Aurevoir PyTorch 1 (#35358)
* fix * fix * fix --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -60,9 +60,6 @@ if is_torch_available():
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reduce_mean,
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reduce_sum,
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)
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from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_12
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else:
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is_torch_greater_or_equal_than_1_12 = False
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class TapasModelTester:
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@@ -411,7 +408,6 @@ class TapasModelTester:
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return config, inputs_dict
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@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
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@require_torch
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class TapasModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
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all_model_classes = (
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@@ -578,7 +574,6 @@ def prepare_tapas_batch_inputs_for_training():
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return table, queries, answer_coordinates, answer_text, float_answer
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@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
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@require_torch
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class TapasModelIntegrationTest(unittest.TestCase):
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@cached_property
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@@ -930,10 +925,6 @@ class TapasModelIntegrationTest(unittest.TestCase):
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self.assertTrue(torch.allclose(outputs.logits, expected_tensor, atol=0.05))
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# Below: tests for Tapas utilities which are defined in modeling_tapas.py.
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# These are based on segmented_tensor_test.py of the original implementation.
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# URL: https://github.com/google-research/tapas/blob/master/tapas/models/segmented_tensor_test.py
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@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
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@require_torch
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class TapasUtilitiesTest(unittest.TestCase):
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def _prepare_tables(self):
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