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[roberta] fix lm_head.decoder.weight ignore_key handling (#12446)

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* fix lm_head.decoder.weight ignore_key handling

* fix the mutable class variable

* Update src/transformers/models/roberta/modeling_roberta.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* replicate the comment

* make deterministic

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Stas Bekman
2021-07-01 10:31:19 -07:00
committed by GitHub
parent 7f0027db30
commit 2d1d92181a
4 changed files with 48 additions and 8 deletions
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6
tests/test_modeling_common.py
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@@ -164,7 +164,7 @@ class ModelTesterMixin:
max_diff = np.amax(np.abs(out_1 - out_2))
self.assertLessEqual(max_diff, 1e-5)
def test_save_load__keys_to_ignore_on_save(self):
def test_save_load_keys_to_ignore_on_save(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
@@ -175,7 +175,7 @@ class ModelTesterMixin:
# check the keys are in the original state_dict
for k in _keys_to_ignore_on_save:
self.assertIn(k, model.state_dict())
self.assertIn(k, model.state_dict().keys(), "\n".join(model.state_dict().keys()))
# check that certain keys didn't get saved with the model
with tempfile.TemporaryDirectory() as tmpdirname:
@@ -183,7 +183,7 @@ class ModelTesterMixin:
output_model_file = os.path.join(tmpdirname, WEIGHTS_NAME)
state_dict_saved = torch.load(output_model_file)
for k in _keys_to_ignore_on_save:
self.assertNotIn(k, state_dict_saved)
self.assertNotIn(k, state_dict_saved.keys(), "\n".join(state_dict_saved.keys()))
# Test we can load the state dict in the model, necessary for the checkpointing API in Trainer.
load_result = model.load_state_dict(state_dict_saved, strict=False)