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W2v2 test require torch (#10665)

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* Adds a @require_torch to a test that requires it

* Tokenizer too

* Style
This commit is contained in:
Lysandre Debut 2021-03-11 12:56:12 -05:00 committed by GitHub
parent 055ed78f52
commit 2adc8c926a
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2 changed files with 4 additions and 2 deletions
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3
tests/test_feature_extraction_wav2vec2.py
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@ -21,7 +21,7 @@ import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, Wav2Vec2Config, Wav2Vec2FeatureExtractor
from transformers.testing_utils import slow
from transformers.testing_utils import require_torch, slow
from .test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
@ -134,6 +134,7 @@ class Wav2Vec2FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest
_check_zero_mean_unit_variance(input_values[2])
@slow
@require_torch
def test_pretrained_checkpoints_are_set_correctly(self):
# this test makes sure that models that are using
# group norm don't have their feature extractor return the

3
tests/test_tokenization_wav2vec2.py
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@ -30,7 +30,7 @@ from transformers import (
Wav2Vec2Tokenizer,
)
from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from transformers.testing_utils import require_torch, slow
from .test_tokenization_common import TokenizerTesterMixin
@ -340,6 +340,7 @@ class Wav2Vec2TokenizerTest(unittest.TestCase):
self.assertListEqual(processed.attention_mask.sum(-1).tolist(), [800, 1000, 1200])
@slow
@require_torch
def test_pretrained_checkpoints_are_set_correctly(self):
# this test makes sure that models that are using
# group norm don't have their tokenizer return the