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fixed tests (#5017)

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Mert 2023-11-13 14:37:39 -05:00 committed by GitHub
parent 464cf903f4
commit 291159e7fc
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1 changed files with 9 additions and 9 deletions
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18
machine-learning/app/test_main.py
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@ -75,9 +75,9 @@ class TestCLIP:
embedding = clip_encoder.predict(pil_image)
assert clip_encoder.mode == "vision"
assert isinstance(embedding, list)
assert len(embedding) == clip_model_cfg["embed_dim"]
assert all([isinstance(num, float) for num in embedding])
assert isinstance(embedding, np.ndarray)
assert embedding.shape[0] == clip_model_cfg["embed_dim"]
assert embedding.dtype == np.float32
clip_encoder.vision_model.run.assert_called_once()
def test_basic_text(
@ -97,9 +97,9 @@ class TestCLIP:
embedding = clip_encoder.predict("test search query")
assert clip_encoder.mode == "text"
assert isinstance(embedding, list)
assert len(embedding) == clip_model_cfg["embed_dim"]
assert all([isinstance(num, float) for num in embedding])
assert isinstance(embedding, np.ndarray)
assert embedding.shape[0] == clip_model_cfg["embed_dim"]
assert embedding.dtype == np.float32
clip_encoder.text_model.run.assert_called_once()
@ -133,9 +133,9 @@ class TestFaceRecognition:
for face in faces:
assert face["imageHeight"] == 800
assert face["imageWidth"] == 600
assert isinstance(face["embedding"], list)
assert len(face["embedding"]) == 512
assert all([isinstance(num, float) for num in face["embedding"]])
assert isinstance(face["embedding"], np.ndarray)
assert face["embedding"].shape[0] == 512
assert face["embedding"].dtype == np.float32
det_model.detect.assert_called_once()
assert rec_model.get_feat.call_count == num_faces