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[Wav2Vec2] Fix torch srcipt (#24062)

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* [Wav2Vec2] Fix torch srcipt

* fix more
This commit is contained in:
Patrick von Platen
2023-06-07 13:27:07 +02:00
committed by GitHub
parent 612b2a1a6d
commit 52972e70c7
2 changed files with 5 additions and 6 deletions
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5
src/transformers/models/wav2vec2/modeling_wav2vec2.py
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@@ -1178,8 +1178,7 @@ class Wav2Vec2PreTrainedModel(PreTrainedModel):
if isinstance(module, (Wav2Vec2Encoder, Wav2Vec2EncoderStableLayerNorm, Wav2Vec2FeatureEncoder)): if isinstance(module, (Wav2Vec2Encoder, Wav2Vec2EncoderStableLayerNorm, Wav2Vec2FeatureEncoder)):
module.gradient_checkpointing = value module.gradient_checkpointing = value
@property def _get_adapters(self):
def _adapters(self):
if self.config.adapter_attn_dim is None: if self.config.adapter_attn_dim is None:
raise ValueError(f"{self.__class__} has no adapter layers. Make sure to define `config.adapter_attn_dim`.") raise ValueError(f"{self.__class__} has no adapter layers. Make sure to define `config.adapter_attn_dim`.")
@@ -1339,7 +1338,7 @@ class Wav2Vec2PreTrainedModel(PreTrainedModel):
f" directory containing a file named {filepath}." f" directory containing a file named {filepath}."
) )
adapter_weights = self._adapters adapter_weights = self._get_adapters()
unexpected_keys = set(state_dict.keys()) - set(adapter_weights.keys()) unexpected_keys = set(state_dict.keys()) - set(adapter_weights.keys())
missing_keys = set(adapter_weights.keys()) - set(state_dict.keys()) missing_keys = set(adapter_weights.keys()) - set(state_dict.keys())

6
tests/models/wav2vec2/test_modeling_wav2vec2.py
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@@ -297,7 +297,7 @@ class Wav2Vec2ModelTester:
config.adapter_attn_dim = 16 config.adapter_attn_dim = 16
model = Wav2Vec2ForCTC(config=config) model = Wav2Vec2ForCTC(config=config)
self.parent.assertIsNotNone(model._adapters) self.parent.assertIsNotNone(model._get_adapters())
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@@ -1146,7 +1146,7 @@ class Wav2Vec2RobustModelTest(ModelTesterMixin, unittest.TestCase):
model = Wav2Vec2ForCTC.from_pretrained(tempdir) model = Wav2Vec2ForCTC.from_pretrained(tempdir)
logits = get_logits(model, input_features) logits = get_logits(model, input_features)
adapter_weights = model._adapters adapter_weights = model._get_adapters()
# save safe weights # save safe weights
safe_filepath = os.path.join(tempdir, WAV2VEC2_ADAPTER_SAFE_FILE.format("eng")) safe_filepath = os.path.join(tempdir, WAV2VEC2_ADAPTER_SAFE_FILE.format("eng"))
@@ -1168,7 +1168,7 @@ class Wav2Vec2RobustModelTest(ModelTesterMixin, unittest.TestCase):
model = Wav2Vec2ForCTC.from_pretrained(tempdir) model = Wav2Vec2ForCTC.from_pretrained(tempdir)
logits = get_logits(model, input_features) logits = get_logits(model, input_features)
adapter_weights = model._adapters adapter_weights = model._get_adapters()
# save pt weights # save pt weights
pt_filepath = os.path.join(tempdir, WAV2VEC2_ADAPTER_PT_FILE.format("eng")) pt_filepath = os.path.join(tempdir, WAV2VEC2_ADAPTER_PT_FILE.format("eng"))