immich/machine-learning/app/conftest.py

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import json
from typing import Any, Iterator
from unittest import mock
import numpy as np
import pytest
from fastapi.testclient import TestClient
from numpy.typing import NDArray
from PIL import Image
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from .main import app
@pytest.fixture
def pil_image() -> Image.Image:
return Image.new("RGB", (600, 800))
@pytest.fixture
def cv_image(pil_image: Image.Image) -> NDArray[np.float32]:
return np.asarray(pil_image)[:, :, ::-1] # PIL uses RGB while cv2 uses BGR
@pytest.fixture
def mock_get_model() -> Iterator[mock.Mock]:
with mock.patch("app.models.cache.from_model_type", autospec=True) as mocked:
yield mocked
@pytest.fixture(scope="session")
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def deployed_app() -> Iterator[TestClient]:
with TestClient(app) as client:
yield client
@pytest.fixture(scope="session")
def responses() -> dict[str, Any]:
responses: dict[str, Any] = json.load(open("responses.json", "r"))
return responses
@pytest.fixture(scope="session")
def clip_model_cfg() -> dict[str, Any]:
return {
"embed_dim": 512,
"vision_cfg": {"image_size": 224, "layers": 12, "width": 768, "patch_size": 32},
"text_cfg": {"context_length": 77, "vocab_size": 49408, "width": 512, "heads": 8, "layers": 12},
}
@pytest.fixture(scope="session")
def clip_preprocess_cfg() -> dict[str, Any]:
return {
"size": [224, 224],
"mode": "RGB",
"mean": [0.48145466, 0.4578275, 0.40821073],
"std": [0.26862954, 0.26130258, 0.27577711],
"interpolation": "bicubic",
"resize_mode": "shortest",
"fill_color": 0,
}
@pytest.fixture(scope="session")
def clip_tokenizer_cfg() -> dict[str, Any]:
return {
"add_prefix_space": False,
"added_tokens_decoder": {
"49406": {
"content": "<|startoftext|>",
"lstrip": False,
"normalized": True,
"rstrip": False,
"single_word": False,
"special": True,
},
"49407": {
"content": "<|endoftext|>",
"lstrip": False,
"normalized": True,
"rstrip": False,
"single_word": False,
"special": True,
},
},
"bos_token": "<|startoftext|>",
"clean_up_tokenization_spaces": True,
"do_lower_case": True,
"eos_token": "<|endoftext|>",
"errors": "replace",
"model_max_length": 77,
"pad_token": "<|endoftext|>",
"tokenizer_class": "CLIPTokenizer",
"unk_token": "<|endoftext|>",
}
@pytest.fixture(scope="function")
def providers(request: pytest.FixtureRequest) -> Iterator[dict[str, Any]]:
marker = request.node.get_closest_marker("providers")
if marker is None:
raise ValueError("Missing marker 'providers'")
providers = marker.args[0]
with mock.patch("app.models.base.ort.get_available_providers") as mocked:
mocked.return_value = providers
yield providers