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Fix deprecation warnings for int div (#15180)

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* Fix deprecation warnings for int div

Co-authored-by: mgoldey <matthew.goldey@gmail.com>

* Fix import

* ensure that tensor output is python scalar

* make backward compatible

* make code more readable

* adapt test functions

Co-authored-by: mgoldey <matthew.goldey@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
This commit is contained in:
Sylvain Gugger
2022-01-18 07:28:53 -05:00
committed by GitHub
parent f6d3fee855
commit 531336bbfd
10 changed files with 43 additions and 30 deletions
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32
tests/test_modeling_wav2vec2.py
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@@ -794,10 +794,10 @@ class Wav2Vec2RobustModelTest(ModelTesterMixin, unittest.TestCase):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = Wav2Vec2ForPreTraining(config).to(torch_device)
features_shape = (
inputs_dict["input_values"].shape[0],
model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]),
)
batch_size = inputs_dict["input_values"].shape[0]
feature_seq_length = int(model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]))
features_shape = (batch_size, feature_seq_length)
mask_time_indices = _compute_mask_indices(
features_shape,
@@ -1158,10 +1158,10 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase):
inputs_dict = feature_extractor(input_speech, return_tensors="pt", padding=True)
features_shape = (
inputs_dict["input_values"].shape[0],
model._get_feat_extract_output_lengths(torch.tensor(inputs_dict["input_values"].shape[1])),
)
batch_size = inputs_dict["input_values"].shape[0]
feature_seq_length = int(model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]))
features_shape = (batch_size, feature_seq_length)
np.random.seed(4)
mask_time_indices = _compute_mask_indices(
@@ -1208,10 +1208,10 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase):
inputs_dict = feature_extractor(input_speech, return_tensors="pt", padding=True)
features_shape = (
inputs_dict["input_values"].shape[0],
model._get_feat_extract_output_lengths(torch.tensor(inputs_dict["input_values"].shape[1])),
)
batch_size = inputs_dict["input_values"].shape[0]
feature_seq_length = int(model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]))
features_shape = (batch_size, feature_seq_length)
torch.manual_seed(0)
mask_time_indices = _compute_mask_indices(
@@ -1279,10 +1279,10 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase):
inputs_dict = feature_extractor(input_speech, return_tensors="pt", padding=True)
features_shape = (
inputs_dict["input_values"].shape[0],
model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]),
)
batch_size = inputs_dict["input_values"].shape[0]
feature_seq_length = int(model._get_feat_extract_output_lengths(inputs_dict["input_values"].shape[1]))
features_shape = (batch_size, feature_seq_length)
torch.manual_seed(0)
np.random.seed(0)