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[Whisper] Fix slow test (#28407)

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* [Whisper] Fix slow test

* update

* update

* update

* update

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Patrick von Platen 2024-01-10 22:35:36 +01:00 committed by GitHub
parent 6c78bbcb83
commit cbbe30749b
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6 changed files with 10 additions and 1 deletions
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1
.github/workflows/self-nightly-scheduled.yml vendored
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@ -16,6 +16,7 @@ env:
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1

1
.github/workflows/self-past.yml vendored
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@ -27,6 +27,7 @@ env:
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1

1
.github/workflows/self-push-amd.yml vendored
View File

@ -15,6 +15,7 @@ env:
PYTEST_TIMEOUT: 60
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
jobs:
check_runner_status:

1
.github/workflows/self-scheduled-amd.yml vendored
View File

@ -16,6 +16,7 @@ env:
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}

3
.github/workflows/self-scheduled.yml vendored
View File

@ -20,6 +20,9 @@ env:
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
# For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
# This token is created under the bot `hf-transformers-bot`.
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1

4
tests/models/whisper/test_modeling_whisper.py
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@ -1651,8 +1651,10 @@ class WhisperModelIntegrationTests(unittest.TestCase):
model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
model.to(torch_device)
ds = load_dataset("common_voice", "ja", split="test", streaming=True)
token = os.getenv("HF_HUB_READ_TOKEN", True)
ds = load_dataset("mozilla-foundation/common_voice_6_1", "ja", split="test", streaming=True, token=token)
ds = ds.cast_column("audio", datasets.Audio(sampling_rate=16_000))
input_speech = next(iter(ds))["audio"]["array"]
input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="pt").input_features.to(
torch_device