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Unverified Commit 3499c49c authored by amyeroberts's avatar amyeroberts Committed by GitHub
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Skipping more high mem tests - Wav2Vec2 Hubert (#21647) 

Skipping more tests
parent 0c9c8472
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Showing with 12 additions and 21 deletions
tests/models/hubert/test_modeling_tf_hubert.py
View file @ 3499c49c
...@@ -321,19 +321,15 @@ class TFHubertModelTest(TFModelTesterMixin, unittest.TestCase): ...@@ -321,19 +321,15 @@ class TFHubertModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFHubertModel.from_pretrained("facebook/hubert-base-ls960") model = TFHubertModel.from_pretrained("facebook/hubert-base-ls960")
self.assertIsNotNone(model) self.assertIsNotNone(model)
# We override here as passing a full batch of 13 samples results in OOM errors for CTC @unittest.skip(reason="Fix me! Hubert hits OOM errors when loss is computed on full batch")
def test_dataset_conversion(self): def test_dataset_conversion(self):
default_batch_size = self.model_tester.batch_size # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
self.model_tester.batch_size = 2 pass
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
# We override here as passing a full batch of 13 samples results in OOM errors for CTC @unittest.skip(reason="Fix me! Hubert hits OOM errors when loss is computed on full batch")
def test_keras_fit(self): def test_keras_fit(self):
default_batch_size = self.model_tester.batch_size # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
self.model_tester.batch_size = 2 pass
super().test_keras_fit()
self.model_tester.batch_size = default_batch_size
@require_tf @require_tf
......
tests/models/wav2vec2/test_modeling_tf_wav2vec2.py
View file @ 3499c49c
...@@ -512,20 +512,15 @@ class TFWav2Vec2RobustModelTest(TFModelTesterMixin, unittest.TestCase): ...@@ -512,20 +512,15 @@ class TFWav2Vec2RobustModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFWav2Vec2Model.from_pretrained("facebook/wav2vec2-base-960h") model = TFWav2Vec2Model.from_pretrained("facebook/wav2vec2-base-960h")
self.assertIsNotNone(model) self.assertIsNotNone(model)
# We override here as passing a full batch of 13 samples results in OOM errors for CTC @unittest.skip(reason="Fix me! Wav2Vec2 hits OOM errors when loss is computed on full batch")
@unittest.skip("Fix me!")
def test_dataset_conversion(self): def test_dataset_conversion(self):
default_batch_size = self.model_tester.batch_size # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
self.model_tester.batch_size = 2 pass
super().test_dataset_conversion()
self.model_tester.batch_size = default_batch_size
# We override here as passing a full batch of 13 samples results in OOM errors for CTC @unittest.skip(reason="Fix me! Wav2Vec2 hits OOM errors when loss is computed on full batch")
def test_keras_fit(self): def test_keras_fit(self):
default_batch_size = self.model_tester.batch_size # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
self.model_tester.batch_size = 2 pass
super().test_keras_fit()
self.model_tester.batch_size = default_batch_size
@require_tf @require_tf
......
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