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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@@ -190,7 +190,7 @@ class WhisperModelTester:
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def __init__(
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self,
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parent,
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batch_size=2,
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batch_size=3, # need batch_size != num_hidden_layers
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seq_length=60,
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is_training=True,
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use_labels=False,
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@@ -1446,6 +1446,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
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model = WhisperForConditionalGeneration(config).eval().to(torch_device)
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input_features = input_dict["input_features"].to(torch_device)
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input_features = input_features[:2]
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# len = 250 with num_input_frames = 60
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long_input_features = torch.cat([input_features.repeat(1, 1, 4), input_features[:, :, :10]], dim=-1)
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@@ -2626,7 +2627,7 @@ class WhisperEncoderModelTester:
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def __init__(
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self,
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parent,
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batch_size=2,
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batch_size=3, # need batch_size != num_hidden layers
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seq_length=60,
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is_training=True,
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use_labels=True,
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@@ -2997,7 +2998,7 @@ class WhisperStandaloneDecoderModelTester:
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def __init__(
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self,
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parent,
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batch_size=2,
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batch_size=3, # need batch_size != num_hidden layers
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is_training=True,
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use_labels=False,
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vocab_size=200,
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