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[misc] update pre-commit and run all files (#4752)

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* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
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48
tests/kit/model_zoo/transformers/whisper.py
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@@ -33,7 +33,7 @@ def data_gen_for_conditional_generation():
# or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored (masked), the loss is
# only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
data = data_gen()
data['labels'] = torch.tensor([[0, 1]], dtype=torch.int64)
data["labels"] = torch.tensor([[0, 1]], dtype=torch.int64)
return data
@@ -44,8 +44,8 @@ def data_gen_for_audio_classification():
# `config.num_labels > 1` a classification loss is computed (Cross-Entropy).
# `WhisperForAudioClassification` does not need `decoder_input_ids`
data = data_gen()
data.pop('decoder_input_ids')
data['labels'] = torch.tensor([1], dtype=torch.int64)
data.pop("decoder_input_ids")
data["labels"] = torch.tensor([1], dtype=torch.int64)
return data
@@ -69,23 +69,29 @@ config = transformers.WhisperConfig(
)
# register the Whisper variants
model_zoo.register(name='transformers_whisper',
model_fn=lambda: transformers.WhisperModel(config),
data_gen_fn=data_gen,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_whisper",
model_fn=lambda: transformers.WhisperModel(config),
data_gen_fn=data_gen,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn,
model_attribute=ModelAttribute(has_control_flow=True),
)
model_zoo.register(name='transformers_whisper_for_conditional_generation',
model_fn=lambda: transformers.WhisperForConditionalGeneration(config),
data_gen_fn=data_gen_for_conditional_generation,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_attr,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_whisper_for_conditional_generation",
model_fn=lambda: transformers.WhisperForConditionalGeneration(config),
data_gen_fn=data_gen_for_conditional_generation,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_attr,
model_attribute=ModelAttribute(has_control_flow=True),
)
model_zoo.register(name='transformers_whisper_for_audio_classification',
model_fn=lambda: transformers.WhisperForAudioClassification(config),
data_gen_fn=data_gen_for_audio_classification,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_attr,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_whisper_for_audio_classification",
model_fn=lambda: transformers.WhisperForAudioClassification(config),
data_gen_fn=data_gen_for_audio_classification,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_attr,
model_attribute=ModelAttribute(has_control_flow=True),
)