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mirror of https://github.com/immich-app/immich.git synced 2024-12-23 02:06:15 +02:00
immich/machine-learning/app/conftest.py
Mert 87a0ba3db3
feat(ml): export clip models to ONNX and host models on Hugging Face (#4700)
* export clip models

* export to hf

refactored export code

* export mclip, general refactoring

cleanup

* updated conda deps

* do transforms with pillow and numpy, add tokenization config to export, general refactoring

* moved conda dockerfile, re-added poetry

* minor fixes

* updated link

* updated tests

* removed `requirements.txt` from workflow

* fixed mimalloc path

* removed torchvision

* cleaner np typing

* review suggestions

* update default model name

* update test
2023-10-31 05:02:04 -05:00

62 lines
1.5 KiB
Python

import json
from pathlib import Path
from typing import Any, Iterator
from unittest import mock
import numpy as np
import pytest
from fastapi.testclient import TestClient
from PIL import Image
from .main import app, init_state
from .schemas import ndarray_f32
@pytest.fixture
def pil_image() -> Image.Image:
return Image.new("RGB", (600, 800))
@pytest.fixture
def cv_image(pil_image: Image.Image) -> ndarray_f32:
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")
def deployed_app() -> TestClient:
init_state()
return TestClient(app)
@pytest.fixture(scope="session")
def responses() -> dict[str, Any]:
return json.load(open("responses.json", "r"))
@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,
}