Datasets:

vinayakchuni

/

issues-with-coments-transfromers

like 0

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[ "I think you flipped model and tokenizer at the beginning. It should be\r\n```python\r\n\r\nfrom transformers import BartTokenizer, BartForConditionalGeneration\r\n\r\ntokenizer = BartTokenizer.from_pretrained('/Downloads/facebook-bart-large-cnn')\r\nmodel = BartForConditionalGeneration.from_pretrained('/Downloads/facebook-bart-large-cnn')\r\n\r\n```", "Pls reopen if there is another issue!", "Damn, this was embarrassing bug on my end. Thank you! 🍻" ]

"2024-05-28T09:07:41"

"2024-05-28T09:07:41"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6923?src=pr&el=h1) Report\n> Merging [#6923](https://codecov.io/gh/huggingface/transformers/pull/6923?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4ebb52afdb4dc4bcd599e7cb503763e5d4afc962?el=desc) will **increase** coverage by `1.90%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6923?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6923 +/- ##\n==========================================\n+ Coverage 77.81% 79.72% +1.90% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n+ Hits 22452 23002 +550 \n+ Misses 6401 5851 -550 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6923?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `22.58% <0.00%> (-72.26%)` | :arrow_down: |\n| [src/transformers/configuration\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX29wZW5haS5weQ==) | `34.28% <0.00%> (-62.86%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `23.87% <0.00%> (-58.39%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `69.06% <0.00%> (-29.32%)` | :arrow_down: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `87.67% <0.00%> (-10.96%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `86.72% <0.00%> (-7.19%)` | :arrow_down: |\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `76.70% <0.00%> (-6.07%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `95.55% <0.00%> (-2.23%)` | :arrow_down: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `82.57% <0.00%> (-1.52%)` | :arrow_down: |\n| ... and [25 more](https://codecov.io/gh/huggingface/transformers/pull/6923/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6923?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/6923?src=pr&el=footer). Last update [4ebb52a...eaef0cb](https://codecov.io/gh/huggingface/transformers/pull/6923?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-27T14:27:57"

"2024-05-27T14:27:57"

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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", "I have the same issue too! Please some guidelines ?", "Same" ]

"2024-05-27T08:45:07"

"2024-05-27T09:08:19"

"2024-05-27T08:59:21"

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"2024-05-27T07:00:59"

"2024-05-27T08:07:16"

"2024-05-27T08:01:08"

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[ "Ok, I know it was my fault. I didn't add the argument `--use-external-format` (gpt2-xl is more than 2GB)\r\nActually I had to open the convert_graph_to_onnx.py file and read each argument's description\r\nThanks again, I'm closing the issue now." ]

"2024-05-26T11:12:07"

"2024-05-27T09:11:17"

"2024-05-27T09:04:54"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6919?src=pr&el=h1) Report\n> Merging [#6919](https://codecov.io/gh/huggingface/transformers/pull/6919?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/dfa10a41ba3fd9c5289bebd3baeff8792b1b2281?el=desc) will **decrease** coverage by `0.20%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6919?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6919 +/- ##\n==========================================\n- Coverage 80.02% 79.82% -0.21% \n==========================================\n Files 157 157 \n Lines 28586 28586 \n==========================================\n- Hits 22876 22818 -58 \n- Misses 5710 5768 +58 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6919?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/configuration\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX29wZW5haS5weQ==) | `34.28% <0.00%> (-62.86%)` | :arrow_down: |\n| [src/transformers/tokenization\\_mbart.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWJhcnQucHk=) | `36.50% <0.00%> (-60.32%)` | :arrow_down: |\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `28.84% <0.00%> (-58.66%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `23.87% <0.00%> (-57.10%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `64.47% <0.00%> (-34.36%)` | :arrow_down: |\n| [src/transformers/configuration\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2JhcnQucHk=) | `90.00% <0.00%> (-4.00%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.66% <0.00%> (-0.28%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.29% <0.00%> (+0.32%)` | :arrow_up: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `95.40% <0.00%> (+0.34%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `89.84% <0.00%> (+0.39%)` | :arrow_up: |\n| ... and [9 more](https://codecov.io/gh/huggingface/transformers/pull/6919/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6919?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/6919?src=pr&el=footer). Last update [dfa10a4...252c784](https://codecov.io/gh/huggingface/transformers/pull/6919?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-24T14:59:45"

"2024-05-24T14:59:45"

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[ "The `AlbertTokenizer` in `transformers` is a SentencePiece based tokenizer, so it cannot load `vocab.txt`. You could try loading it in `BertTokenizer`, as it seems to be a wordpiece tokenizer vocabulary.", "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" ]

"2024-05-24T12:43:39"

"2024-05-28T12:41:22"

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[ "@mfuntowicz - Since T5 relies on google's sentencepiece tokenizer for now, can we do anything against it before our own sentencepiece tokenizer is implemented? ", "Verified that this is a problem with the original T5 sentencepience tokenizer. Opened an issue with the Google's T5 repository. https://github.com/google-research/text-to-text-transfer-transformer/issues/390", "Closing this issue , quoting from T5 github issue\r\n> > { is OOV because we intentionally removed any pages with { or } from C4 to avoid pre-training on anything other than natural language. So, it gets encoded to ??. SentencePiece has a byte fallback feature but it was not available when we trained our sentencepiece model." ]

"2024-05-24T07:54:51"

"2024-05-24T07:54:51"

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[ "I can confirm it was previously checking the model weights and re-downloading if the weights had been changed. Investigating.", "This is due to the CDN caching files, with a 24 hour delay. After 24 hours it should download your file, but if you want it now you can use the `use_cdn` flag and set it to `False`. You can see the documentation for this [here](https://github.com/huggingface/transformers/blob/master/src/transformers/file_utils.py#L573-L585).", "Thank you for the hint, @LysandreJik. So `from_pretrained(mname, use_cdn=False)`\r\n\r\nBut that might be tricky for end users who won't know that the code base has changed yet the model weights they get are out sync.\r\n\r\nIs there a way to signal CDN to invalidate the cache for some files? It could then be done from the upload util.\r\n\r\n\r\n\r\n", "FWIW, I wrote a one liner to force cache update for the 4 models I'm working at the moment.\r\n```\r\nPYTHONPATH=\"src\" python -c 'from transformers import AutoModel; [AutoModel.from_pretrained(\"stas/fsmt-wmt19-\"+p, use_cdn=False) for p in [\"en-ru\",\"ru-en\",\"en-de\",\"de-en\"]]'\r\n```\r\nI now have that in my script, so I don't need to think about it.", "@LysandreJik, unfortunately this doesn't solve the issue\r\n\r\n`AutoModel.from_pretrained(mname, use_cdn=False)`\r\n\r\nIndeed forces a download of the recently updated model - but then if this flag is no longer used in the application - it still downloads the CDN cached version and ends up using the wrong version.\r\n\r\nSo, basically, this results in 2 copies (different hashes) sitting in the cache dir. \r\n\r\nAnd normal usage w/o using `use_cdn=False` looks up the old version and not the new one. (so things like `run_eval.py` still use the old one)\r\n\r\nThanks.\r\n", "can you run `AutoModel.from_pretrained(mname, use_cdn=False)` in a debugger and check whether the downloaded url is a `https://cdn.huggingface.co` or a `https://s3.amazonaws.com/models.huggingface.co` url?", "I can do that, but I already checked that it downloads the updated model w/ `use_cdn=False`. But then if you run it again w/o `use_cdn=False` it ignores the new download and uses the old model again (if I delete the cached version, it redownloads the old cached version w/o `use_cdn=False` ).", "Oh yeah ok, I see. Can you `run_eval.py` on a local folder path then?", "> Can you `run_eval.py` on a local folder path then?\r\n\r\nYes. Except others can't as they don't have my local copy.\r\n\r\ne.g. @sshleifer wants to eval my PR https://github.com/huggingface/transformers/pull/6940, but now has to wait till tomorrow for CDN to expire (or hack around it).\r\n\r\nLast night I uploaded an experimental model, which proved to be invalid, thought I re-downloaded it OK as it was working OK and made a PR, except I was testing against the non-current cached version, which was a good one.", "Can we please re-open this ticket? It hasn't been resolved", "Can we add a `--no_cdn` boolean flag to `run_eval.py` that would then call `AutoModelForSeq2SeqLM.from_pretrained(use_cdn=False)`?\r\n\r\nIn our dev workflow we mostly don't use the cdn while the files are still in-flux. Cloudfront invalidation comes with its own set of issues so it's better to view cdn as a means to distribute permanent files. (for this reason we don't serve config.json files from Cloudfront)", "> Can we add a `--no_cdn` boolean flag to `run_eval.py` that would then call `AutoModelForSeq2SeqLM.from_pretrained(use_cdn=False)`?\r\n\r\nIt could be done. I have a feeling then there will be others.\r\n\r\nPerhaps an alternative solution would be to introduce an env var, that would transparently override cdn cache in any situation w/o needing to change every script? `TRANSFORMERS_USE_CDN=False`?\r\n\r\n> In our dev workflow we mostly don't use the cdn while the files are still in-flux. Cloudfront invalidation comes with its own set of issues so it's better to view cdn as a means to distribute permanent files. (for this reason we don't serve config.json files from Cloudfront)\r\n\r\nUnderstood!\r\n\r\nHow do you let others onto testing the model files? Putting them on dropbox or something and sharing the link?\r\n", "No, just S3 links!", "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", "https://github.com/huggingface/transformers/pull/8324 should resolve this." ]

"2024-05-22T23:52:15"

"2024-05-23T00:07:53"

"2024-05-23T00:07:53"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6915?src=pr&el=h1) Report\n> Merging [#6915](https://codecov.io/gh/huggingface/transformers/pull/6915?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4ebb52afdb4dc4bcd599e7cb503763e5d4afc962?el=desc) will **increase** coverage by `2.01%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6915?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6915 +/- ##\n==========================================\n+ Coverage 77.81% 79.83% +2.01% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n+ Hits 22452 23034 +582 \n+ Misses 6401 5819 -582 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6915?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.82% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.13% <0.00%> (-73.83%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `22.58% <0.00%> (-72.26%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `32.20% <0.00%> (-66.95%)` | :arrow_down: |\n| [src/transformers/tokenization\\_pegasus.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcGVnYXN1cy5weQ==) | `46.03% <0.00%> (-49.21%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `76.70% <0.00%> (-6.07%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9ucy5weQ==) | `85.00% <0.00%> (-5.00%)` | :arrow_down: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `95.55% <0.00%> (-2.23%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `80.96% <0.00%> (-1.30%)` | :arrow_down: |\n| ... and [23 more](https://codecov.io/gh/huggingface/transformers/pull/6915/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6915?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/6915?src=pr&el=footer). Last update [4ebb52a...481baa3](https://codecov.io/gh/huggingface/transformers/pull/6915?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "I run a test with this change on my ubuntu 18.04 with a 2080Ti GPU, tensorflow-gpu 2.2.0:\r\n```\r\nfrom tensorflow.keras.layers import Input, Embedding, Bidirectional, GRU, Dense\r\nfrom tensorflow.keras.models import Model\r\nfrom transformers import TFDistilBertModel\r\nfrom tensorflow.keras.mixed_precision import experimental as mixed_precision\r\npolicy = mixed_precision.Policy('mixed_float16')\r\nmixed_precision.set_policy(policy)\r\n\r\nbert = TFDistilBertModel.from_pretrained('distilbert-base-uncased')\r\ninputs = Input(shape=(None,), dtype='int32')\r\nbert_out = bert(inputs)[0]\r\noutput = Dense(9, activation='softmax', dtype='float32')(bert_out)\r\nmodel = Model(inputs, output)\r\nmodel.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\r\nmodel.summary()\r\nx = [[5, 2, 3] * 3] * 100\r\ny = [[1, 2, 3] * 3] * 100\r\nmodel.fit(x=x, y=y, epochs=20, batch_size=16)\r\n```\r\nAnd get error info:\r\n```\r\nTraceback (most recent call last):\r\n File \"test.py\", line 8, in <module>\r\n bert = TFDistilBertModel.from_pretrained('distilbert-base-uncased')\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_utils.py\", line 602, in from_pretrained\r\n model(model.dummy_inputs, training=False) # build the network with dummy inputs\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 615, in call\r\n outputs = self.distilbert(inputs, **kwargs)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 508, in call\r\n tfmr_output = self.transformer(\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 401, in call\r\n layer_outputs = layer_module(hidden_state, attn_mask, head_mask[i], output_attentions, training=training)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 355, in call\r\n ffn_output = self.ffn(sa_output, training=training) # (bs, seq_length, dim)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 304, in call\r\n x = self.activation(x)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py\", line 968, in __call__\r\n outputs = self.call(cast_inputs, *args, **kwargs)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/keras/layers/core.py\", line 420, in call\r\n return self.activation(inputs)\r\n File \"/home/xingya/transformers/src/transformers/modeling_tf_distilbert.py\", line 79, in gelu\r\n cdf = 0.5 * (1.0 + tf.math.erf(x / tf.math.sqrt(2.0)))\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py\", line 984, in binary_op_wrapper\r\n return func(x, y, name=name)\r\n File \"/home/xingya/.conda/envs/transformers/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py\", line 1081, in _truediv_python3\r\n raise TypeError(\"x and y must have the same dtype, got %r != %r\" %\r\nTypeError: x and y must have the same dtype, got tf.float16 != tf.float32\r\n```\r\nI made a modification to L299:\r\n`self.activation = (\r\n tf.keras.layers.Activation(gelu, dtype='float32') if config.activation == \"gelu\" else tf.keras.activations.relu\r\n )`\r\nAnd then the model began to train, however the loss don't decrease and the accuracy is always 0:\r\n```\r\n7/7 [==============================] - 0s 28ms/step - loss: 2.1972 - accuracy: 0.0000e+00\r\nEpoch 2/20\r\n7/7 [==============================] - 0s 29ms/step - loss: 2.1972 - accuracy: 0.0000e+00\r\nEpoch 3/20\r\n7/7 [==============================] - 0s 30ms/step - loss: 2.1972 - accuracy: 0.0000e+00\r\nEpoch 4/20\r\n7/7 [==============================] - 0s 31ms/step - loss: 2.1972 - accuracy: 0.0000e+00\r\n```\r\n\r\nI have trid this code in float32 precision, and it works. \r\n```\r\nEpoch 1/20\r\n7/7 [==============================] - 0s 31ms/step - loss: 2.5418 - accuracy: 0.2800\r\nEpoch 2/20\r\n7/7 [==============================] - 0s 33ms/step - loss: 1.2452 - accuracy: 0.3356\r\nEpoch 3/20\r\n7/7 [==============================] - 0s 31ms/step - loss: 1.1438 - accuracy: 0.3267\r\nEpoch 4/20\r\n7/7 [==============================] - 0s 33ms/step - loss: 1.1219 - accuracy: 0.3400\r\n```", "@xuxingya , the accuracy not improved during training is due to a line \r\n\r\n > scores = scores - 1e30 * (1.0 - mask)\r\n\r\nwhile `1e30` with `half precision` will cause `nan` values. I am still trying to figure out a way to deal with it.", "@xuxingya Would you mind to run the test on your side again, please? I tested it with your example, and it is fine now.", "@chiapas Yes, I run the test and now it's fine." ]

"2024-05-22T13:36:33"

"2024-05-22T15:02:04"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6914?src=pr&el=h1) Report\n> Merging [#6914](https://codecov.io/gh/huggingface/transformers/pull/6914?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4ebb52afdb4dc4bcd599e7cb503763e5d4afc962?el=desc) will **increase** coverage by `1.21%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6914?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6914 +/- ##\n==========================================\n+ Coverage 77.81% 79.03% +1.21% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n+ Hits 22452 22804 +352 \n+ Misses 6401 6049 -352 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6914?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `24.55% <0.00%> (-72.36%)` | :arrow_down: |\n| [src/transformers/tokenization\\_pegasus.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcGVnYXN1cy5weQ==) | `30.15% <0.00%> (-65.08%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `77.73% <0.00%> (-19.35%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.30% <0.00%> (-0.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `88.05% <0.00%> (+0.18%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `89.84% <0.00%> (+0.39%)` | :arrow_up: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.21% <0.00%> (+0.83%)` | :arrow_up: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.64% <0.00%> (+1.34%)` | :arrow_up: |\n| [src/transformers/modeling\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kaXN0aWxiZXJ0LnB5) | `97.84% <0.00%> (+1.61%)` | :arrow_up: |\n| [src/transformers/modelcard.py](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGNhcmQucHk=) | `85.18% <0.00%> (+2.46%)` | :arrow_up: |\n| ... and [12 more](https://codecov.io/gh/huggingface/transformers/pull/6914/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6914?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/6914?src=pr&el=footer). Last update [4ebb52a...408286d](https://codecov.io/gh/huggingface/transformers/pull/6914?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-22T09:58:54"

"2024-05-22T12:50:31"

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[ "Hi! Yes, this isn't an issue, this is the intended behavior. It's the standard behavior with Sphinx/ReadTheDocs. You can see a similar example with the [PyTorch docs](https://pytorch.org/docs/stable/tensors.html)." ]

"2024-05-22T05:30:14"

"2024-05-22T05:31:10"

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[ "Hi, are you sure your issue comes from the tokenizer? If you encode your text using `encode_plus` and `batch_encode_plus`, do you see a difference in the tokens generated?", "I only use encode_plus and batch_encode_plus and call model inference. I do not think the model inference is the problem as you see in the function calls. so I think it is coming from encode_plus and batch_encode_plus. Regarding your question, I see that that batch_encode_plus add ones at the end of the list \" 1, 1, 1, 1, 1, 1]\". and I thought this is this difference may be a reason for the problem.", "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" ]

"2024-05-22T00:55:30"

"2024-05-22T19:19:58"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6911?src=pr&el=h1) Report\n> Merging [#6911](https://codecov.io/gh/huggingface/transformers/pull/6911?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4ebb52afdb4dc4bcd599e7cb503763e5d4afc962?el=desc) will **increase** coverage by `2.25%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6911?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6911 +/- ##\n==========================================\n+ Coverage 77.81% 80.06% +2.25% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n+ Hits 22452 23102 +650 \n+ Misses 6401 5751 -650 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6911?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `24.55% <0.00%> (-72.36%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `24.53% <0.00%> (-63.81%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `76.70% <0.00%> (-6.07%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/6911/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/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `93.90% <0.00%> (-0.51%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.30% <0.00%> (-0.41%)` | :arrow_down: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `87.50% <0.00%> (-0.37%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.76% <0.00%> (-0.14%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.66% <0.00%> (+0.25%)` | :arrow_up: |\n| ... and [18 more](https://codecov.io/gh/huggingface/transformers/pull/6911/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6911?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/6911?src=pr&el=footer). Last update [4ebb52a...87055d8](https://codecov.io/gh/huggingface/transformers/pull/6911?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-21T12:10:24"

"2024-05-23T08:05:58"

"2024-05-23T07:59:57"

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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" ]

"2024-05-21T07:41:09"

"2024-05-23T06:04:05"

"2024-05-23T05:58:05"

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[ "I personally wouldn't like having a pre-commit hook change all my commits without me being able to see the end result.\r\nOn my setup, I have a pre-push hook that aborts a push if make quality fails. I think if we had an install script, we could handle both options?", "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", "Hi! bring back this because I think in suggest pre-commit instead of `make ...`\r\n\r\nWith the pre-commit, we can see the results/modifications, like by example:\r\n\r\n`git add .`\r\n`git commit -m \"any\"` **this will run the pre-commit**\r\n- if everything it's ok at the pre-commit pipeline, the commit will be created\r\n- else if he modifies something (like black or style hook) he will not create the commit and change the files\r\n - when this occurs, we can see with git diff what the pre-commit change, or can just use the `--show-diff-on-failure` flag when running pre-commit.\r\n\r\nI think that doesn't need everybody use pre-commit, can use both option (the actual format with running manually `make ...` and also using pre-commit) – but maybe don't make sense because will duplicate things? \r\n\r\nA little setup for pre-commit, i have tested here:\r\n\r\nadd `.pre-commit-config.yaml` - \r\n```yml\r\nrepos:\r\n- repo: https://github.com/psf/black\r\n rev: 22.1.0\r\n hooks:\r\n - id: black\r\n- repo: https://github.com/pycqa/isort\r\n rev: 5.10.1\r\n hooks:\r\n - id: isort\r\n name: isort (python)\r\n- repo: https://github.com/PyCQA/flake8\r\n rev: 4.0.1\r\n hooks:\r\n - id: flake8\r\n- repo: local\r\n hooks:\r\n - id: autogenerate_code\r\n name: autogenerate_code\r\n entry: python setup.py deps_table_update\r\n language: python\r\n types: [python]\r\n pass_filenames: false\r\n - id: extra_style_checks\r\n name: extra_style_checks\r\n entry: make extra_style_checks\r\n language: system\r\n```\r\nNote:\r\n - The hooks _autogenerate_code_ and _extra_style_checks_, can be call using the make command or running the python.\r\n\r\nInstall pre-commit:\r\n`pre-commit install`\r\n\r\nModify src/transformers/activations.py:\r\n```diff\r\n@@ -31,7 +31,8 @@ class NewGELUActivation(nn.Module):\r\n \"\"\"\r\n def forward(self, input: Tensor) -> Tensor:\r\n- return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))\r\n+ return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 /\r\n+ math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))\r\n```\r\n```console\r\n$ git add -u\r\n$ git commit -m \"test pre-commit pipeline\"\r\n\r\nblack....................................................................Failed\r\n- hook id: black\r\n- files were modified by this hook\r\n\r\nreformatted src/transformers/activations.py\r\n\r\nAll done! ✨ 🍰 ✨\r\n1 file reformatted.\r\n\r\nisort (python)...........................................................Passed\r\nflake8...................................................................Passed\r\nautogenerate_code........................................................Passed\r\nextra_style_checks.......................................................Passed\r\n\r\n$ git status\r\nOn branch master\r\nYour branch is up to date with 'origin/master'.\r\n\r\nChanges to be committed:\r\n (use \"git restore --staged <file>...\" to unstage)\r\n modified: src/transformers/activations.py\r\n\r\nChanges not staged for commit:\r\n (use \"git add <file>...\" to update what will be committed)\r\n (use \"git restore <file>...\" to discard changes in working directory)\r\n modified: src/transformers/activations.py\r\n\r\n$ git diff\r\n--- a/src/transformers/activations.py\r\n+++ b/src/transformers/activations.py\r\n@@ -31,8 +31,7 @@ class NewGELUActivation(nn.Module):\r\n \"\"\"\r\n \r\n def forward(self, input: Tensor) -> Tensor:\r\n- return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 /\r\n- math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))\r\n+ return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))\r\n```\r\n\r\n\r\nto show git diff automatically after the pre-commit can add:\r\n```yml\r\n- repo: local\r\n hooks:\r\n - id: git-diff\r\n name: git diff\r\n entry: git diff --exit-code\r\n language: system\r\n pass_filenames: false\r\n always_run: true\r\n```\r\n", "Even though I originally created this thread 1.5 years later I now agree with @sgugger, that I don't want format changes done while pushing - I need to see what has been changed since sometimes the autoformatter messes things up badly and I need to rewrite things to make the end result readable.\r\n\r\nIf this can be done as an option and not a requirement then I'm not against it, but there needs to be a way to validate/reformat files before git is involved.\r\n\r\nBTW, `precommit` can be run manually as well and not via git, which doesn't require `pre-commit install`:\r\n\r\n```\r\npre-commit run --all-files\r\n```\r\n\r\nAnd we have 2 ways to reformat files: `fixup` (fast - only modified files) - `style` (slow)", "yes use pre-commit don't make sense if does not want to always run the pipeline...\r\n\r\nAbout the `fixup` and `style`, i think can be done equal... by default pre-commit will run just in modified files (files at the commit) and if wants to run for all files can do as you shows.\r\nFor me, by default, i think makes sense always just run at modified files. And if the autoformatter messes things we can see, and if we prefer not to use some hook (like the autoformatter that have messed up something), by example run again with `SKIP=black ...`\r\n\r\nAnd the pre-commit tool will not let the commit be created if something fails, if the dev wants “force” the failed hook will need to add the `SKIP=hook ...` before the commit command", "(i personally agree with @sgugger that local hooks are best left as user-level tooling)" ]

"2024-05-21T07:11:20"

"2024-05-21T07:45:58"

"2024-05-21T07:38:25"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6908?src=pr&el=h1) Report\n> Merging [#6908](https://codecov.io/gh/huggingface/transformers/pull/6908?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0f360d3d1c606d6d79cdf1efa53c3d719249573d?el=desc) will **increase** coverage by `0.71%`.\n> The diff coverage is `87.71%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6908?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6908 +/- ##\n==========================================\n+ Coverage 80.23% 80.95% +0.71% \n==========================================\n Files 161 164 +3 \n Lines 30119 30925 +806 \n==========================================\n+ Hits 24167 25035 +868 \n+ Misses 5952 5890 -62 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6908?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/commands/convert.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb21tYW5kcy9jb252ZXJ0LnB5) | `26.98% <20.00%> (-0.61%)` | :arrow_down: |\n| [src/transformers/modeling\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19mdW5uZWwucHk=) | `86.76% <86.76%> (ø)` | |\n| [src/transformers/tokenization\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZnVubmVsLnB5) | `97.67% <97.67%> (ø)` | |\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.31% <100.00%> (+0.01%)` | :arrow_up: |\n| [src/transformers/configuration\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2F1dG8ucHk=) | `93.47% <100.00%> (+0.14%)` | :arrow_up: |\n| [src/transformers/configuration\\_funnel.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2Z1bm5lbC5weQ==) | `100.00% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `78.97% <100.00%> (+0.12%)` | :arrow_up: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `97.87% <100.00%> (+2.22%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.13% <0.00%> (-73.83%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `72.25% <0.00%> (-10.00%)` | :arrow_down: |\n| ... and [15 more](https://codecov.io/gh/huggingface/transformers/pull/6908/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6908?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/6908?src=pr&el=footer). Last update [0f360d3...8c684cc](https://codecov.io/gh/huggingface/transformers/pull/6908?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Awesome! The model seems quite complex so I didn't really understand all the functionality. \r\nA couple of things from my side:\r\n\r\n1) IMO, it's super useful to have hard coded integration tests in the test file which makes the model a lot easier to maintain (every change can quickly be checked by making sure the model stays mathematically equivalent).\r\n\r\n2) I guess a couple of comments and assert statements would be nice to make the code a bit easier to understand\r\n\r\n3) Personally, I don't like single letter variables. Search replace commands don't work on such variables and it is very difficult to understand what they mean. ", "Thanks for all the comments. I think I replied/addressed all of them except the fast small integration tests, which are going to take a bit more work (starting on this now). Let me know if I missed anything since there are a lot of comments!", "All checkpoints uploaded so I updated the incomplete lists. Also added mention of the model in all indexes, the model summary and the big table of pretrained models (sorry about the diff on that file, Funnel Transformer is one character too long and required to add an extra space on every line).\r\n\r\nShould be good to merge at the beginning of next week!", "@sgugger although you've named the models \"`funnel-base`\", \"`funnel-medium`\" so on so forth, the paper talks about all this in a different format, could a docstring be added saying `funnel-base` is `B4-4-4H768` and same for the rest. If someone wants to replicate the papers' results that would be great.\r\n\r\nedit: my bad, its there in the comments next to the model name, but still would be better in a docstring too. Sorry!\r\n" ]

"2024-05-20T02:43:59"

"2024-05-24T10:58:09"

"2024-05-24T10:58:09"

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[ "Results for 1):\r\n\r\n```\r\n1 / 1\r\n\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: multiple - Script: True 500 128 2.575 \r\nType: multiple - Script: True 500 512 3.898 \r\nType: multiple - Script: True 2500 128 13.173 \r\nType: multiple - Script: True 2500 512 18.263 \r\n--------------------------------------------------------------------------------\r\n1 / 1\r\n\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: multiple - Script: False 500 128 3.733 \r\nType: multiple - Script: False 500 512 3.857 \r\nType: multiple - Script: False 2500 128 19.101 \r\nType: multiple - Script: False 2500 512 19.356 \r\n--------------------------------------------------------------------------------\r\n```\r\n\r\nFor the smaller sequence length 128 we can see a significant speed-up (~30%) - for the longer sequence length 512, the speed-up is much smaller (and only for the bigger list of inputs).", "Results for 2)\r\n\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 Type: batched - Script: True 512 128 0.819 \r\n Type: batched - Script: True 512 512 3.769 \r\n Type: batched - Script: True 4096 128 6.705 \r\n Type: batched - Script: True 4096 512 26.549 \r\n--------------------------------------------------------------------------------\r\n1 / 1\r\n\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: batched - Script: False 512 128 0.837 \r\nType: batched - Script: False 512 512 3.88 \r\nType: batched - Script: False 4096 128 6.75 \r\nType: batched - Script: False 4096 512 27.162 \r\n--------------------------------------------------------------------------------\r\n```\r\n\r\nHere no clear speed gains can be seen. ", "I'm not sure I understand all the interactions in the benchmarking framework, but I think in line 9 (non-script model) we should be returning torch.jit.trace(model, sample_input), not the untraced model. And the sample input would have be max_length for it to work. That's were most of the gain comes from.\r\nThen the comparison is between using torch.jit.trace() and torch.jit.script(). Or maybe I'm missing some code that does that elsewhere? \r\n\r\n", "Okey, yeah that makes sense! I changed the benchmarking script accordingly and have the following results now: \r\n\r\n1)\r\n```\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: multiple - Script: True 500 128 1.793 \r\nType: multiple - Script: True 500 512 3.628 \r\nType: multiple - Script: True 2500 128 8.774 \r\nType: multiple - Script: True 2500 512 19.471 \r\n--------------------------------------------------------------------------------\r\n1 / 1\r\n\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: multiple - Trace: True 500 128 1.83 \r\nType: multiple - Trace: True 500 512 3.783 \r\nType: multiple - Trace: True 2500 128 9.083 \r\nType: multiple - Trace: True 2500 512 20.569 \r\n--------------------------------------------------------------------------------\r\n```\r\n\r\nand \r\n\r\n2) \r\n```\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\n Type: batched - Script: True 512 128 1.043 \r\n Type: batched - Script: True 512 512 4.913 \r\n Type: batched - Script: True 4096 128 8.499 \r\n Type: batched - Script: True 4096 512 34.187 \r\n--------------------------------------------------------------------------------\r\n1 / 1\r\n\r\n==================== INFERENCE - SPEED - RESULT ====================\r\n--------------------------------------------------------------------------------\r\n Model Name Batch Size Seq Length Time in s \r\n--------------------------------------------------------------------------------\r\nType: batched - Trace: True 512 128 1.046 \r\nType: batched - Trace: True 512 512 4.916 \r\nType: batched - Trace: True 4096 128 8.042 \r\nType: batched - Trace: True 4096 512 30.874 \r\n--------------------------------------------------------------------------------\r\n```\r\n\r\n=> So my understanding is now that `torch.trace(...)` is much more efficient for dynamic input shapes than not using torch.jit at all, but I also don't see how `torch.script(...)` is better than `torch.trace(...)`. If our models are compatible with `torch.trace(...)`, why do we need to have a model that is compatible with `torch.script(...)`? It is definitely more convenient to just call `torch.trace(model)` without having to provide any `input_ids`, but I'm not 100% sure whether it's worth a huge refactoring. \r\n\r\nalso cc @sgugger @LysandreJik ", "We saw different behavior in our experiments a few months ago. Will try to reproduce and update here.", "> We saw different behavior in our experiments a few months ago. Will try to reproduce and update here.\r\n\r\nWas `torch.script()` much faster than `torch.trace()` in your experiments?", "In our experiments, using trace(model, example_input) would result in a model that would only accept a sequence of the same length as example_sequence, whereas script(model) had no such restriction. This is the case mentioned in your documentation here: https://huggingface.co/transformers/torchscript.html#dummy-inputs-and-standard-lengths\r\n\r\nWhat that meant in practice is that you needed to trace with an example sequence of length = max_length, and then pad every example of length < max_length with zeros. Since the speed of the model is basically linear in the sequence length, for a set of inputs with varying sequence lengths we got a speed up of avg_len/max_length by using script() instead of trace().\r\n\r\nUpon further investigation, it looks like when we ran these experiments, several months ago, we were using Torch 1.2. It looks like in Torch 1.3 the fixed-length problem is no longer an issue for your BERT models (we still encounter it with other models architectures we build). So there's no longer a big speed gain from script() vs trace().\r\n\r\nThere are still some good reasons for preferring script() to trace() - scripting is guaranteed to capture the model codepath logic, whereas tracing might miss a logic branch if the example input doesn't flow through it. Also, currently tracing your models produces several warnings like the one below. But I'm not sure if those on their own are enough of a motivation to make major changes in your code base.\r\n```\r\nTracerWarning: Converting a tensor to a Python index might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\r\n```", "> In our experiments, using trace(model, example_input) would result in a model that would only accept a sequence of the same length as example_sequence, whereas script(model) had no such restriction. This is the case mentioned in your documentation here: https://huggingface.co/transformers/torchscript.html#dummy-inputs-and-standard-lengths\r\n> \r\n> What that meant in practice is that you needed to trace with an example sequence of length = max_length, and then pad every example of length < max_length with zeros. Since the speed of the model is basically linear in the sequence length, for a set of inputs with varying sequence lengths we got a speed up of avg_len/max_length by using script() instead of trace().\r\n> \r\n> Upon further investigation, it looks like when we ran these experiments, several months ago, we were using Torch 1.2. It looks like in Torch 1.3 the fixed-length problem is no longer an issue for your BERT models (we still encounter it with other models architectures we build). So there's no longer a big speed gain from script() vs trace().\r\n> \r\n> There are still some good reasons for preferring script() to trace() - scripting is guaranteed to capture the model codepath logic, whereas tracing might miss a logic branch if the example input doesn't flow through it. Also, currently tracing your models produces several warnings like the one below. But I'm not sure if those on their own are enough of a motivation to make major changes in your code base.\r\n> \r\n> ```\r\n> TracerWarning: Converting a tensor to a Python index might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\r\n> ```\r\n\r\n@sgugger - what are your thoughts on this? ", "I think adding the scriptable layers seems cleaner to make sure everything works right with scripting/tracing. Not the approach in this PR but the other linked in a comment (@sbrody18 I don't know if you saw my PR to rebase on master for this branch). It ends up with most changes being helpful to read the code (type annotations and asserts) and a few extra classes for the scriptable layers but not much added code.", "@sgugger I agree - I think the extra benefit of the type and None-checking is really helpful to prevent bugs and makes the code better.\r\nI saw your PR late Friday and didn't have time to look into it. Will try to do so by end of day.", "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" ]

"2024-05-18T05:07:23"

"2024-05-18T08:53:28"

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"2024-05-17T23:19:37"

"2024-05-17T23:19:37"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6905?src=pr&el=h1) Report\n> Merging [#6905](https://codecov.io/gh/huggingface/transformers/pull/6905?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8f2723caf0f1bf7e1f639d28d004f81c96d19bbc?el=desc) will **decrease** coverage by `0.12%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6905?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6905 +/- ##\n==========================================\n- Coverage 79.81% 79.69% -0.13% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n- Hits 23029 22994 -35 \n- Misses 5824 5859 +35 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6905?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `25.13% <0.00%> (-73.83%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `22.58% <0.00%> (-72.26%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `32.20% <0.00%> (-66.95%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `42.10% <0.00%> (-57.90%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `84.52% <0.00%> (-10.72%)` | :arrow_down: |\n| [src/transformers/tokenization\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fZ3B0Mi5weQ==) | `87.50% <0.00%> (-9.73%)` | :arrow_down: |\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `76.70% <0.00%> (-6.07%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9ucy5weQ==) | `85.00% <0.00%> (-5.00%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `89.97% <0.00%> (-4.07%)` | :arrow_down: |\n| ... and [14 more](https://codecov.io/gh/huggingface/transformers/pull/6905/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6905?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/6905?src=pr&el=footer). Last update [8f2723c...0037bd4](https://codecov.io/gh/huggingface/transformers/pull/6905?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thx for fixing this!" ]

"2024-05-17T16:01:41"

"2024-05-17T16:01:41"

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[ "Didn't realize that `postprocess_next_token_scores` mutates its argument." ]

"2024-05-17T14:32:57"

"2024-05-17T14:52:56"

"2024-05-17T14:46:54"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6903?src=pr&el=h1) Report\n> Merging [#6903](https://codecov.io/gh/huggingface/transformers/pull/6903?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/485da7222f7f9ca9854db1a6df027b00d348d017?el=desc) will **increase** coverage by `0.29%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6903?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6903 +/- ##\n==========================================\n+ Coverage 79.30% 79.59% +0.29% \n==========================================\n Files 157 157 \n Lines 28853 28853 \n==========================================\n+ Hits 22882 22966 +84 \n+ Misses 5971 5887 -84 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6903?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/configuration\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX2F1dG8ucHk=) | `93.18% <ø> (ø)` | |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.64% <ø> (+0.67%)` | :arrow_up: |\n| [src/transformers/modelcard.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGNhcmQucHk=) | `85.18% <ø> (ø)` | |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `78.73% <ø> (ø)` | |\n| [src/transformers/modeling\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19kaXN0aWxiZXJ0LnB5) | `97.84% <ø> (ø)` | |\n| [src/transformers/modeling\\_encoder\\_decoder.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbmNvZGVyX2RlY29kZXIucHk=) | `92.00% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `66.86% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `64.47% <ø> (-34.36%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.29% <ø> (+0.32%)` | :arrow_up: |\n| [src/transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `87.50% <ø> (ø)` | |\n| ... and [23 more](https://codecov.io/gh/huggingface/transformers/pull/6903/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6903?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/6903?src=pr&el=footer). Last update [485da72...e8fd79c](https://codecov.io/gh/huggingface/transformers/pull/6903?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-16T13:35:51"

"2024-05-17T03:40:04"

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[ "Thanks for reporting! The PR mentioned above should fix all of those." ]

"2024-05-16T12:21:27"

"2024-05-16T12:57:02"

"2024-05-16T12:51:05"

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[ "I don't see anything blocking with this. Wdyt @sgugger @julien-c ?", "We can give a warning but then the rest of the method will fail. Are you thinking of aborting the save entirely for models that are not `PretrainedModel`s? Also, why are you not inheriting from `PretrainedModel` in your example? Is there something limiting?\r\n\r\nNote that Trainer is not supposed to be a generic training loop, but we can surely make it a bit more flexible.", "Yes, `Trainer` is not a general loop, but it works for custom models as I've tried. Majority of its parts are generalized. `PreTrainedModel` also inherits from `nn.Module`, so users can do that, although its quite common for users to inherit from `nn.Module` directly. I'm not sure how the method will fail ? We can just add a warning instead of raising a `ValueError`. The reason why I'm saying is that users would want to do more than just what `transformers` provide out of the box (for instance justing using `AutoModel` and not `SequenceClassification` models (I'm seeing a growing interest in using such models). I think `nlp` is heading towards that direction (making everything general). This works fine for all cases, I guess:\r\n```\r\nfrom types import MethodType\r\n\r\ndef _save(self, output_dir: Optional[str] = None):\r\n output_dir = output_dir if output_dir is not None else self.args.output_dir\r\n os.makedirs(output_dir, exist_ok=True)\r\n logger.info(\"Saving model checkpoint to %s\", output_dir)\r\n\r\n torch.save(\r\n {\"model_state_dict\": self.model.state_dict()},\r\n os.path.join(output_dir, \"pytorch_model.bin\"),\r\n )\r\n\r\n # Good practice: save your training arguments together with the trained model\r\n torch.save(self.args, os.path.join(output_dir, \"training_args.bin\"))\r\n\r\ntrainer._save = MethodType(_save, trainer)\r\n```\r\nWhere do you think the approach may not work ? After providing the warning, its upto users if they further want to make changes by overriding this method (they would know that `transformers` is not responsible anymore since its not a `PreTrainedModel`. Current method completely breaks the training due to `ValueError`.\r\nThis is optional, I felt that it would be useful to have. I'll open a PR if you approve.", "`save_pretrained` does more than the method you mention, but we could refactor the code inside to work with all models probably. I don't see any place it uses specific stuff from `PretrainedModel`. The thing we don't want is to add and maintain too generic code, but if it's easy enough I see no objection.\r\n\r\nYou didn't tell me why subclassing `PreTrainedModel` did not work however ;-) That is what I would expect a user building a custom model using transformers to do .", "The `PreTrainedModel` is a generic class amongst all models in `transformers`, all classes pertaining to it comply in terms of the methods it provides and can use functionalities such as `init_weights`, `prune_heads`. They might not work for custom models. For instance, some methods require `.config.` attribute which custom models may not directly have. I guess one can define their custom model to be exactly what `PreTrainedModel` requires them to be (haven't looked into that), but that would be asking users to read through what `PreTrainedModel` expects or maybe specifying in docs. It's totally up to you what you expect the users to do in case they use custom models.", "After some internal discussion with @julien-c we will lower the requirement from `PreTrainedModel` to some lower abstractclass/protocol so the user knows exactly what they have to implement for their model to work seamlessly with `Trainer`. I will work on this end of this week beginning of next. ", "Sounds good. I'll look forward to that part then." ]

"2024-05-16T11:40:22"

"2024-05-16T12:51:06"

"2024-05-16T12:51:06"

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[ "DistilBERT can support sentence pair-like inputs but does not make use of token type IDs. It detects sentence pairs according to the special tokens. cc @VictorSanh ", "@Yusifu Did you find a solution for this problem? I'm also doing sentence-pair classification (NLI) with Distilbert.", "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" ]

"2024-05-15T17:48:34"

"2024-05-15T17:48:49"

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[ "Hey @wulaoshi - I don't fully understand your question. Could you maybe post such a higher level question on the forum at `discuss.huggingface.co` ? :-) ", "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" ]

"2024-05-15T14:11:35"

"2024-05-15T14:11:35"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6898?src=pr&el=h1) Report\n> Merging [#6898](https://codecov.io/gh/huggingface/transformers/pull/6898?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d822ab636b6a14ed50f7bca0797c1de42c19de61?el=desc) will **increase** coverage by `1.00%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6898?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6898 +/- ##\n==========================================\n+ Coverage 79.61% 80.62% +1.00% \n==========================================\n Files 157 157 \n Lines 28826 28826 \n==========================================\n+ Hits 22951 23241 +290 \n+ Misses 5875 5585 -290 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6898?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `24.53% <0.00%> (-63.81%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `42.10% <0.00%> (-57.90%)` | :arrow_down: |\n| [src/transformers/modeling\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19tYXJpYW4ucHk=) | `60.00% <0.00%> (-30.00%)` | :arrow_down: |\n| [src/transformers/activations.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9hY3RpdmF0aW9ucy5weQ==) | `85.00% <0.00%> (-5.00%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `90.10% <0.00%> (-3.93%)` | :arrow_down: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `95.55% <0.00%> (-2.23%)` | :arrow_down: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `95.97% <0.00%> (-0.68%)` | :arrow_down: |\n| [src/transformers/modeling\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iYXJ0LnB5) | `93.90% <0.00%> (-0.34%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.41% <0.00%> (-0.26%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.21% <0.00%> (+0.27%)` | :arrow_up: |\n| ... and [7 more](https://codecov.io/gh/huggingface/transformers/pull/6898/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6898?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/6898?src=pr&el=footer). Last update [d822ab6...6b67e49](https://codecov.io/gh/huggingface/transformers/pull/6898?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-14T05:21:57"

"2024-05-16T14:36:57"

"2024-05-16T14:28:16"

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6897?src=pr&el=h1) Report\n> Merging [#6897](https://codecov.io/gh/huggingface/transformers/pull/6897?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d822ab636b6a14ed50f7bca0797c1de42c19de61?el=desc) will **increase** coverage by `0.77%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/6897?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #6897 +/- ##\n==========================================\n+ Coverage 79.61% 80.39% +0.77% \n==========================================\n Files 157 157 \n Lines 28826 28826 \n==========================================\n+ Hits 22951 23174 +223 \n+ Misses 5875 5652 -223 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6897?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.42% <ø> (ø)` | |\n| [src/transformers/tokenization\\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `42.10% <0.00%> (-57.90%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `45.41% <0.00%> (-47.81%)` | :arrow_down: |\n| [src/transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yb2JlcnRhLnB5) | `57.29% <0.00%> (-39.79%)` | :arrow_down: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `76.71% <0.00%> (-21.92%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `86.85% <0.00%> (-7.19%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_fast.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfZmFzdC5weQ==) | `92.14% <0.00%> (-2.15%)` | :arrow_down: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `82.57% <0.00%> (-1.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydC5weQ==) | `91.96% <0.00%> (-0.45%)` | :arrow_down: |\n| [src/transformers/data/data\\_collator.py](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL2RhdGFfY29sbGF0b3IucHk=) | `92.30% <0.00%> (-0.41%)` | :arrow_down: |\n| ... and [13 more](https://codecov.io/gh/huggingface/transformers/pull/6897/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6897?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/6897?src=pr&el=footer). Last update [d822ab6...b6c59a1](https://codecov.io/gh/huggingface/transformers/pull/6897?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

"2024-05-13T17:33:59"

"2024-05-16T14:28:17"

"2024-05-16T14:28:17"

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