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Add torchcodec in docstrings/tests for datasets 4.0 (#39156)

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* fix dataset run_object_detection

* bump version

* keep same dataset actually

* torchcodec in docstrings and testing utils

* torchcodec in dockerfiles and requirements

* remove duplicate

* add torchocodec to all the remaining docker files

* fix tests

* support torchcodec in audio classification and ASR

* [commit to revert] build ci-dev images

* [commit to revert] trigger circleci

* [commit to revert] build ci-dev images

* fix

* fix modeling_hubert

* backward compatible run_object_detection

* revert ci trigger commits

* fix mono conversion and support torch tensor as input

* revert map_to_array docs + fix it

* revert mono

* nit in docstring

* style

* fix modular

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Quentin Lhoest
2025-07-08 17:06:12 +02:00
committed by GitHub
parent 1255480fd2
commit 1ecd52e50a
78 changed files with 448 additions and 350 deletions
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2
tests/models/speecht5/test_feature_extraction_speecht5.py
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@@ -381,7 +381,7 @@ class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
# automatic decoding with librispeech
speech_samples = ds.sort("id").select(range(num_samples))[:num_samples]["audio"]
speech_samples = ds.sort("id")[:num_samples]["audio"]
return [x["array"] for x in speech_samples]

4
tests/models/speecht5/test_modeling_speecht5.py
View File

@@ -764,7 +764,7 @@ class SpeechT5ForSpeechToTextIntegrationTests(unittest.TestCase):
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
# automatic decoding with librispeech
speech_samples = ds.sort("id").select(range(num_samples))[:num_samples]["audio"]
speech_samples = ds.sort("id")[:num_samples]["audio"]
return [x["array"] for x in speech_samples]
@@ -1792,7 +1792,7 @@ class SpeechT5ForSpeechToSpeechIntegrationTests(unittest.TestCase):
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
# automatic decoding with librispeech
speech_samples = ds.sort("id").select(range(num_samples))[:num_samples]["audio"]
speech_samples = ds.sort("id")[:num_samples]["audio"]
return [x["array"] for x in speech_samples]