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

Pipeline testing - using tiny models on Hub (#20426)

Browse Source 
* rework pipeline tests

* run pipeline tests

* fix

* fix

* fix

* revert the changes in get_test_pipeline() parameter list

* fix expected error message

* skip a test

* clean up

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-01-30 10:39:43 +01:00
committed by GitHub
parent a582cfce3c
commit c749bd405e
26 changed files with 286 additions and 274 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
tests/pipelines/test_pipelines_audio_classification.py
View File

@@ -27,8 +27,8 @@ from .test_pipelines_common import ANY, PipelineTestCaseMeta
class AudioClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTestCaseMeta):
model_mapping = MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
def get_test_pipeline(self, model, tokenizer, feature_extractor, image_processor):
audio_classifier = AudioClassificationPipeline(model=model, feature_extractor=feature_extractor)
def get_test_pipeline(self, model, tokenizer, processor):
audio_classifier = AudioClassificationPipeline(model=model, feature_extractor=processor)
# test with a raw waveform
audio = np.zeros((34000,))