SUMIN/HuggingFace_transformer
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Add SimMIM (#15586)

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* Add first draft

* Make model importable

* Make SwinForMaskedImageModeling importable

* Fix imports

* Add missing inits

* Add support for Swin

* Fix bug

* Fix bug

* Fix another bug

* Fix Swin MIM implementation

* Fix default encoder stride

* Fix Swin

* Add print statements for debugging

* Add image_size data argument

* Fix Swin

* Fix image_size

* Add print statements for debugging

* Fix print statement

* Remove print statements

* Improve reshaping of bool_masked_pos

* Add support for DeiT, fix tests

* Improve docstrings

* Apply new black version

* Improve script

* Fix bug

* Improve README

* Apply suggestions from code review

* Remove DS_Store and add to gitignore

* Apply suggestions from code review + fix BEiT Flax

* Revert BEiT changes

* Improve README

* Fix code quality

* Improve README

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
This commit is contained in:
NielsRogge
2022-02-17 19:44:55 +01:00
committed by GitHub
parent 426b96230a
commit 57882177be
26 changed files with 1075 additions and 51 deletions
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6
tests/test_modeling_common.py
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@@ -72,6 +72,7 @@ if is_torch_available():
MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
MODEL_FOR_CAUSAL_LM_MAPPING,
MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
@@ -165,6 +166,11 @@ class ModelTesterMixin:
inputs_dict["labels"] = torch.zeros(
(self.model_tester.batch_size, self.model_tester.seq_length), dtype=torch.long, device=torch_device
)
elif model_class in get_values(MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING):
num_patches = self.model_tester.image_size // self.model_tester.patch_size
inputs_dict["bool_masked_pos"] = torch.zeros(
(self.model_tester.batch_size, num_patches**2), dtype=torch.long, device=torch_device
)
return inputs_dict
def test_save_load(self):