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Add TF port of BLIP (#22090)

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* Initial commit

* more stash commit

* Yet another stash commit

* yet more stash commit

* Mostly working except for docs / repo consistency

* Stop importing model list from torch file

* Add TF BLIP models to docs

* Add auto classes

* Move get_text_features and get_image_features

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip_text.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/blip/test_modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/blip/test_modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/models/blip/test_modeling_tf_blip_text.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip_text.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use channels_last convolutions in TF (better performance + compatibility)

* Remove _shape function

* Move multi-line statement to one line in PT + TF

* Specify tf.keras.layers instead of importing from it

* Remove test_gradient_checkpointing and empty test_training methods

* move some multi-line statements to one line

* Update docstring for generate

* Remove pruned heads set

* Remove self.seq_len_dim

* Fixed issues with loss computation, should resolve some tests. Also ensured that the PT version follows the config for output_attentions and output_hidden_states

* ensure original model follows config in more cases

* Skip the same cross-attention tests in the PT tests - didn't realize we did it twice!

* Add training args throughout the models and layers

* make fixup

* Fix docstring for inputs_embeds

* Add docstring for is_decoder

* Add docstrings to text models

* Remove redundant computation

* Add unpack_inputs / keras_serializable

* Add modeling_tf_blip to doctests

* Add config classes for keras serialization

* Changes to allow model porting with pt-to-tf

* Quick fix to decoder head and test tweaks

* Revert an issue with masking the embeddings outputs

* Allow missing keys in some equivalence tests (for unused layers)

* Add tf-pt equivalence tests back in

* Update src/transformers/models/blip/modeling_tf_blip.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip_text.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/blip/modeling_tf_blip_text.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* make fixup

* Refactor invert_attention_mask out into tf_utils

* Re-enable cross-tests on the PT side too

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Matt
2023-04-04 16:05:22 +01:00
committed by GitHub
parent a515d0a77c
commit 5f3ea66bc0
21 changed files with 4059 additions and 45 deletions
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18
tests/test_modeling_common.py
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@@ -1984,7 +1984,7 @@ class ModelTesterMixin:
self.check_pt_tf_outputs(tf_outputs, pt_outputs, type(pt_model))
@is_pt_tf_cross_test
def test_pt_tf_model_equivalence(self):
def test_pt_tf_model_equivalence(self, allow_missing_keys=False):
import transformers
for model_class in self.all_model_classes:
@@ -2036,8 +2036,12 @@ class ModelTesterMixin:
# Check we can load pt model in tf and vice-versa with model => model functions
# Here requires `tf_inputs_dict` to build `tf_model`
tf_inputs_dict = self.prepare_tf_inputs_from_pt_inputs(pt_inputs_dict)
tf_model = transformers.load_pytorch_model_in_tf2_model(tf_model, pt_model, tf_inputs=tf_inputs_dict)
pt_model = transformers.load_tf2_model_in_pytorch_model(pt_model, tf_model)
tf_model = transformers.load_pytorch_model_in_tf2_model(
tf_model, pt_model, tf_inputs=tf_inputs_dict, allow_missing_keys=allow_missing_keys
)
pt_model = transformers.load_tf2_model_in_pytorch_model(
pt_model, tf_model, allow_missing_keys=allow_missing_keys
)
# Original test: check without `labels`
self.check_pt_tf_models(tf_model, pt_model, pt_inputs_dict)
@@ -2049,11 +2053,15 @@ class ModelTesterMixin:
with tempfile.TemporaryDirectory() as tmpdirname:
pt_checkpoint_path = os.path.join(tmpdirname, "pt_model.bin")
torch.save(pt_model.state_dict(), pt_checkpoint_path)
tf_model = transformers.load_pytorch_checkpoint_in_tf2_model(tf_model, pt_checkpoint_path)
tf_model = transformers.load_pytorch_checkpoint_in_tf2_model(
tf_model, pt_checkpoint_path, allow_missing_keys=allow_missing_keys
)
tf_checkpoint_path = os.path.join(tmpdirname, "tf_model.h5")
tf_model.save_weights(tf_checkpoint_path)
pt_model = transformers.load_tf2_checkpoint_in_pytorch_model(pt_model, tf_checkpoint_path)
pt_model = transformers.load_tf2_checkpoint_in_pytorch_model(
pt_model, tf_checkpoint_path, allow_missing_keys=allow_missing_keys
)
# Original test: check without `labels`
self.check_pt_tf_models(tf_model, pt_model, pt_inputs_dict)