Add magic method to our TF models to convert datasets with column inference#17160
Add magic method to our TF models to convert datasets with column inference#17160Rocketknight1 merged 35 commits intomainfrom
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Hey all, this is the method in
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gante
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In general looks good -- the biggest question to settle is the import requirement of datasets
All our models inherit from
I'd keep the same defaults as in
We are getting to the point where we have a lot of content to announce (these changes, the metrics working correctly, generate and its updates, new models, ...), maybe we can start a once-a-week TF communication of some sort! |
sgugger
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Thanks for working on this! Let's polish the type annotations/imports and it should be good to go.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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Quick update: I think this is ready to merge, but I've only really tested it with the updated |
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I've merged the |
…erence (huggingface#17160) * Add method to call to_tf_dataset() with column inference * Add test for dataset creation * Add a default arg for data collator * Fix test * Fix call with non-dev version of datasets * Test correct column removal too * make fixup * More tests to make sure we remove unwanted columns * Fix test to avoid predicting on unbuilt models * Fix test to avoid predicting on unbuilt models * Fix test to remove unwanted head mask columns from inputs * Stop pushing your debug breakpoints to the main repo of the $2bn company you work for * Skip the test in convnext because no grouped conv support * Drop bools from the dataset dict * Make style * Skip the training test for models whose input dicts don't give us labels * Skip transformerXL in the test because it doesn't return a simple loss * Skip TFTapas because of some odd NaN losses * make style * make fixup * Add docstring * fixup * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Remove breakpoint from tests * Fix assert, add requires_backends * Protect tokenizer import with if TYPE_CHECKING * make fixup * Add noqa, more fixup * More rearranging for ~* aesthetics *~ * Adding defaults for shuffle and batch_size to match to_tf_dataset() * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
…erence (huggingface#17160) * Add method to call to_tf_dataset() with column inference * Add test for dataset creation * Add a default arg for data collator * Fix test * Fix call with non-dev version of datasets * Test correct column removal too * make fixup * More tests to make sure we remove unwanted columns * Fix test to avoid predicting on unbuilt models * Fix test to avoid predicting on unbuilt models * Fix test to remove unwanted head mask columns from inputs * Stop pushing your debug breakpoints to the main repo of the $2bn company you work for * Skip the test in convnext because no grouped conv support * Drop bools from the dataset dict * Make style * Skip the training test for models whose input dicts don't give us labels * Skip transformerXL in the test because it doesn't return a simple loss * Skip TFTapas because of some odd NaN losses * make style * make fixup * Add docstring * fixup * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Remove breakpoint from tests * Fix assert, add requires_backends * Protect tokenizer import with if TYPE_CHECKING * make fixup * Add noqa, more fixup * More rearranging for ~* aesthetics *~ * Adding defaults for shuffle and batch_size to match to_tf_dataset() * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
…erence (huggingface#17160) * Add method to call to_tf_dataset() with column inference * Add test for dataset creation * Add a default arg for data collator * Fix test * Fix call with non-dev version of datasets * Test correct column removal too * make fixup * More tests to make sure we remove unwanted columns * Fix test to avoid predicting on unbuilt models * Fix test to avoid predicting on unbuilt models * Fix test to remove unwanted head mask columns from inputs * Stop pushing your debug breakpoints to the main repo of the $2bn company you work for * Skip the test in convnext because no grouped conv support * Drop bools from the dataset dict * Make style * Skip the training test for models whose input dicts don't give us labels * Skip transformerXL in the test because it doesn't return a simple loss * Skip TFTapas because of some odd NaN losses * make style * make fixup * Add docstring * fixup * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Remove breakpoint from tests * Fix assert, add requires_backends * Protect tokenizer import with if TYPE_CHECKING * make fixup * Add noqa, more fixup * More rearranging for ~* aesthetics *~ * Adding defaults for shuffle and batch_size to match to_tf_dataset() * Update src/transformers/modeling_tf_utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Left to do:
dataset(sincedatasetsisn't imported)batch_size/shuffle?