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Try to avoid/reduce some remaining CI job failures (#37202)

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* try

* try

* Update tests/pipelines/test_pipelines_video_classification.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
This commit is contained in:
Yih-Dar
2025-04-02 14:39:57 +02:00
committed by GitHub
parent 6f5dc9c82e
commit adfc91cd46
3 changed files with 18 additions and 7 deletions
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14
tests/pipelines/test_pipelines_video_classification.py
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@@ -19,6 +19,7 @@ from huggingface_hub import VideoClassificationOutputElement, hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
_run_pipeline_tests,
compare_pipeline_output_to_hub_spec,
is_pipeline_test,
nested_simplify,
@@ -39,6 +40,11 @@ from .test_pipelines_common import ANY
class VideoClassificationPipelineTests(unittest.TestCase):
model_mapping = MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING
if _run_pipeline_tests:
example_video_filepath = hf_hub_download(
repo_id="nateraw/video-demo", filename="archery.mp4", repo_type="dataset"
)
def get_test_pipeline(
self,
model,
@@ -48,9 +54,6 @@ class VideoClassificationPipelineTests(unittest.TestCase):
processor=None,
torch_dtype="float32",
):
example_video_filepath = hf_hub_download(
repo_id="nateraw/video-demo", filename="archery.mp4", repo_type="dataset"
)
video_classifier = VideoClassificationPipeline(
model=model,
tokenizer=tokenizer,
@@ -61,8 +64,9 @@ class VideoClassificationPipelineTests(unittest.TestCase):
top_k=2,
)
examples = [
example_video_filepath,
"https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4",
self.example_video_filepath,
# TODO: re-enable this once we have a stable hub solution for CI
# "https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4",
]
return video_classifier, examples

8
tests/utils/test_audio_utils.py
View File

@@ -39,6 +39,9 @@ if is_librosa_available():
class AudioUtilsFunctionTester(unittest.TestCase):
# will be set in `def _load_datasamples`
_dataset = None
def test_hertz_to_mel(self):
self.assertEqual(hertz_to_mel(0.0), 0.0)
self.assertAlmostEqual(hertz_to_mel(100), 150.48910241)
@@ -274,8 +277,9 @@ class AudioUtilsFunctionTester(unittest.TestCase):
def _load_datasamples(self, num_samples):
from datasets import load_dataset
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
speech_samples = ds.sort("id").select(range(num_samples))[:num_samples]["audio"]
if self._dataset is None:
self._dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
speech_samples = self._dataset.sort("id").select(range(num_samples))[:num_samples]["audio"]
return [x["array"] for x in speech_samples]
def test_spectrogram_impulse(self):