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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 95cfe22866
feat(ml)!: cuda and openvino acceleration (#5619)
* cuda and openvino ep, refactor, update dockerfile

* updated workflow

* typing fixes

* added tests

* updated ml test gh action

* updated README

* updated docker-compose

* added compute to hwaccel.yml

* updated gh matrix

updated gh matrix

updated gh matrix

updated gh matrix

updated gh matrix

give up

* remove cuda/arm64 build

* add hwaccel image tags to docker-compose

* remove unnecessary quotes

* add suffix to git tag

* fixed kwargs in base model

* armnn ld_library_path

* update pyproject.toml

* add armnn workflow

* formatting

* consolidate hwaccel files, update docker compose

* update hw transcoding docs

* add ml hwaccel docs

* update dev and prod docker-compose

* added armnn prerequisite docs

* support 3.10

* updated docker-compose comments

* formatting

* test coverage

* don't set arena extend strategy for openvino

* working openvino

* formatting

* fix dockerfile

* added type annotation

* add wsl configuration for openvino

* updated lock file

* copy python3

* comment out extends section

* fix platforms

* simplify workflow suffix tagging

* simplify aio transcoding doc

* update docs and workflow for `hwaccel.yml` change

* revert docs
2024-01-21 18:22:39 -05:00

108 lines
3.0 KiB
Python

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
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")
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