feat(server,ml): remove image tagging ()

* remove image tagging

* updated lock

* fixed tests, improved logging

* be nice

* fixed tests
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Mert 2023-12-20 20:47:56 -05:00 committed by GitHub
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commit 092a23fd7f
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65 changed files with 988 additions and 2930 deletions
machine-learning/app

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@ -17,42 +17,9 @@ from .models.base import PicklableSessionOptions
from .models.cache import ModelCache
from .models.clip import OpenCLIPEncoder
from .models.facial_recognition import FaceRecognizer
from .models.image_classification import ImageClassifier
from .schemas import ModelType
class TestImageClassifier:
classifier_preds = [
{"label": "that's an image alright", "score": 0.8},
{"label": "well it ends with .jpg", "score": 0.1},
{"label": "idk, im just seeing bytes", "score": 0.05},
{"label": "not sure", "score": 0.04},
{"label": "probably a virus", "score": 0.01},
]
def test_min_score(self, pil_image: Image.Image, mocker: MockerFixture) -> None:
mocker.patch.object(ImageClassifier, "load")
classifier = ImageClassifier("test_model_name", min_score=0.0)
assert classifier.min_score == 0.0
classifier.model = mock.Mock()
classifier.model.return_value = self.classifier_preds
all_labels = classifier.predict(pil_image)
classifier.min_score = 0.5
filtered_labels = classifier.predict(pil_image)
assert all_labels == [
"that's an image alright",
"well it ends with .jpg",
"idk",
"im just seeing bytes",
"not sure",
"probably a virus",
]
assert filtered_labels == ["that's an image alright"]
class TestCLIP:
embedding = np.random.rand(512).astype(np.float32)
cache_dir = Path("test_cache")
@ -63,11 +30,13 @@ class TestCLIP:
mocker: MockerFixture,
clip_model_cfg: dict[str, Any],
clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
) -> None:
mocker.patch.object(OpenCLIPEncoder, "download")
mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
mocker.patch("app.models.clip.AutoTokenizer.from_pretrained", autospec=True)
mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)
mocked = mocker.patch("app.models.clip.ort.InferenceSession", autospec=True)
mocked.return_value.run.return_value = [[self.embedding]]
@ -85,11 +54,13 @@ class TestCLIP:
mocker: MockerFixture,
clip_model_cfg: dict[str, Any],
clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
) -> None:
mocker.patch.object(OpenCLIPEncoder, "download")
mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
mocker.patch("app.models.clip.AutoTokenizer.from_pretrained", autospec=True)
mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)
mocked = mocker.patch("app.models.clip.ort.InferenceSession", autospec=True)
mocked.return_value.run.return_value = [[self.embedding]]
@ -145,17 +116,15 @@ class TestFaceRecognition:
class TestCache:
async def test_caches(self, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache()
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION)
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
assert len(model_cache.cache._cache) == 1
mock_get_model.assert_called_once()
async def test_kwargs_used(self, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache()
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION, cache_dir="test_cache")
mock_get_model.assert_called_once_with(
ModelType.IMAGE_CLASSIFICATION, "test_model_name", cache_dir="test_cache"
)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, cache_dir="test_cache")
mock_get_model.assert_called_once_with(ModelType.FACIAL_RECOGNITION, "test_model_name", cache_dir="test_cache")
async def test_different_clip(self, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache()
@ -172,14 +141,14 @@ class TestCache:
@mock.patch("app.models.cache.OptimisticLock", autospec=True)
async def test_model_ttl(self, mock_lock_cls: mock.Mock, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache(ttl=100)
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
mock_lock_cls.return_value.__aenter__.return_value.cas.assert_called_with(mock.ANY, ttl=100)
@mock.patch("app.models.cache.SimpleMemoryCache.expire")
async def test_revalidate(self, mock_cache_expire: mock.Mock, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache(ttl=100, revalidate=True)
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION)
await model_cache.get("test_model_name", ModelType.IMAGE_CLASSIFICATION)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
mock_cache_expire.assert_called_once_with(mock.ANY, 100)
@ -188,23 +157,6 @@ class TestCache:
reason="More time-consuming since it deploys the app and loads models.",
)
class TestEndpoints:
def test_tagging_endpoint(
self, pil_image: Image.Image, responses: dict[str, Any], deployed_app: TestClient
) -> None:
byte_image = BytesIO()
pil_image.save(byte_image, format="jpeg")
response = deployed_app.post(
"http://localhost:3003/predict",
data={
"modelName": "microsoft/resnet-50",
"modelType": "image-classification",
"options": json.dumps({"minScore": 0.0}),
},
files={"image": byte_image.getvalue()},
)
assert response.status_code == 200
assert response.json() == responses["image-classification"]
def test_clip_image_endpoint(
self, pil_image: Image.Image, responses: dict[str, Any], deployed_app: TestClient
) -> None: