Add magic method to our TF models to convert datasets with column inference (#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>
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@@ -498,6 +498,10 @@ class TFTapasModelTest(TFModelTesterMixin, unittest.TestCase):
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config_and_inputs = self.model_tester.prepare_config_and_inputs()
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self.model_tester.create_and_check_for_sequence_classification(*config_and_inputs)
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@unittest.skip(reason="The default test gets NaN losses with the test-generated inputs")
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def test_dataset_conversion(self):
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pass
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def prepare_tapas_single_inputs_for_inference():
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# Here we prepare a single table-question pair to test TAPAS inference on:
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