Add tests for batching support (#29297)
* add tests for batching support * Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * Update tests/test_modeling_common.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * Update tests/test_modeling_common.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * Update tests/test_modeling_common.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * fixes and comments * use cosine distance for conv models * skip mra model testing * Update tests/models/vilt/test_modeling_vilt.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * finzalize and make style * check model type by input names * Update tests/models/vilt/test_modeling_vilt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * fixed batch size for all testers * Revert "fixed batch size for all testers" This reverts commit 525f3a0a058f069fbda00352cf202b728d40df99. * add batch_size for all testers * dict from model output * do not skip layoutlm * bring back some code from git revert * Update tests/test_modeling_common.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/test_modeling_common.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * clean-up * where did minus go in tolerance * make whisper happy * deal with consequences of losing minus * deal with consequences of losing minus * maskformer needs its own test for happiness * fix more models * tag flaky CV models from Amy's approval * make codestyle --------- Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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@@ -19,7 +19,7 @@ import unittest
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from transformers import DPTConfig
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from transformers.file_utils import is_torch_available, is_vision_available
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from transformers.testing_utils import require_torch, require_vision, slow, torch_device
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from transformers.testing_utils import is_flaky, require_torch, require_vision, slow, torch_device
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from ...test_configuration_common import ConfigTester
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from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
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@@ -306,6 +306,10 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
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with self.assertRaises(ValueError):
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_ = DPTForDepthEstimation(config)
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@is_flaky(description="is_flaky https://github.com/huggingface/transformers/issues/29516")
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def test_batching_equivalence(self):
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super().test_batching_equivalence()
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# We will verify our results on an image of cute cats
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def prepare_img():
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