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Replace input_values_processing with unpack_inputs (#21502)

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* Replace input_values_prrocessing with unpack_inputs

* Skip test failing with OOM

* Update tests
This commit is contained in:
amyeroberts
2023-02-10 18:19:39 +00:00
committed by GitHub
parent 557125637d
commit cb56590111
4 changed files with 96 additions and 427 deletions
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46
tests/models/wav2vec2/test_modeling_tf_wav2vec2.py
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@@ -369,18 +369,15 @@ class TFWav2Vec2ModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.check_training(*config_and_inputs)
# Wav2Vec2 has no inputs_embeds
@unittest.skip(reason="Wav2Vec2 has no input embeddings")
def test_inputs_embeds(self):
pass
# Wav2Vec2 cannot resize token embeddings
# since it has no tokens embeddings
@unittest.skip(reason="Wav2Vec2 has no tokens embeddings")
def test_resize_tokens_embeddings(self):
pass
# Wav2Vec2 has no inputs_embeds
# and thus the `get_input_embeddings` fn
# is not implemented
@unittest.skip(reason="Wav2Vec2 has no input embeddings")
def test_model_common_attributes(self):
pass
@@ -389,13 +386,19 @@ class TFWav2Vec2ModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFWav2Vec2Model.from_pretrained("facebook/wav2vec2-base-960h")
self.assertIsNotNone(model)
@unittest.skip(reason="Dataset conversion goes OOM and crashes with the default options!")
# We override here as passing a full batch of 13 samples results in OOM errors for CTC
def test_dataset_conversion(self):
pass
default_batch_size = self.model_tester.batch_size
self.model_tester.batch_size = 2
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
@unittest.skip(reason="Training goes OOM and crashes with the default options!")
# We override here as passing a full batch of 13 samples results in OOM errors for CTC
def test_keras_fit(self):
pass
default_batch_size = self.model_tester.batch_size
self.model_tester.batch_size = 2
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
@require_tf
@@ -497,18 +500,15 @@ class TFWav2Vec2RobustModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.check_training(*config_and_inputs)
# Wav2Vec2 has no inputs_embeds
@unittest.skip(reason="Wav2Vec2 has no input embeddings")
def test_inputs_embeds(self):
pass
# Wav2Vec2 cannot resize token embeddings
# since it has no tokens embeddings
@unittest.skip(reason="Wav2Vec2 has no tokens embeddings")
def test_resize_tokens_embeddings(self):
pass
# Wav2Vec2 has no inputs_embeds
# and thus the `get_input_embeddings` fn
# is not implemented
@unittest.skip(reason="Wav2Vec2 has no input embeddings")
def test_model_common_attributes(self):
pass
@@ -517,13 +517,19 @@ class TFWav2Vec2RobustModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFWav2Vec2Model.from_pretrained("facebook/wav2vec2-base-960h")
self.assertIsNotNone(model)
@unittest.skip(reason="Dataset conversion goes OOM and crashes with the default options!")
# We override here as passing a full batch of 13 samples results in OOM errors for CTC
def test_dataset_conversion(self):
pass
default_batch_size = self.model_tester.batch_size
self.model_tester.batch_size = 2
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
@unittest.skip(reason="Training goes OOM and crashes with the default options!")
# We override here as passing a full batch of 13 samples results in OOM errors for CTC
def test_keras_fit(self):
pass
default_batch_size = self.model_tester.batch_size
self.model_tester.batch_size = 2
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
@require_tf