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[tests] enable automatic speech recognition pipeline tests on XPU (#29308)

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* use require_torch_gpu

* enable on XPU
This commit is contained in:
Fanli Lin
2024-03-04 15:24:38 +08:00
committed by GitHub
parent 831bc25d8f
commit aade711d1e
1 changed files with 3 additions and 3 deletions
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tests/pipelines/test_pipelines_automatic_speech_recognition.py
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@@ -1221,7 +1221,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase):
processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en") processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en")
model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en") model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
model = model.to("cuda") model = model.to(torch_device)
pipe = pipeline( pipe = pipeline(
"automatic-speech-recognition", "automatic-speech-recognition",
@@ -1229,7 +1229,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase):
tokenizer=processor.tokenizer, tokenizer=processor.tokenizer,
feature_extractor=processor.feature_extractor, feature_extractor=processor.feature_extractor,
max_new_tokens=128, max_new_tokens=128,
device="cuda:0", device=torch_device,
) )
ds = load_dataset("distil-whisper/meanwhile", "default")["test"] ds = load_dataset("distil-whisper/meanwhile", "default")["test"]
@@ -1246,7 +1246,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase):
pipe = pipeline( pipe = pipeline(
"automatic-speech-recognition", "automatic-speech-recognition",
model="facebook/seamless-m4t-v2-large", model="facebook/seamless-m4t-v2-large",
device="cuda:0", device=torch_device,
) )
dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") dataset = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")