://codecov.io/gh/huggingface/transformers/pull/4901?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f45e873910e60d89511ae0193711e71c5c710468&el=desc) will **increase** coverage by `0.72%`.\n> The diff coverage is `91.26%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4901?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4901 +/- ##\n==========================================\n+ Coverage 77.19% 77.91% +0.72% \n==========================================\n Files 133 137 +4 \n Lines 22233 23470 +1237 \n==========================================\n+ Hits 17163 18287 +1124 \n- Misses 5070 5183 +113 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4901?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tb2JpbGViZXJ0LnB5) | `88.74% <88.74%> (ø)` | |\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `93.32% <93.32%> (ø)` | |\n| [src/transformers/configuration\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX21vYmlsZWJlcnQucHk=) | `97.05% <97.05%> (ø)` | |\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.19% <100.00%> (+0.02%)` | :arrow_up: |\n| [src/transformers/configuration\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2F1dG8ucHk=) | `93.18% <100.00%> (+0.15%)` | :arrow_up: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `70.93% <100.00%> (+0.16%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `72.50% <100.00%> (+0.23%)` | :arrow_up: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `97.77% <100.00%> (+0.10%)` | :arrow_up: |\n| [src/transformers/tokenization\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbW9iaWxlYmVydC5weQ==) | `100.00% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.51% <0.00%> (-1.39%)` | :arrow_down: |\n| ... and [5 more](https://codecov.io/gh/huggingface/transformers/pull/4901/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4901?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/4901?src=pr&el=footer). Last update [f45e873...e73fde7](https://codecov.io/gh/huggingface/transformers/pull/4901?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Will add the documentation in the following commit and ping you for review then @patrickvonplaten @sgugger ", "I just pushed the TensorFlow implementation, and added several models: `MobileBertFor{MaskedLM, NextSentencePrediction, MultipleChoice, TokenClassification}` alongside their tests and documentation.\r\n\r\nWill solve the two remaining tests on Monday, put the TensorFlow checkpoints on S3 and we'll be good to merge!", "Thanks for your reviews @patrickvonplaten @sgugger!" ]

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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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[ "Hey, @patrickvonplaten I observed the same with TFBertModel. So pretty much evident that the issue must be with the parent (if at all that helps)", "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", "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", "> \r\n> \r\n> While using the TFXLNetModel:\r\n> `xlnet = TFXLNetModel.from_pretrained('xlnet-base-cased')`\r\n> according to the docs, `input_ids` and `inputs_embeds` can be optionally used. However, when I tried using:\r\n> \r\n> `xlnet(inputs_embeds=embeddings, attention_mask=attn_masks)[0]`\r\n> it throws: `ValueError: The first argument to Layer.call must always be passed.`\r\n\r\ntry something like this:\r\nxlnet({'attention_mask':attention_mask, 'token_type_ids':token_type_ids},inputs_embeds=embeddings, training=training)\r\n\r\nworked for me when getting the same error for a bert model\r\n", "```python\r\nmodel_outputs = self.transformer(\r\n input_ids=None, # add this line\r\n inputs_embeds=dense_feature,\r\n attention_mask=attention_mask\r\n)\r\n```", "Is this still relevant? Gently pinging @gante @Rocketknight1 here ", "I got around the issue by changing the code from this\r\n```\r\nconfig = MobileBertConfig()\r\nmbert = TFMobileBertModel(config)\r\nmbert(inputs={\"input_ids\":input_ids, \"attention_mask\":attention_mask})\r\n```\r\nto \r\n```\r\nconfig = MobileBertConfig()\r\nmbert = TFMobileBertModel(config)\r\nmbert(input_ids=input_ids, attention_mask=attention_mask)\r\n```\r\n\r\ntransformers version : 4.22.1" ]

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[ "The \"sentiment-analysis\" pipeline is only compatible with text classification models, i.e. those that can be loaded without error with `AutoModelForSequenceClassification`" ]

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[ "Well that was quick. Awesome! Let me know if you need some help (for the pytorch part) or code review.", "Looks like a duplicate of https://github.com/huggingface/transformers/pull/4186", "> Looks like a duplicate of #4186\r\n\r\nYou are absolutely right. Closing this in favour of https://github.com/huggingface/transformers/pull/4186" ]

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[ "You can take a look at this blog post https://mccormickml.com/2019/07/22/BERT-fine-tuning/", "Thank You" ]

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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", "Looking at the interest this topic has, I am bumping it to re-open it.", "Hi,\r\n\r\nSo when #4186 is closed, this will close as well? Or is there any more changes expected. on this issue, apart from what #4186 adds?\r\n\r\nThanks\r\n", "If I've understood things correctly, I think #4186 only addresses the Pytorch implementation of the trainer. @BramVanroy if that's the case I'm happy to work on implementing this feature in Tensorflow (trainer_tf.py).", "@san7988 @KMFODA This issue should not directly be closed when that PR is merged because as @KMFODA mentions, it only seems to address PyTorch. A PR for Tensorflow is also welcome!", "Thanks for clarifying @BramVanroy. Apologies I was out for the past month due to a personal issue. I'll submit a PR for Tensorflow early stopping now.", "An early stopping callback has now been introduced in the PyTorch trainer by @cbrochtrup! 👏 \r\n\r\nAFAIK the implementation the TF Trainer is still under way (https://github.com/huggingface/transformers/pull/7533) so I'll keep this topic open for now.", "I gather from the conversation on #7533 that this issue should now be closed; is that correct, @BramVanroy ?" ]

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[ "See https://github.com/huggingface/transformers/issues/4814 as well. Over there the TPU evaluation is broken.\r\nTo make the TPU pipeline reliable, a end-to-end test could really help.", "Hi! Thank you for raising this issue, I'll take a look.\r\n\r\nOf course, having an end-to-end test would really help. Unfortunately, such suites don't exist with TPU right now.", "Thank you for fixing this so quickly!" ]

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[ "Still facing this problem. Has anyone else encountered something similar? ", "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 also face this problem. How to solve it?" ]

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[ "Thanks for bringing this up, @Colanim! I worked on #4757, and didn't realize the same could automatically extend to TFTrainer as well.\r\n\r\nPlease take a look at #4925 to see if it'd solve this for you." ]

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[ "Sure, and you can use the `add_prefix_space` flag to do that." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=h1) Report\n> Merging [#4889](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e603cb7892b49a2cbbc10ba859759f92c3fb7a6&el=desc) will **decrease** coverage by `0.03%`.\n> The diff coverage is `16.66%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4889 +/- ##\n==========================================\n- Coverage 77.00% 76.96% -0.04% \n==========================================\n Files 128 128 \n Lines 21602 21614 +12 \n==========================================\n+ Hits 16634 16636 +2 \n- Misses 4968 4978 +10 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4889/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `88.68% <16.66%> (-1.02%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4889/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.49% <0.00%> (-0.12%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4889/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (ø)` | |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4889/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.49% <0.00%> (+0.40%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4889?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/4889?src=pr&el=footer). Last update [6e603cb...560abea](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "I don't think this method is really necessary. Also, it doesn't allow to prepare decider_inputs in batches since kwargs is only given to then encoder_inputs", "I agree with @patrickvonplaten .\r\n\r\nAlso I'm currently removing `trim_batch` from `tokenization_utils` since only the BART summarization example uses it.\r\n\r\nI think it's better to keep all these small helpers in examples scripts unless you find other members of the team interested in using them as well or unless you can propose a larger modification of the general API to incorporate them seamlessly in the general abstractions we use (tokenizers, etc.).", "I think @joeddav used `trim_batch`, but fine to keep it in examples/" ]

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[ "I encountered the same problem.\r\nIf you were converting a local `pytorch_model.bin` model, you can try this\r\n\r\nsomewhere around line 258 in `convert_pytorch_checkpoint_to_tf2.py`\r\n\r\n```\r\naws_model_maps = {}\r\nconfig_class, model_class, pt_model_class, aws_config_map = MODEL_CLASSES[model_type]\r\n# config_class, model_class, pt_model_class, aws_model_maps, aws_config_map = MODEL_CLASSES[model_type]\r\n```", "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/4887?src=pr&el=h1) Report\n> Merging [#4887](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/13aa174112f0c2ee794c44188ecf13b241694db0&el=desc) will **increase** coverage by `0.01%`.\n> The diff coverage is `80.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4887 +/- ##\n==========================================\n+ Coverage 76.97% 76.99% +0.01% \n==========================================\n Files 128 128 \n Lines 21602 21607 +5 \n==========================================\n+ Hits 16629 16636 +7 \n+ Misses 4973 4971 -2 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4887/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `95.80% <80.00%> (-0.58%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4887/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.26% <0.00%> (-0.16%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4887/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4887?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/4887?src=pr&el=footer). Last update [13aa174...513ba3b](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Are we actually planning on completely removing `output_attentions` from the config? I changed my mind a bit in that I think we can keep the hierarchy 1. use function argument 2. if nothing is provided => use config parameter as is done for the generation arguments. Also another small advantage of keeping it in the config would be that attentions can easily be outputted when using torchscript. \r\n\r\nWhat is your opinion on that @thomwolf ?", "Ah, I wasn't aware of that, I thought we were deprecating them to be later removed :sweat_smile: \r\n\r\nIn that case, we should add back the documentation regarding `output_attentions` that [was removed](https://github.com/huggingface/transformers/commit/6e603cb7892b49a2cbbc10ba859759f92c3fb7a6#diff-0f9b535706b4f09eb22f7189c6c9039cL46-L49) in #4538.", "I wanted to do a PR about this and also add `use_cache` correctly back to the configs", "Cool, sounds good @patrickvonplaten " ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=h1) Report\n> Merging [#4886](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase** coverage by `0.09%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4886 +/- ##\n==========================================\n+ Coverage 76.46% 76.56% +0.09% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n+ Hits 16442 16463 +21 \n+ Misses 5060 5039 -21 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4886/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4886?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/4886?src=pr&el=footer). Last update [02e5f79...b78ed3a](https://codecov.io/gh/huggingface/transformers/pull/4886?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/4885?src=pr&el=h1) Report\n> Merging [#4885](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f0340b30310cb78555c6f78bed7262101f251940&el=desc) will **increase** coverage by `0.10%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4885 +/- ##\n==========================================\n+ Coverage 76.47% 76.57% +0.10% \n==========================================\n Files 128 128 \n Lines 21502 21528 +26 \n==========================================\n+ Hits 16443 16486 +43 \n+ Misses 5059 5042 -17 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.13% <ø> (ø)` | |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `73.60% <ø> (ø)` | |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `86.27% <ø> (ø)` | |\n| [src/transformers/modeling\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hbGJlcnQucHk=) | `77.68% <100.00%> (+1.34%)` | :arrow_up: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.58% <0.00%> (-1.39%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (ø)` | |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4885/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4885?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/4885?src=pr&el=footer). Last update [f0340b3...09b0fd5](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "This needs rework now that #4921 has been merged, so do not merge just yet.", "Ugh, rebase went wrong, closing..." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=h1) Report\n> Merging [#4884](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase** coverage by `0.02%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4884 +/- ##\n==========================================\n+ Coverage 76.46% 76.49% +0.02% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n+ Hits 16442 16448 +6 \n+ Misses 5060 5054 -6 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `74.74% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `55.55% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `86.48% <0.00%> (-6.31%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/4884/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/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `95.87% <0.00%> (-0.57%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `89.46% <0.00%> (-0.24%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (ø)` | |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `74.27% <0.00%> (+0.41%)` | :arrow_up: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4884/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4884?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/4884?src=pr&el=footer). Last update [02e5f79...9693577](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Ahah @LysandreJik you have been too fast :smile: ", "Not only this class should have been updated but all that inherit directly from `tf.keras.layers.Layer`. I will do the rest :) \r\n\r\nThanks a lot @harkous very nice catch!!!", "Thanks!\r\n@jplu I tried to verify whether other classes that inherit directly from `tf.keras.layers.Layer` have the same issue but couldn't find any that directly passes `config`. Feel free to double check though.", "Great, thanks a lot @jplu !", "Oh I didn't know you have already checked that. It is more more than perfect then!! Sorry for my previous post, my bad." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=h1) Report\n> Merging [#4883](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `66.66%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4883 +/- ##\n=======================================\n Coverage 76.55% 76.56% \n=======================================\n Files 128 128 \n Lines 21502 21504 +2 \n=======================================\n+ Hits 16461 16464 +3 \n+ Misses 5041 5040 -1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4883/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.67% <66.66%> (+0.99%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4883/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (-0.32%)` | :arrow_down: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4883?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/4883?src=pr&el=footer). Last update [9f5d5a5...9c9d9c3](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "> Wouldn't the more robust fix be to change these values to scalars if they're not?\r\n> \r\n> In the case were a string is passed (which seems to be your case), I think a warning would be better than a silently not registering anything. What do you think?\r\n\r\nI agree that logging the non-scalar values would be an improvement, and I'll update this PR to that effect. I haven't characterized what the exact error is, so I'm not sure that we can even cast the troublesome values to scalars. Thank you very much for the good feedback here @LysandreJik.", "@LysandreJik please feel free to suggest a different log level or log message from that in a33e28b" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=h1) Report\n> Merging [#4882](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase** coverage by `0.09%`.\n> The diff coverage is `0.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4882 +/- ##\n==========================================\n+ Coverage 76.46% 76.56% +0.09% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n+ Hits 16442 16462 +20 \n+ Misses 5060 5040 -20 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4882/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `89.69% <0.00%> (ø)` | |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4882/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.12% <0.00%> (-0.16%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4882/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4882?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/4882?src=pr&el=footer). Last update [02e5f79...1ce1fd3](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "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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[ "Nice!! I didn't know that parameter ^^\r\n\r\nDoes it seems better now?", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=h1) Report\n> Merging [#4881](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase** coverage by `0.07%`.\n> The diff coverage is `7.69%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4881 +/- ##\n==========================================\n+ Coverage 76.46% 76.54% +0.07% \n==========================================\n Files 128 128 \n Lines 21502 21511 +9 \n==========================================\n+ Hits 16442 16465 +23 \n+ Misses 5060 5046 -14 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/4881/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `28.21% <0.00%> (-0.45%)` | :arrow_down: |\n| [src/transformers/data/processors/glue.py](https://codecov.io/gh/huggingface/transformers/pull/4881/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvZ2x1ZS5weQ==) | `49.09% <20.00%> (-0.36%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4881/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `74.27% <0.00%> (+0.41%)` | :arrow_up: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4881/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4881?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/4881?src=pr&el=footer). Last update [02e5f79...2060038](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Ok, if this one is ok I'm gonna update the other methods the same way.", "Should be ok now.", "@julien-c @thomwolf @LysandreJik any issue to merge this?", "@LysandreJik anything else to merge?" ]

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[ "This is because the `huggingface/prunebert-xxx` configurations have a model type `masked_bert`.\r\n\r\nSince these files should be loaded directly in `BertForXXX` classes, it would probably be best to update that field to `bert`, right @julien-c?", "Yes. Can you confirm @VictorSanh?", "Seems to be working fine now, thanks @LysandreJik and @julien-c " ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=h1) Report\n> Merging [#4878](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/86578bb04c9b34f9d8e35cd4fad42a85910dd9e9&el=desc) will **decrease** coverage by `0.38%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4878 +/- ##\n==========================================\n- Coverage 77.55% 77.16% -0.39% \n==========================================\n Files 128 128 \n Lines 21791 21794 +3 \n==========================================\n- Hits 16899 16818 -81 \n- Misses 4892 4976 +84 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4878/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.13% <100.00%> (ø)` | |\n| [src/transformers/tokenization\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/4878/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `95.12% <100.00%> (+0.38%)` | :arrow_up: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/4878/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `28.66% <0.00%> (-28.03%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4878/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.61% <0.00%> (+0.11%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4878/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.73% <0.00%> (+0.46%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4878?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/4878?src=pr&el=footer). Last update [86578bb...1752816](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "I think we will need a test, there are no tests for `RobertaTokenizerFast` in `test_tokenization_roberta.py` file.", "The test is in `test_tokenization_fast`, so I think we're OK on that front.\r\nGoing to wait for @n1t0 or @mfuntowicz to approve and merge, because they are working on this concurrently. " ]

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[ "@aretius Thank you for mentioning ProphetNet. ProphetNet for huggingface is sheduled as you suggested. ", "@qiweizhen this sounds great, I would love to give it a go. Any planned date for delivering this?", "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/4876?src=pr&el=h1) Report\n> Merging [#4876](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **decrease** coverage by `0.59%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4876 +/- ##\n==========================================\n- Coverage 76.46% 75.86% -0.60% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n- Hits 16442 16313 -129 \n- Misses 5060 5189 +129 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/4876/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `28.15% <0.00%> (-63.03%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4876/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `94.73% <0.00%> (+10.04%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4876?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/4876?src=pr&el=footer). Last update [02e5f79...954557d](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ { "login": "patrickvonplaten", "id": 23423619, "node_id": "MDQ6VXNlcjIzNDIzNjE5", "avatar_url": "https://avatars.githubusercontent.com/u/23423619?v=4", "gravatar_id": "", "url": "https://api.github.com/users/patrickvonplaten", "html_url": "https://github.com/patrickvonplaten", "followers_url": "https://api.github.com/users/patrickvonplaten/followers", "following_url": "https://api.github.com/users/patrickvonplaten/following{/other_user}", "gists_url": "https://api.github.com/users/patrickvonplaten/gists{/gist_id}", "starred_url": "https://api.github.com/users/patrickvonplaten/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/patrickvonplaten/subscriptions", "organizations_url": "https://api.github.com/users/patrickvonplaten/orgs", "repos_url": "https://api.github.com/users/patrickvonplaten/repos", "events_url": "https://api.github.com/users/patrickvonplaten/events{/privacy}", "received_events_url": "https://api.github.com/users/patrickvonplaten/received_events", "type": "User", "site_admin": false } ]

[ "Hey @cstorm125, \r\n\r\nI think, those `28` leftover embeddings are simply not used. The reason why the embedding matrix is of length 32128 as far as I know is simply because 32128 is a more GPU friendly number `32128 = 128 * 251` than `32100 = 4 * 8025`. That means that the GPU is probably more efficient if it can directly deal with a power of 2 shape. \r\n\r\nAlso see: https://www.quora.com/Why-should-I-choose-a-mini-batch-size-of-32-64-128-256-etc-i-e-a-power-of-two-and-not-a-size-of-50-100-500-1000-Is-there-any-benefit-of-choosing-power-of-two-mini-batch-sizes\r\n\r\n", "Hi all, I ran into this too. But I did find a bug as a result of this mismatch. I try to resize the embedding to be smaller and got a Cuda assert error. See bug report. \r\n\r\nhttps://github.com/huggingface/transformers/issues/8643\r\n", "I found this mismatch recently and I think this may result in many bugs. Wish someone can fix it.", "> Hey @cstorm125,\r\n> \r\n> I think, those `28` leftover embeddings are simply not used. The reason why the embedding matrix is of length 32128 as far as I know is simply because 32128 is a more GPU friendly number `32128 = 128 * 251` than `32100 = 4 * 8025`. That means that the GPU is probably more efficient if it can directly deal with a power of 2 shape.\r\n> \r\n> Also see: https://www.quora.com/Why-should-I-choose-a-mini-batch-size-of-32-64-128-256-etc-i-e-a-power-of-two-and-not-a-size-of-50-100-500-1000-Is-there-any-benefit-of-choosing-power-of-two-mini-batch-sizes\r\n\r\nThis is wrong. It shouldn't be this way. In case model predicts wong index and when you calculate loss, it will cause serious issues. Its hard to believe no one cares this. ", "Hey @s4sarath, \r\n\r\nDuring training all input_ids and labels are defined by the tokenizer. If the tokenizer has a vocab_size of 32000 there is no way that it will tokenize to an id >= 32000 neither for `input_ids` nor for `labels`. Because no label ever has an id >= 32000 the model learns to never predict those ids. I don't really see a problem with this to be honest", "Hi Patrick,\n\nThanks for the reply.\nIf the embedding matrix is 32128 x d , for an example if the predicted id\nis say 32099, if we are using Sentencepiece tokenizer ( not huggingface ),\nit will fail to decode that.\n\nAnd special tokens ( 100 tokens ) are added extra, right. Which are\nactually not a part of official sentecepice model. That's why I told, it\nshouldn't be that way.\n\nThanks anyway, I really appreciate your reply.:-)\n\nOn Fri, 10 Dec, 2021, 7:11 pm Patrick von Platen, ***@***.***>\nwrote:\n\n> Hey @s4sarath <https://github.com/s4sarath>,\n>\n> During training all input_ids and labels are defined by the tokenizer. If\n> the tokenizer has a vocab_size of 32000 there is no way that it will\n> tokenize to an id >= 32000 neither for input_ids nor for labels. Because\n> no label ever has an id >= 32000 the model learns to never predict those\n> ids. I don't really see a problem with this to be honest\n>\n> —\n> You are receiving this because you were mentioned.\n> Reply to this email directly, view it on GitHub\n> <https://github.com/huggingface/transformers/issues/4875#issuecomment-990983491>,\n> or unsubscribe\n> <https://github.com/notifications/unsubscribe-auth/ACRE6KAZNTAF4DX5ZXOHUH3UQH7P5ANCNFSM4NZOPKUQ>\n> .\n> Triage notifications on the go with GitHub Mobile for iOS\n> <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675>\n> or Android\n> <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.\n>\n>\n", "Upvoting this. Another subtle bug this causes is when doing prompt tuning. The common way to do it is to call `add_tokens` to add some special prompt tokens, and also create a special embedding class that consists of two embedding matrics, the original one + one for the prompt tokens, and the forward call simply indexes into the two matrices concatenated together. Then all parameters but the prompt token embedding matrix are frozen. The expected behavior is that the IDs of the added tokens correspond to the prompt token embeddings when concatenated with the original. However, this mismatch causes the tokenizer to assign IDs starting from 32100, which are still a part of the original embedding matrix, which doesn't get gradients.", "Temporary Solution : `model.resize_token_embeddings(len(tokenizer))`\r\n", "I just found that it sometimes generates > 32100 input ids in generate function. Especially that happens if I evaluate a fine-tuned model in the very early step while training. Thanks, @Darshan2104 ! model.resize_token_embeddings(len(tokenizer)) temporally resolves my issue.", "I am also facing the `IndexError: index out of range in self` issue due to this difference between the vocab size in the t5 tokenizer and the model for ConditionalGeneration. Should I resize model token_embeddings?", "> model.resize_token_embeddings(len(tokenizer)\r\n\r\nI tried this but not helping.", "> > model.resize_token_embeddings(len(tokenizer)\r\n> \r\n> I tried this but not helping.\r\n\r\n@kanak8278 , could you double-check that you are using the right tokenizer for the model?\r\n\r\nFor the model, could you show me what happens when you run this code?\r\n```python\r\n{n:p.shape for n, p in model.named_parameters() if \"embedding\" in n}\r\n```\r\n\r\nFor the tokenizer, could you do `len(tokenizer)` and report what it says?\r\n\r\nAnd then could you do this on your input ids? `torch.tensor(input_ids).max()`", "This is a bit troubling, especially because I'm only interested in using a model for inference. I'm generating some sequences using multinomial sampling from `pythia-70M` model. When I attempt to obtain the corresponding scores to this sequence, I obtain a CUDA assertion (which, when running in the CPU, reveals itself as an indexing error). Upon checking the size of the model and the tokenizer, I find these are different, and although I understand @patrickvonplaten's justification, I am not sure how to proceed in terms of replacing these tokens, the fact is that they are being selected during the random sampling (even though they shouldn't since they were learned...). The other troubling problem of having a model head greater than the vocab size is that, by definition, these tokens will still contain some probability mass.", "@PastelBelem8 \r\n\r\nThe model was never incentivized to predict those tokens so the weights for the tokens with ids > len(tokenizer) will have extraordinarily low scores. I did a quick test and the scores for those extra tokens summed together to be on the order of 1e-30 for each token. That is basically 0. \r\n\r\nCould you share your sampling approach?", "Never mind, it was an error on my end! I apologize for the confusion! I thought I had tried everything and was desperate. " ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=h1) Report\n> Merging [#4874](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3ae2e86baffc1fea8b8b93695fb5a10941fd63dc&el=desc) will **decrease** coverage by `0.68%`.\n> The diff coverage is `88.88%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4874 +/- ##\n==========================================\n- Coverage 77.11% 76.43% -0.69% \n==========================================\n Files 128 128 \n Lines 21651 21671 +20 \n==========================================\n- Hits 16697 16564 -133 \n- Misses 4954 5107 +153 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_encoder\\_decoder.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbmNvZGVyX2RlY29kZXIucHk=) | `92.20% <ø> (ø)` | |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.17% <88.88%> (-0.12%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9weXRvcmNoX3V0aWxzLnB5) | `8.72% <0.00%> (-81.21%)` | :arrow_down: |\n| [src/transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19jdHJsLnB5) | `96.56% <0.00%> (-2.58%)` | :arrow_down: |\n| [src/transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG5ldC5weQ==) | `76.31% <0.00%> (-2.31%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.51% <0.00%> (-1.39%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `38.26% <0.00%> (-1.18%)` | :arrow_down: |\n| [src/transformers/benchmark/benchmark\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9iZW5jaG1hcmsvYmVuY2htYXJrX3V0aWxzLnB5) | `72.80% <0.00%> (-0.30%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4874/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.79% <0.00%> (+0.40%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4874?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/4874?src=pr&el=footer). Last update [3ae2e86...56a698f](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "It's possible to do it in a non-breaking way with a deprecation warning if a not-None `labels_lm` is passed to `BertForMaskedLM`. I was following the discussion of #4711 that implied it was okay to have a breaking change for this.", "I'm fine with this PR. IMO, `BertForMaskedLM` was never really used before for causal language modeling except when using Bert in an encoder-decoder setting and the encoder-decoder code is not really released yet. Also since we keep the same names for the submodules `self.bert` and `self.cls`, there won't be any errors or inconsistencies when loading pre-trained weights into the Bert2Bert encoder-decoder. \r\n\r\nIn my opinion, this change is necessary to have a clean separation between masked lm and causal lm (Reformer and Longformer will eventually run into the same issue).\r\n\r\nThe heavily used `BertForMaskedLM` for the normal masked encoder bert model does not change at all except for `lm_labels`, so that's good in terms of backward compatibility. \r\n\r\nOne thing which is problematic though is that the `MODEL_WITH_LM_HEAD_MAPPING` contains a mixture of causal models and masked encoder models at the moment: https://github.com/huggingface/transformers/blob/02e5f79662d72cccdca81a47e3001a5f6d36e5b1/src/transformers/modeling_auto.py#L187\r\n\r\nNow since Bert has both a causal model and a masked encoder model we need two mappings. \r\n\r\nI would suggest here to create 2 new mappings `MODEL_FOR_MASKED_LM_MAPPING` and `MODEL_FOR_CAUSAL_LM_MAPPING` and two new AutoModels: `AutoModelForMaksedLM` , `AutoModelForCausalLM` and for now keep `AutoModelWithLMHead` as it is and add a depreciated warning to it. \r\n\r\nWe can add `BertLMHeadModel` to `MODEL_FOR_CAUSAL_LM_MAPPING` and change to `AutoModelForCausalLM` in the encoder-decoder model. Also @thomwolf and @julien-c here", "I agree with @patrickvonplaten on the need to split `AutoModelWithLMHead` in two. Note that if the name `AutoModelForCausalLM` is picked, we should then rename (with a deprecation first of course) all `ModeltypeLMHeadModel` to `ModeltypeForCausalLM` for consistency (and clarity since just saying it has an LM head doesn't tell us if it's intended to be masked or causal).", "I agree that having two additional `AutoXXX` classes for the distinction between masked/causal would be nice. We should, however, keep the `AutoModelWithLMHead` class available for backwards compatibility.\r\n\r\nI don't agree with renaming all causal model with language modeling heads `XXXForCausalLM`. It would be more consistent, but is an aesthetic change with a very big breaking change. Even adding aliases to keep backwards compatibility would create a large overhead for the user, in my opinion, as all those classes would exist twice when importing from the library.", "In that case I would advocate to keep `AutoModelWithLMHead` for causal language models and only add an `AutoModelForMaskedLM`. Consistency is cosmetic, I agree, but it also helps not confusing beginners.", "1) For now, I think the best solution would be to keep `AutoModelForMaskedLM` as it is and add two new `AutoXXX` classes. The EncoderDecoderModel would be the first model to use `AutoModelForCausalLM` in its code. \r\n\r\n`AutoModelWithLMHead` is heavily used for all kinds of masked bert encoder models, so if we create an `AutoModelForMaskedLM` and move `BertForMaskedLM` there, we would have a lot of breaking change. I think we could add a depreciation warning to `AutoModelWithLMHead` though. \r\n\r\n2) I'm a bit indifferent to renaming all other model classes. While I'm also a big fan of consistency I agree with @LysandreJik in that I think it's a big user-facing API change that is not really urgent atm.", "In the short term, I would advocate only exposing the classical \"masked-lm\" flavour of BERT through AutoModelWithLMHead (as is done in this PR), and not even documenting/adding BertLMHeadModel to the `__init__`, as it's only used as a building block to other models.\r\n\r\nIn the longer term, I'd be ok with creating `AutoModelFor{Masked,Causal}LM` (name TBD for the second one) and not even creating a deprecation for `AutoModelWithLMHead`, forcing users to explicitly choose one or the other. This would need to be a major release though.", "@julien-c as long as we do a major release for the AutoModel renaming, I'm all for this!", "> In the short term, I would advocate only exposing the classical \"masked-lm\" flavour of BERT through AutoModelWithLMHead (as is done in this PR), and not even documenting/adding BertLMHeadModel to the `__init__`, as it's only used as a building block to other models.\r\n> \r\n> In the longer term, I'd be ok with creating `AutoModelFor{Masked,Causal}LM` (name TBD for the second one) and not even creating a deprecation for `AutoModelWithLMHead`, forcing users to explicitly choose one or the other. This would need to be a major release though.\r\n\r\nFor the encoder decoder models, I think we need `BertLMHeadModel` in the `init` and we would also need a `AutoModelForCausalLM`. Here: https://github.com/huggingface/transformers/blob/29c36e9f3678702e5ffd3fe2f1c9f6c1d6672578/src/transformers/modeling_encoder_decoder.py#L160 we need to instantiate a `BertWithCausalLM`", "I'm fine either way, I think you guys got all the important issues (backward compatibility versus cleanly building the future). I like what @patrickvonplaten and @julien-c are proposing.", "Fixed conflicts and followed @julien-c advice. @LysandreJik or @patrickvonplaten, could you do one final review just to make sure everything is fine to merge?", "This currently breaks the encoder-decoder framework `from_encoder_decoder_pretrained()` method. Will do a PR tomorrow to fix it." ]

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[ "Thank you for your fast answer.\r\n\r\nYour patch seems to fix some KeyError but not all of them.\r\n\r\nHere is an example of a context and a question that raise it :\r\n\r\n[context2.txt](https://github.com/huggingface/transformers/files/4758844/context2.txt)\r\n\r\nQuestion : \r\nQuel est l'étage se situe les locaux ?", "Indeed, this PR was not the correct fix so I closed it. Will open a new one soon.", "Just for your information, your patch also return an empty response string, but with the right location in the context.\r\n\r\nExample :\r\n[context_empty_response.txt](https://github.com/huggingface/transformers/files/4764895/context_empty_response.txt)\r\n\r\n\r\nQuestion :\r\n```\r\nQuel est la taille en mètres carrés des locaux ?\r\n```\r\n\r\nThanks for your help", "@LysandreJik Do you have an update on this ?\r\nCan I help you in any way ? ", "After some research it appears that my problem came from the fact that I was using a model trained with a `max_seq_length` set to 512 but was using the pipeline with this variable set to the default : 384.", "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/4872?src=pr&el=h1) Report\n> Merging [#4872](https://codecov.io/gh/huggingface/transformers/pull/4872?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase** coverage by `0.01%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4872?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4872 +/- ##\n==========================================\n+ Coverage 76.55% 76.56% +0.01% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n+ Hits 16461 16464 +3 \n+ Misses 5041 5038 -3 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4872?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4872/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (-0.32%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4872/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `74.27% <0.00%> (+0.41%)` | :arrow_up: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4872/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4872?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/4872?src=pr&el=footer). Last update [9f5d5a5...aad9cb1](https://codecov.io/gh/huggingface/transformers/pull/4872?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/4871?src=pr&el=h1) Report\n> Merging [#4871](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4871 +/- ##\n=======================================\n Coverage 76.55% 76.56% \n=======================================\n Files 128 128 \n Lines 21502 21502 \n=======================================\n+ Hits 16461 16462 +1 \n+ Misses 5041 5040 -1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4871/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.12% <0.00%> (-0.48%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4871/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4871?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/4871?src=pr&el=footer). Last update [9f5d5a5...40bc44a](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "cc @LysandreJik, you're going to like this:)" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=h1) Report\n> Merging [#4869](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase** coverage by `0.01%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4869 +/- ##\n==========================================\n+ Coverage 76.55% 76.57% +0.01% \n==========================================\n Files 128 128 \n Lines 21502 21510 +8 \n==========================================\n+ Hits 16461 16471 +10 \n+ Misses 5041 5039 -2 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/hf\\_argparser.py](https://codecov.io/gh/huggingface/transformers/pull/4869/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9oZl9hcmdwYXJzZXIucHk=) | `69.23% <100.00%> (+2.96%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4869/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.12% <0.00%> (-0.48%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4869/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `74.27% <0.00%> (+0.41%)` | :arrow_up: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4869/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4869?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/4869?src=pr&el=footer). Last update [9f5d5a5...4461f41](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Hi @LysandreJik , what do you think about this ? If it's not really necessary, I will close the PR. Thanks!" ]

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[ "Hello! You're using `transformers` version 2.1.1, which didn't have all of these features, as you can see in the [documentation of version 2.1.1](https://huggingface.co/transformers/v2.1.1/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.encode_plus).\r\n\r\nI would recommend upgrading your `transformers` version to the latest one to have access to all features!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=h1) Report\n> Merging [#4867](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase** coverage by `0.00%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4867 +/- ##\n=======================================\n Coverage 76.55% 76.56% \n=======================================\n Files 128 128 \n Lines 21502 21502 \n=======================================\n+ Hits 16461 16462 +1 \n+ Misses 5041 5040 -1 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4867/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.12% <0.00%> (-0.48%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4867/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4867?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/4867?src=pr&el=footer). Last update [9f5d5a5...26de790](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "@songyouwei run_pplm.py Can you follow the Readme steps to success run it? And I report this error? Could you teach me? \r\n\r\n\r\n\r\n \r\n" ]

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[ "Duplicate of #4844?", "my bad. yes" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=h1) Report\n> Merging [#4865](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **decrease** coverage by `0.00%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4865 +/- ##\n==========================================\n- Coverage 76.55% 76.54% -0.01% \n==========================================\n Files 128 128 \n Lines 21502 21502 \n==========================================\n- Hits 16461 16459 -2 \n- Misses 5041 5043 +2 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/4865/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.58% <0.00%> (-1.39%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4865/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (-0.32%)` | :arrow_down: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4865/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4865?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/4865?src=pr&el=footer). Last update [9f5d5a5...c1b9024](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "Closing in favor of #5240" ]

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[ "Hi! Can you load your tokenizer using\r\n\r\n```py\r\nfrom transformers import BertTokenizer\r\n\r\ntokenizer = BertTokenizer.from_pretrained(directory_containing_vocab_txt)\r\n```\r\n?", "> \r\n> \r\n> Hi! Can you load your tokenizer using\r\n> \r\n> ```python\r\n> from transformers import BertTokenizer\r\n> \r\n> tokenizer = BertTokenizer.from_pretrained(directory_containing_vocab_txt)\r\n> ```\r\n> \r\n> ?\r\n\r\nHi LysandreJik,\r\n Great ! It works . May I ask another question-- Do you have any experience on the loss score. Generally what score should be appropriate , my loss around 1.12 is it ok? ", "This really depends of your training set and what model you use, what checkpoint you use, etc. " ]

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[ "Interesting use-case!\r\n\r\nThe easiest way would be to simply load to models, one with the `bert-base-cased` checkpoint, the other randomly initialized, and to assign trained layers to the new model. Something like this:\r\n\r\n```py\r\nfrom transformers import BertModel, BertConfig\r\nimport torch\r\n\r\nbert_base_cased = BertModel.from_pretrained(\"bert-base-cased\") # Instantiate model using the trained weights\r\nmodel = BertModel(BertConfig.from_pretrained(\"bert-base-cased\")) # Randomly initialize model, with the same size as the trained model\r\n\r\nlayers_to_replace = [1, 2, 3, 8]\r\nfor layer in layers_to_replace:\r\n model.base_model.encoder.layer[layer] = bert_base_cased.base_model.encoder.layer[layer]\r\n\r\n# Let's compare the key values of the attention layers to make sure they're the same\r\ni = 0\r\nfor original_layer, new_layer in zip(model.base_model.encoder.layer, bert_base_cased.base_model.encoder.layer):\r\n original_attention_key = original_layer.attention.self.key.weight\r\n new_attention_key = new_layer.attention.self.key.weight\r\n difference = (torch.max(torch.abs(original_attention_key - new_attention_key)).item())\r\n\r\n print(f\"Layers {i} are {'not ' if difference else ''}the same.\")\r\n i += 1\r\n\r\n```\r\n\r\nThis outputs:\r\n\r\n```\r\nLayers 0 are not the same.\r\nLayers 1 are the same.\r\nLayers 2 are the same.\r\nLayers 3 are the same.\r\nLayers 4 are not the same.\r\nLayers 5 are not the same.\r\nLayers 6 are not the same.\r\nLayers 7 are not the same.\r\nLayers 8 are the same.\r\nLayers 9 are not the same.\r\nLayers 10 are not the same.\r\nLayers 11 are not the same.\r\n```", "Thanks, but I find this does not work for GPT2LMHeadModel. How could I extract the hidden layers of a GPT2LMHeadModel please?", "You can do the same, but the layers are under `model.base_model.h`:\r\n\r\n```py\r\n[...]\r\nfor layer in layers_to_replace:\r\n model.base_model.h[layer] = [...]\r\n[...]\r\n```", "Thanks @LysandreJik !\r\n\r\nI am wondering how you would do this in the keras versions. From tinkering around, I think you access the layers with `model.layers[0].encoder.layer`, since the length of this is 12, so I'm guessing it's for the 12 layers in the Bert model. \r\n\r\nSo you would do something like \r\n\r\n```\r\nlayers_to_replace = [1, 2, 3, 8]\r\nfor layer in layers_to_replace:\r\n newModel.layers[0].encoder.layer[layer] = trainedModel.layers[0].encoder.layer[layer]\r\n```\r\n\r\nDoes that seem right to you?", "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", "@LysandreJik This solution randomly initialize Embedding layer's weight rather than load from bert pretrained Embedding，which leads to a huge performance decline and confuses me for a week. The correct solution is:\r\n```python\r\nfrom transformers import BertModel, BertConfig\r\nimport torch\r\n\r\nbert_version = \"bert-base-cased\"\r\nbert_base_cased = BertModel.from_pretrained(bert_version) # Instantiate model using the trained weights\r\nconfig = BertConfig.from_pretrained(bert_version)\r\nmodel = BertModel(config=config) # Randomly initialize model, with the same size as the trained model\r\n\r\n# add these two lines\r\nmodel.embeddings = bert_base_cased.embeddings\r\nmodel.pooler = bert_base_cased.pooler\r\n\r\nlayers_to_replace = [1, 2, 3, 8]\r\nfor layer in layers_to_replace:\r\n model.base_model.encoder.layer[layer] = bert_base_cased.base_model.encoder.layer[layer]\r\n```\r\n\r\nalso，if you just want the first 4 layers, the easier and safer way is:\r\n```python\r\nfrom transformers import BertModel, BertConfig\r\nimport torch\r\n\r\nbert_version = \"bert-base-cased\"\r\nbert_base_cased = BertModel.from_pretrained(bert_version) # Instantiate model using the trained weights\r\nconfig = BertConfig.from_pretrained(bert_version)\r\nconfig.num_hidden_layers = 4\r\nmodel = BertModel.from_pretrained(bert_version, config=config) # auto skip unused layers\r\n\r\nfor param_name in model.state_dict():\r\n sub_param, full_param = model.state_dict()[param_name], bert_base_cased.state_dict()[param_name] # type: torch.Tensor, torch.Tensor\r\n assert (sub_param.cpu().numpy() == full_param.cpu().numpy()).all(), param_name\r\n \r\n```", "@dalek-who hey I tried to run your code before my other code to construct the model (and this is all in Sagemaker), however got this error: \r\n\r\nCUDA error: device-side assert triggered\r\nCUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.\r\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\r\n\r\nHere's the code I ran after your code:\r\n\r\n```\r\nclass BERTClass(torch.nn.Module):\r\n def __init__(self):\r\n super(BERTClass, self).__init__()\r\n self.bert_model = model \r\n self.dropout = torch.nn.Dropout(0.5)\r\n self.linear = torch.nn.Linear(768, 9) \r\n def forward(self, input_ids, attn_mask, token_type_ids):\r\n output = self.bert_model(\r\n input_ids, \r\n attention_mask=attn_mask, \r\n token_type_ids=token_type_ids\r\n )\r\n output_dropout = self.dropout(output.pooler_output)\r\n output = self.linear(output_dropout)\r\n return output\r\nbert_model = BERTClass()\r\nbert_model.to(device)\r\n```\r\n\r\nAnyone has any idea why?", "@Bambry When do you get this error? On construct the model, or on forward?\r\n`CUDA error: device-side assert triggered` often occurs when a layer receives illegal inputs, for example a `BCELoss` receives a illegal label `3`.\r\nMaybe you should check your tensor and parameter's shape, value or dtype." ]

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[ "```python\r\nfrom transformers import ReformerModelWithLMHead, ReformerConfig\r\nconfig = ReformerConfig() # define the config as you like\r\nmodel = ReformerModelWithLMHead(config)\r\nloss = model(input_ids, labels=input_ids) # input_ids are automatically shifted for labels\r\n=> train\r\n```\r\n\r\nAll this can also be done using the trainer. See this notebook for example:\r\nhttps://github.com/patrickvonplaten/notebooks/blob/master/PyTorch_Reformer.ipynb " ]

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[ "So, I investigated the google's code, then I found:\r\n\r\nhttps://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/evaluation/metrics.py#L76\r\n\r\nI think that they uses not \"rougeL\" but \"rougeLsum\".\r\nAnd also, they says:\r\n \"# Add newlines between sentences so that rougeLsum is computed correctly.\"\r\n\r\nhttps://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/evaluation/metrics.py#L82\r\n\r\n\r\nSo, I tried the following hacks:\r\n\r\n```\r\n$ g log -p\r\ncommit 11bd4a086438b100c47e5e2b7e8696fcd67e94d1\r\nAuthor: Takahiro Ito <[email protected]>\r\nDate: Tue Jun 9 14:35:19 2020 +0900\r\n\r\n スコア計算の不具合を修正\r\n\r\ndiff --git a/examples/summarization/t5/evaluate_cnn.py b/examples/summarization/t5/evaluate_cnn.py\r\nindex d2d6ee9..e1db944 100644\r\n--- a/examples/summarization/t5/evaluate_cnn.py\r\n+++ b/examples/summarization/t5/evaluate_cnn.py\r\n@@ -44,17 +44,27 @@ def generate_summaries(lns, output_file_path, model_size, batch_size, device):\r\n\r\n def calculate_rouge(output_lns, reference_lns, score_path):\r\n score_file = Path(score_path).open(\"w\")\r\n- scorer = rouge_scorer.RougeScorer([\"rouge1\", \"rouge2\", \"rougeL\"], use_stemmer=True)\r\n+ scorer = rouge_scorer.RougeScorer([\"rouge1\", \"rouge2\", \"rougeL\", \"rougeLsum\"], use_stemmer=True)\r\n aggregator = scoring.BootstrapAggregator()\r\n\r\n+ # copy from\r\n+ # https://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/evaluation/metrics.py#L80\r\n+ def _prepare_summary(summary):\r\n+ # Make sure the summary is not bytes-type\r\n+ # Add newlines between sentences so that rougeLsum is computed correctly.\r\n+ summary = summary.replace(\" . \", \" .\\n\")\r\n+ return summary\r\n+\r\n for reference_ln, output_ln in zip(reference_lns, output_lns):\r\n+ reference_ln = _prepare_summary(reference_ln)\r\n+ output_ln = _prepare_summary(output_ln)\r\n scores = scorer.score(reference_ln, output_ln)\r\n aggregator.add_scores(scores)\r\n\r\n result = aggregator.aggregate()\r\n score_file.write(\r\n- \"ROUGE_1: \\n{} \\n\\n ROUGE_2: \\n{} \\n\\n ROUGE_L: \\n{} \\n\\n\".format(\r\n- result[\"rouge1\"], result[\"rouge2\"], result[\"rougeL\"]\r\n+ \"ROUGE_1: \\n{} \\n\\n ROUGE_2: \\n{} \\n\\n ROUGE_L: \\n{} \\n\\n ROUGE_Lsum: \\n{} \\n\\n\".format(\r\n+ result[\"rouge1\"], result[\"rouge2\"], result[\"rougeL\"], result[\"rougeLsum\"]\r\n )\r\n )\r\n```\r\n\r\n, and I got a score (37.94), near paper score.\r\nNote that: the above my code shows both \"rougeL\" and \"rougeLsum\".\r\n\r\nQuestion:\r\nWhy don't your code use \"rougeLsum\" ?\r\n\r\nhttps://github.com/huggingface/transformers/blob/master/examples/summarization/t5/evaluate_cnn.py#L47\r\n\r\nI'm sorry, I'm not good at English.\r\nI hope some kind people fix this and create PR, thanks.\r\n\r\nBest,", "P.S.\r\nthe above hack is based on 41a1d27cdefd6417c298518198f99e3b8431a5c0:\r\n\r\n```\r\n$ gglv\r\n* commit 11bd4a086438b100c47e5e2b7e8696fcd67e94d1 (HEAD, master)\r\n| Author: Takahiro Ito <[email protected]>\r\n| Date: Tue Jun 9 14:35:19 2020 +0900\r\n| \r\n| スコア計算の不具合を修正\r\n| \r\n* commit 41a1d27cdefd6417c298518198f99e3b8431a5c0 (origin/master, origin/HEAD)\r\n| Author: Sylvain Gugger <[email protected]>\r\n| Date: Mon Jun 8 21:22:37 2020 -0400\r\n```\r\n", "Sorry, I accidentally closed 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" ]

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[ "Hello, Our code has just been released at [DeBERTa]( https://github.com/microsoft/DeBERTa)\r\nPlease take a try and your feedback will be good for our improvements, we also welcome the community to work together with us to improve it.\r\nWe are also glad to integrate DeBERTa into transformers.\r\n", "PR Add deberta model #5929 ", "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 - very close to merge!", "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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[ "@boy2000-007man Hi, folk. Just curious about how do you find this bug? It costs me almost the whole day... Anyway, thank you so much!", "OMG!!! Awesome Advice!!!! ", "I spent a whole night to address the dependencies problems and almost lost my mind. This answer saved my life. Appreciate!", "Thanks for this! Also curious how you worked this out - I've spent a whole day trying to figure this out!", "Thanks so much you saved my day.", "I was dreading the thought of having to dive into this issue with faulthandler and meticulously cross referencing dependencies with a working version....but this post just saved my night. Thanks @boy2000-007man \r\n\r\nThis seems like a new pytorch v1.4.0 incompatibility issue with the latest huggingface releases. I'm assuming this may have been missed due to the focus on v1.5.0 support, but it seems like many people cannot make the jump to cuda 10.2/pytorch 1.5.0 currently, so this seems like a pretty big headache that should be addressed.", "Closing this as solved by #5418", "You are excellent!", "same problem when use sentencepiece==0.1.94", "Having the same problem with sentencepiece==0.1.94", "Cf #8199 we will remove the hard dependency on sentencepiece (replaced by the `tokenizers` library) in a coming release, probably end of next week.", "Thank you a lot! You saved my day!" ]

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[ "Hello!\r\n\r\nIndeed, it is a bug in the way the TensorFlow dataset is generated. A fix is on its way :)" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=h1) Report\n> Merging [#4855](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a139d1a1602ee72ca98d5e0412efbd68f746d2c8&el=desc) will **increase** coverage by `2.61%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #4855 +/- ##\n==========================================\n+ Coverage 73.93% 76.54% +2.61% \n==========================================\n Files 128 128 \n Lines 21498 21501 +3 \n==========================================\n+ Hits 15894 16458 +564 \n+ Misses 5604 5043 -561 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.13% <ø> (ø)` | |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `73.60% <ø> (ø)` | |\n| [src/transformers/modeling\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG1fcm9iZXJ0YS5weQ==) | `100.00% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.58% <0.00%> (-1.39%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.28% <0.00%> (+0.15%)` | :arrow_up: |\n| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.23%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.26% <0.00%> (+1.42%)` | :arrow_up: |\n| [src/transformers/modeling\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yZWZvcm1lci5weQ==) | `88.19% <0.00%> (+72.36%)` | :arrow_up: |\n| [src/transformers/configuration\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/4855/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3JlZm9ybWVyLnB5) | `100.00% <0.00%> (+78.94%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4855?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/4855?src=pr&el=footer). Last update [a139d1a...b2b4f9c](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]