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[Wav2vec2 + LM Test] Improve wav2vec2 with lm tests and make torch version dependent for now (#18749)

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* add first generation tutorial

* remove generation

* make version dependent expected values

* Apply suggestions from code review

* Update tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py

* fix typo
This commit is contained in:
Patrick von Platen
2022-08-26 14:11:55 +02:00
committed by GitHub
parent 8869bf41fe
commit 62ceb4d661
1 changed files with 13 additions and 14 deletions
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27
tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py
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@@ -23,6 +23,7 @@ from pathlib import Path
import datasets import datasets
import numpy as np import numpy as np
from datasets import load_dataset from datasets import load_dataset
from packaging import version
from transformers import AutoProcessor from transformers import AutoProcessor
from transformers.models.wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor from transformers.models.wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor
@@ -435,21 +436,19 @@ class Wav2Vec2ProcessorWithLMTest(unittest.TestCase):
self.assertEqual(" ".join(self.get_from_offsets(word_time_stamps, "word")), output.text) self.assertEqual(" ".join(self.get_from_offsets(word_time_stamps, "word")), output.text)
# output times # output times
start_times = [round(x, 2) for x in self.get_from_offsets(word_time_stamps, "start_time")] start_times = torch.tensor(self.get_from_offsets(word_time_stamps, "start_time"))
end_times = [round(x, 2) for x in self.get_from_offsets(word_time_stamps, "end_time")] end_times = torch.tensor(self.get_from_offsets(word_time_stamps, "end_time"))
# fmt: off # fmt: off
self.assertListEqual( expected_start_tensor = torch.tensor([1.42, 1.64, 2.12, 2.26, 2.54, 3.0, 3.24, 3.6, 3.8, 4.1, 4.26, 4.94, 5.28, 5.66, 5.78, 5.94, 6.32, 6.54, 6.66])
start_times,
[
1.42, 1.64, 2.12, 2.26, 2.54, 3.0, 3.24, 3.6, 3.8, 4.1, 4.26, 4.94, 5.28, 5.66, 5.78, 5.94, 6.32, 6.54, 6.66,
],
)
self.assertListEqual( # TODO(Patrick): This if-else version statement should be removed once
end_times, # https://github.com/huggingface/datasets/issues/4889 is resolved
[ if version.parse(version.parse(torch.__version__).base_version) >= version.parse("1.12.0"):
1.54, 1.88, 2.14, 2.46, 2.9, 3.18, 3.54, 3.72, 4.02, 4.18, 4.76, 5.16, 5.56, 5.7, 5.86, 6.2, 6.38, 6.62, 6.94, expected_end_tensor = torch.tensor([1.54, 1.88, 2.14, 2.46, 2.9, 3.16, 3.54, 3.72, 4.02, 4.18, 4.76, 5.16, 5.56, 5.7, 5.86, 6.2, 6.38, 6.62, 6.94])
], else:
) expected_end_tensor = torch.tensor([1.54, 1.88, 2.14, 2.46, 2.9, 3.18, 3.54, 3.72, 4.02, 4.18, 4.76, 5.16, 5.56, 5.7, 5.86, 6.2, 6.38, 6.62, 6.94])
# fmt: on # fmt: on
self.assertTrue(torch.allclose(start_times, expected_start_tensor, atol=0.01))
self.assertTrue(torch.allclose(end_times, expected_end_tensor, atol=0.01))