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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/vit.py
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@@ -18,15 +18,15 @@ def data_gen():
def data_gen_for_image_classification():
data = data_gen()
data['labels'] = torch.tensor([0])
data["labels"] = torch.tensor([0])
return data
def data_gen_for_masked_image_modeling():
data = data_gen()
num_patches = (config.image_size // config.patch_size)**2
num_patches = (config.image_size // config.patch_size) ** 2
bool_masked_pos = torch.randint(low=0, high=2, size=(1, num_patches)).bool()
data['bool_masked_pos'] = bool_masked_pos
data["bool_masked_pos"] = bool_masked_pos
return data
@@ -42,23 +42,29 @@ loss_fn_for_masked_image_modeling = lambda x: x.loss
# transformers.ViTModel,
# transformers.ViTForMaskedImageModeling,
# transformers.ViTForImageClassification,
model_zoo.register(name='transformers_vit',
model_fn=lambda: transformers.ViTModel(config),
data_gen_fn=data_gen,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_vit_model,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_vit",
model_fn=lambda: transformers.ViTModel(config),
data_gen_fn=data_gen,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_vit_model,
model_attribute=ModelAttribute(has_control_flow=True),
)
model_zoo.register(name='transformers_vit_for_masked_image_modeling',
model_fn=lambda: transformers.ViTForMaskedImageModeling(config),
data_gen_fn=data_gen_for_masked_image_modeling,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_masked_image_modeling,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_vit_for_masked_image_modeling",
model_fn=lambda: transformers.ViTForMaskedImageModeling(config),
data_gen_fn=data_gen_for_masked_image_modeling,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_masked_image_modeling,
model_attribute=ModelAttribute(has_control_flow=True),
)
model_zoo.register(name='transformers_vit_for_image_classification',
model_fn=lambda: transformers.ViTForImageClassification(config),
data_gen_fn=data_gen_for_image_classification,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_image_classification,
model_attribute=ModelAttribute(has_control_flow=True))
model_zoo.register(
name="transformers_vit_for_image_classification",
model_fn=lambda: transformers.ViTForImageClassification(config),
data_gen_fn=data_gen_for_image_classification,
output_transform_fn=output_transform_fn,
loss_fn=loss_fn_for_image_classification,
model_attribute=ModelAttribute(has_control_flow=True),
)