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

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* 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
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4
tests/pipelines/test_pipelines_image_classification.py
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@@ -49,8 +49,8 @@ class ImageClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest
model_mapping = MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
tf_model_mapping = TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
def get_test_pipeline(self, model, tokenizer, feature_extractor, image_processor):
image_classifier = ImageClassificationPipeline(model=model, feature_extractor=feature_extractor, top_k=2)
def get_test_pipeline(self, model, tokenizer, processor):
image_classifier = ImageClassificationPipeline(model=model, feature_extractor=processor, top_k=2)
examples = [
Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"),
"http://images.cocodataset.org/val2017/000000039769.jpg",