SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

fix audio classification pipeline fp16 test on cuda (#36359)

Browse Source 
* fix audio classification pipeline fp16 test on cuda

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* add comments

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Update tests/pipelines/test_pipelines_audio_classification.py

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
This commit is contained in:
jiqing-feng
2025-02-25 22:01:25 +08:00
committed by GitHub
parent c3700b0eee
commit 7c8916ddb5
1 changed files with 9 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
tests/pipelines/test_pipelines_audio_classification.py
View File

@@ -144,18 +144,21 @@ class AudioClassificationPipelineTests(unittest.TestCase):
audio = np.ones((8000,)) audio = np.ones((8000,))
output = audio_classifier(audio, top_k=4) output = audio_classifier(audio, top_k=4)
# Expected outputs are collected running the test on torch 2.6 in few scenarios.
# Running on CUDA T4/A100 and on XPU PVC (note: using stock torch xpu, NOT using IPEX):
EXPECTED_OUTPUT = [ EXPECTED_OUTPUT = [
{"score": 0.0833, "label": "go"},
{"score": 0.0833, "label": "off"},
{"score": 0.0833, "label": "stop"},
{"score": 0.0833, "label": "on"},
]
# Running on CPU:
EXPECTED_OUTPUT_PT_2 = [
{"score": 0.0839, "label": "no"}, {"score": 0.0839, "label": "no"},
{"score": 0.0837, "label": "go"}, {"score": 0.0837, "label": "go"},
{"score": 0.0836, "label": "yes"}, {"score": 0.0836, "label": "yes"},
{"score": 0.0835, "label": "right"}, {"score": 0.0835, "label": "right"},
] ]
EXPECTED_OUTPUT_PT_2 = [
{"score": 0.0845, "label": "stop"},
{"score": 0.0844, "label": "on"},
{"score": 0.0841, "label": "right"},
{"score": 0.0834, "label": "left"},
]
self.assertIn(nested_simplify(output, decimals=4), [EXPECTED_OUTPUT, EXPECTED_OUTPUT_PT_2]) self.assertIn(nested_simplify(output, decimals=4), [EXPECTED_OUTPUT, EXPECTED_OUTPUT_PT_2])
audio_dict = {"array": np.ones((8000,)), "sampling_rate": audio_classifier.feature_extractor.sampling_rate} audio_dict = {"array": np.ones((8000,)), "sampling_rate": audio_classifier.feature_extractor.sampling_rate}