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chore(ml): installable package (#17153)

Browse Source 
* app -> immich_ml

* fix test ci

* omit file name

* add new line

* add new line
This commit is contained in:
Mert 2025-03-27 15:49:09 -04:00 committed by GitHub
parent f7d730eb05
commit 84c35e35d6
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31 changed files with 347 additions and 316 deletions
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8
.github/workflows/test.yml vendored
View File

@ -395,16 +395,16 @@ jobs:
uv sync --extra cpu
- name: Lint with ruff
run: |
uv run ruff check --output-format=github app
uv run ruff check --output-format=github immich_ml
- name: Check black formatting
run: |
uv run black --check app
uv run black --check immich_ml
- name: Run mypy type checking
run: |
uv run mypy --strict app/
uv run mypy --strict immich_ml/
- name: Run tests and coverage
run: |
uv run pytest app --cov=app --cov-report term-missing
uv run pytest --cov=immich_ml --cov-report term-missing
github-files-formatting:
name: .github Files Formatting

22
machine-learning/Dockerfile
View File

@ -51,7 +51,6 @@ ARG DEVICE
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
VIRTUAL_ENV=/opt/venv
WORKDIR /usr/src/app
RUN apt-get update && apt-get install -y --no-install-recommends g++
@ -66,6 +65,8 @@ RUN if [ "$DEVICE" = "rocm" ]; then \
FROM python:3.11-slim-bookworm@sha256:7029b00486ac40bed03e36775b864d3f3d39dcbdf19cd45e6a52d541e6c178f0 AS prod-cpu
ENV LD_PRELOAD=/usr/lib/libmimalloc.so.2
FROM prod-cpu AS prod-openvino
RUN apt-get update && \
@ -94,7 +95,8 @@ FROM rocm/dev-ubuntu-22.04:6.3.4-complete@sha256:1f7e92ca7e3a3785680473329ed1091
FROM prod-cpu AS prod-armnn
ENV LD_LIBRARY_PATH=/opt/armnn
ENV LD_LIBRARY_PATH=/opt/armnn \
LD_PRELOAD=/usr/lib/libmimalloc.so.2
RUN apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopencl1 mesa-opencl-icd libgomp1 && \
rm -rf /var/lib/apt/lists/* && \
@ -114,6 +116,8 @@ COPY --from=builder-armnn \
FROM prod-cpu AS prod-rknn
ENV LD_PRELOAD=/usr/lib/libmimalloc.so.2
ADD --checksum=sha256:73993ed4b440460825f21611731564503cc1d5a0c123746477da6cd574f34885 https://github.com/airockchip/rknn-toolkit2/raw/refs/tags/v2.3.0/rknpu2/runtime/Linux/librknn_api/aarch64/librknnrt.so /usr/lib/
FROM prod-${DEVICE} AS prod
@ -126,14 +130,18 @@ RUN apt-get update && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
WORKDIR /usr/src/app
RUN ln -s "/usr/lib/$(arch)-linux-gnu/libmimalloc.so.2" /usr/lib/libmimalloc.so.2
WORKDIR /usr/src
ENV TRANSFORMERS_CACHE=/cache \
PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
PATH="/opt/venv/bin:$PATH" \
PYTHONPATH=/usr/src \
DEVICE=${DEVICE} \
VIRTUAL_ENV=/opt/venv
VIRTUAL_ENV=/opt/venv \
LD_BIND_NOW=1 \
MACHINE_LEARNING_CACHE_FOLDER=/cache
# prevent core dumps
RUN echo "hard core 0" >> /etc/security/limits.conf && \
@ -141,9 +149,7 @@ RUN echo "hard core 0" >> /etc/security/limits.conf && \
echo 'ulimit -S -c 0 > /dev/null 2>&1' >> /etc/profile
COPY --from=builder /opt/venv /opt/venv
COPY ann/ann.py /usr/src/ann/ann.py
COPY start.sh log_conf.json gunicorn_conf.py ./
COPY app .
COPY immich_ml immich_ml
ARG BUILD_ID
ARG BUILD_IMAGE
@ -161,6 +167,6 @@ ENV IMMICH_SOURCE_COMMIT=${BUILD_SOURCE_COMMIT}
ENV IMMICH_SOURCE_URL=https://github.com/immich-app/immich/commit/${BUILD_SOURCE_COMMIT}
ENTRYPOINT ["tini", "--"]
CMD ["./start.sh"]
CMD ["python", "-m", "immich_ml"]
HEALTHCHECK CMD python3 healthcheck.py

23
machine-learning/app/conftest.py → machine-learning/conftest.py
View File

@ -8,9 +8,8 @@ from fastapi.testclient import TestClient
from numpy.typing import NDArray
from PIL import Image
from app.config import log
from .main import app
from immich_ml.config import log
from immich_ml.main import app
@pytest.fixture
@ -25,7 +24,7 @@ def cv_image(pil_image: Image.Image) -> NDArray[np.float32]:
@pytest.fixture
def mock_get_model() -> Iterator[mock.Mock]:
with mock.patch("app.models.cache.from_model_type", autospec=True) as mocked:
with mock.patch("immich_ml.models.cache.from_model_type", autospec=True) as mocked:
yield mocked
@ -104,14 +103,14 @@ def providers(request: pytest.FixtureRequest) -> Iterator[mock.Mock]:
raise ValueError("Missing marker 'providers'")
providers = marker.args[0]
with mock.patch("app.sessions.ort.ort.get_available_providers") as mocked:
with mock.patch("immich_ml.sessions.ort.ort.get_available_providers") as mocked:
mocked.return_value = providers
yield providers
@pytest.fixture(scope="function")
def ort_pybind() -> Iterator[mock.Mock]:
with mock.patch("app.sessions.ort.ort.capi._pybind_state") as mocked:
with mock.patch("immich_ml.sessions.ort.ort.capi._pybind_state") as mocked:
yield mocked
@ -126,25 +125,25 @@ def ov_device_ids(request: pytest.FixtureRequest, ort_pybind: mock.Mock) -> Iter
@pytest.fixture(scope="function")
def ort_session() -> Iterator[mock.Mock]:
with mock.patch("app.sessions.ort.ort.InferenceSession") as mocked:
with mock.patch("immich_ml.sessions.ort.ort.InferenceSession") as mocked:
yield mocked
@pytest.fixture(scope="function")
def ann_session() -> Iterator[mock.Mock]:
with mock.patch("app.sessions.ann.Ann") as mocked:
with mock.patch("immich_ml.sessions.ann.Ann") as mocked:
yield mocked
@pytest.fixture(scope="function")
def rknn_session() -> Iterator[mock.Mock]:
with mock.patch("app.sessions.rknn.RknnPoolExecutor") as mocked:
with mock.patch("immich_ml.sessions.rknn.RknnPoolExecutor") as mocked:
yield mocked
@pytest.fixture(scope="function")
def rmtree() -> Iterator[mock.Mock]:
with mock.patch("app.models.base.rmtree", autospec=True) as mocked:
with mock.patch("immich_ml.models.base.rmtree", autospec=True) as mocked:
mocked.avoids_symlink_attacks = True
yield mocked
@ -158,7 +157,7 @@ def path() -> Iterator[mock.Mock]:
path.with_suffix.return_value = path
path.return_value = path
with mock.patch("app.models.base.Path", return_value=path) as mocked:
with mock.patch("immich_ml.models.base.Path", return_value=path) as mocked:
yield mocked
@ -182,5 +181,5 @@ def exception() -> Iterator[mock.Mock]:
@pytest.fixture(scope="function")
def snapshot_download() -> Iterator[mock.Mock]:
with mock.patch("app.models.base.snapshot_download") as mocked:
with mock.patch("immich_ml.models.base.snapshot_download") as mocked:
yield mocked

0
machine-learning/app/__init__.py → machine-learning/immich_ml/__init__.py
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43
machine-learning/immich_ml/__main__.py Normal file
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@ -0,0 +1,43 @@
import os
import signal
import subprocess
from pathlib import Path
from .config import log, non_prefixed_settings, settings
if source_ref := os.getenv("IMMICH_SOURCE_REF"):
log.info(f"Initializing Immich ML [{source_ref}]")
else:
log.info("Initializing Immich ML")
module_dir = Path(__file__).parent
try:
with subprocess.Popen(
[
"python",
"-m",
"gunicorn",
"immich_ml.main:app",
"-k",
"immich_ml.config.CustomUvicornWorker",
"-c",
module_dir / "gunicorn_conf.py",
"-b",
f"{non_prefixed_settings.immich_host}:{non_prefixed_settings.immich_port}",
"-w",
str(settings.workers),
"-t",
str(settings.worker_timeout),
"--log-config-json",
module_dir / "log_conf.json",
"--keep-alive",
str(settings.http_keepalive_timeout_s),
"--graceful-timeout",
"10",
],
) as cmd:
cmd.wait()
except KeyboardInterrupt:
cmd.send_signal(signal.SIGINT)
exit(cmd.returncode)

16
machine-learning/app/config.py → machine-learning/immich_ml/config.py
View File

@ -51,12 +51,12 @@ class Settings(BaseSettings):
protected_namespaces=("settings_",),
)
cache_folder: Path = Path("/cache")
cache_folder: Path = (Path.home() / ".cache" / "immich_ml").resolve()
model_ttl: int = 300
model_ttl_poll_s: int = 10
host: str = "0.0.0.0"
port: int = 3003
workers: int = 1
worker_timeout: int = 300
http_keepalive_timeout_s: int = 2
test_full: bool = False
request_threads: int = os.cpu_count() or 4
model_inter_op_threads: int = 0
@ -74,9 +74,11 @@ class Settings(BaseSettings):
return os.environ.get("MACHINE_LEARNING_DEVICE_ID", "0")
class LogSettings(BaseSettings):
class NonPrefixedSettings(BaseSettings):
model_config = SettingsConfigDict(case_sensitive=False)
immich_host: str = "[::]"
immich_port: int = 3003
immich_log_level: str = "info"
no_color: bool = False
@ -100,14 +102,14 @@ LOG_LEVELS: dict[str, int] = {
}
settings = Settings()
log_settings = LogSettings()
non_prefixed_settings = NonPrefixedSettings()
LOG_LEVEL = LOG_LEVELS.get(log_settings.immich_log_level.lower(), logging.INFO)
LOG_LEVEL = LOG_LEVELS.get(non_prefixed_settings.immich_log_level.lower(), logging.INFO)
class CustomRichHandler(RichHandler):
def __init__(self) -> None:
console = Console(color_system="standard", no_color=log_settings.no_color)
console = Console(color_system="standard", no_color=non_prefixed_settings.no_color)
self.excluded = ["uvicorn", "starlette", "fastapi"]
super().__init__(
show_path=False,

0
machine-learning/gunicorn_conf.py → machine-learning/immich_ml/gunicorn_conf.py
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21
machine-learning/immich_ml/log_conf.json Normal file
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@ -0,0 +1,21 @@
{
"version": 1,
"disable_existing_loggers": false,
"handlers": {
"console": {
"class": "immich_ml.config.CustomRichHandler"
}
},
"loggers": {
"gunicorn.error": {
"handlers": [
"console"
]
}
},
"root": {
"handlers": [
"console"
]
}
}

6
machine-learning/app/main.py → machine-learning/immich_ml/main.py
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@ -18,9 +18,9 @@ from PIL.Image import Image
from pydantic import ValidationError
from starlette.formparsers import MultiPartParser
from app.models import get_model_deps
from app.models.base import InferenceModel
from app.models.transforms import decode_pil
from immich_ml.models import get_model_deps
from immich_ml.models.base import InferenceModel
from immich_ml.models.transforms import decode_pil
from .config import PreloadModelData, log, settings
from .models.cache import ModelCache

8
machine-learning/app/models/__init__.py → machine-learning/immich_ml/models/__init__.py
View File

@ -1,9 +1,9 @@
from typing import Any
from app.models.base import InferenceModel
from app.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
from app.models.clip.visual import OpenClipVisualEncoder
from app.schemas import ModelSource, ModelTask, ModelType
from immich_ml.models.base import InferenceModel
from immich_ml.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
from immich_ml.models.clip.visual import OpenClipVisualEncoder
from immich_ml.schemas import ModelSource, ModelTask, ModelType
from .constants import get_model_source
from .facial_recognition.detection import FaceDetector

8
machine-learning/app/models/base.py → machine-learning/immich_ml/models/base.py
View File

@ -7,9 +7,9 @@ from typing import Any, ClassVar
from huggingface_hub import snapshot_download
import ann.ann
import app.sessions.rknn as rknn
from app.sessions.ort import OrtSession
import immich_ml.sessions.ann.loader
import immich_ml.sessions.rknn as rknn
from immich_ml.sessions.ort import OrtSession
from ..config import clean_name, log, settings
from ..schemas import ModelFormat, ModelIdentity, ModelSession, ModelTask, ModelType
@ -171,7 +171,7 @@ class InferenceModel(ABC):
def _model_format_default(self) -> ModelFormat:
if rknn.is_available:
return ModelFormat.RKNN
elif ann.ann.is_available and settings.ann:
elif immich_ml.sessions.ann.loader.is_available and settings.ann:
return ModelFormat.ARMNN
else:
return ModelFormat.ONNX

4
machine-learning/app/models/cache.py → machine-learning/immich_ml/models/cache.py
View File

@ -4,8 +4,8 @@ from aiocache.backends.memory import SimpleMemoryCache
from aiocache.lock import OptimisticLock
from aiocache.plugins import TimingPlugin
from app.models import from_model_type
from app.models.base import InferenceModel
from immich_ml.models import from_model_type
from immich_ml.models.base import InferenceModel
from ..schemas import ModelTask, ModelType, has_profiling

8
machine-learning/app/models/clip/textual.py → machine-learning/immich_ml/models/clip/textual.py
View File

@ -8,10 +8,10 @@ import numpy as np
from numpy.typing import NDArray
from tokenizers import Encoding, Tokenizer
from app.config import log
from app.models.base import InferenceModel
from app.models.transforms import clean_text, serialize_np_array
from app.schemas import ModelSession, ModelTask, ModelType
from immich_ml.config import log
from immich_ml.models.base import InferenceModel
from immich_ml.models.transforms import clean_text, serialize_np_array
from immich_ml.schemas import ModelSession, ModelTask, ModelType
class BaseCLIPTextualEncoder(InferenceModel):

8
machine-learning/app/models/clip/visual.py → machine-learning/immich_ml/models/clip/visual.py
View File

@ -8,9 +8,9 @@ import numpy as np
from numpy.typing import NDArray
from PIL import Image
from app.config import log
from app.models.base import InferenceModel
from app.models.transforms import (
from immich_ml.config import log
from immich_ml.models.base import InferenceModel
from immich_ml.models.transforms import (
crop_pil,
decode_pil,
get_pil_resampling,
@ -19,7 +19,7 @@ from app.models.transforms import (
serialize_np_array,
to_numpy,
)
from app.schemas import ModelSession, ModelTask, ModelType
from immich_ml.schemas import ModelSession, ModelTask, ModelType
class BaseCLIPVisualEncoder(InferenceModel):

4
machine-learning/app/models/constants.py → machine-learning/immich_ml/models/constants.py
View File

@ -1,5 +1,5 @@
from app.config import clean_name
from app.schemas import ModelSource
from immich_ml.config import clean_name
from immich_ml.schemas import ModelSource
_OPENCLIP_MODELS = {
"RN101__openai",

6
machine-learning/app/models/facial_recognition/detection.py → machine-learning/immich_ml/models/facial_recognition/detection.py
View File

@ -4,9 +4,9 @@ import numpy as np
from insightface.model_zoo import RetinaFace
from numpy.typing import NDArray
from app.models.base import InferenceModel
from app.models.transforms import decode_cv2
from app.schemas import FaceDetectionOutput, ModelSession, ModelTask, ModelType
from immich_ml.models.base import InferenceModel
from immich_ml.models.transforms import decode_cv2
from immich_ml.schemas import FaceDetectionOutput, ModelSession, ModelTask, ModelType
class FaceDetector(InferenceModel):

15
machine-learning/app/models/facial_recognition/recognition.py → machine-learning/immich_ml/models/facial_recognition/recognition.py
View File

@ -10,10 +10,17 @@ from numpy.typing import NDArray
from onnx.tools.update_model_dims import update_inputs_outputs_dims
from PIL import Image
from app.config import log, settings
from app.models.base import InferenceModel
from app.models.transforms import decode_cv2, serialize_np_array
from app.schemas import FaceDetectionOutput, FacialRecognitionOutput, ModelFormat, ModelSession, ModelTask, ModelType
from immich_ml.config import log, settings
from immich_ml.models.base import InferenceModel
from immich_ml.models.transforms import decode_cv2, serialize_np_array
from immich_ml.schemas import (
FaceDetectionOutput,
FacialRecognitionOutput,
ModelFormat,
ModelSession,
ModelTask,
ModelType,
)
class FaceRecognizer(InferenceModel):

0
machine-learning/app/models/transforms.py → machine-learning/immich_ml/models/transforms.py
View File

0
machine-learning/app/schemas.py → machine-learning/immich_ml/schemas.py
View File

0
machine-learning/app/sessions/__init__.py → machine-learning/immich_ml/sessions/__init__.py
View File

6
machine-learning/app/sessions/ann.py → machine-learning/immich_ml/sessions/ann/__init__.py
View File

@ -6,10 +6,10 @@ from typing import Any, NamedTuple
import numpy as np
from numpy.typing import NDArray
from ann.ann import Ann
from app.schemas import SessionNode
from immich_ml.config import log, settings
from immich_ml.schemas import SessionNode
from ..config import log, settings
from .loader import Ann
class AnnSession:

2
machine-learning/ann/ann.py → machine-learning/immich_ml/sessions/ann/loader.py
View File

@ -7,7 +7,7 @@ from typing import Any, Protocol, TypeVar
import numpy as np
from numpy.typing import NDArray
from app.config import log
from immich_ml.config import log
try:
CDLL("libmali.so") # fail if libmali.so is not mounted into container

4
machine-learning/app/sessions/ort.py → machine-learning/immich_ml/sessions/ort.py
View File

@ -7,8 +7,8 @@ import numpy as np
import onnxruntime as ort
from numpy.typing import NDArray
from app.models.constants import SUPPORTED_PROVIDERS
from app.schemas import SessionNode
from immich_ml.models.constants import SUPPORTED_PROVIDERS
from immich_ml.schemas import SessionNode
from ..config import log, settings

4
machine-learning/app/sessions/rknn/__init__.py → machine-learning/immich_ml/sessions/rknn/__init__.py
View File

@ -6,8 +6,8 @@ from typing import Any, NamedTuple
import numpy as np
from numpy.typing import NDArray
from app.config import log, settings
from app.schemas import SessionNode
from immich_ml.config import log, settings
from immich_ml.schemas import SessionNode
from .rknnpool import RknnPoolExecutor, is_available, soc_name

4
machine-learning/app/sessions/rknn/rknnpool.py → machine-learning/immich_ml/sessions/rknn/rknnpool.py
View File

@ -10,8 +10,8 @@ from typing import Callable
import numpy as np
from numpy.typing import NDArray
from app.config import log
from app.models.constants import RKNN_COREMASK_SUPPORTED_SOCS, RKNN_SUPPORTED_SOCS
from immich_ml.config import log
from immich_ml.models.constants import RKNN_COREMASK_SUPPORTED_SOCS, RKNN_SUPPORTED_SOCS
def get_soc(device_tree_path: Path | str) -> str | None:

15
machine-learning/log_conf.json
View File

@ -1,15 +0,0 @@
{
"version": 1,
"disable_existing_loggers": false,
"handlers": {
"console": {
"class": "app.config.CustomRichHandler"
}
},
"loggers": {
"gunicorn.error": {
"handlers": ["console"]
}
},
"root": { "handlers": ["console"] }
}

6
machine-learning/pyproject.toml
View File

@ -1,5 +1,5 @@
[project]
name = "machine-learning"
name = "immich-ml"
version = "1.129.0"
description = ""
authors = [{ name = "Hau Tran", email = "alex.tran1502@gmail.com" }]
@ -66,10 +66,10 @@ explicit = true
onnxruntime-gpu = { index = "cuda12" }
[tool.hatch.build.targets.sdist]
include = ["app"]
include = ["immich_ml"]
[tool.hatch.build.targets.wheel]
include = ["app"]
include = ["immich_ml"]
[build-system]
requires = ["hatchling"]

0
machine-learning/app/healthcheck.py → machine-learning/scripts/healthcheck.py
View File

31
machine-learning/start.sh
View File

@ -1,31 +0,0 @@
#!/usr/bin/env sh
echo "Initializing Immich ML $IMMICH_SOURCE_REF"
if ! [ "$DEVICE" = "openvino" ]; then
: "${MACHINE_LEARNING_WORKER_TIMEOUT:=120}"
else
: "${MACHINE_LEARNING_WORKER_TIMEOUT:=300}"
fi
# mimalloc seems to increase memory usage dramatically with openvino, need to investigate
if ! [ "$DEVICE" = "openvino" ] && ! [ "$DEVICE" = "rocm" ]; then
lib_path="/usr/lib/$(arch)-linux-gnu/libmimalloc.so.2"
export LD_PRELOAD="$lib_path"
export LD_BIND_NOW=1
fi
: "${IMMICH_HOST:=[::]}"
: "${IMMICH_PORT:=3003}"
: "${MACHINE_LEARNING_WORKERS:=1}"
: "${MACHINE_LEARNING_HTTP_KEEPALIVE_TIMEOUT_S:=2}"
gunicorn app.main:app \
-k app.config.CustomUvicornWorker \
-c gunicorn_conf.py \
-b "$IMMICH_HOST":"$IMMICH_PORT" \
-w "$MACHINE_LEARNING_WORKERS" \
-t "$MACHINE_LEARNING_WORKER_TIMEOUT" \
--log-config-json log_conf.json \
--keep-alive "$MACHINE_LEARNING_HTTP_KEEPALIVE_TIMEOUT_S" \
--graceful-timeout 0

91
machine-learning/app/test_main.py → machine-learning/test_main.py
View File

@ -18,19 +18,18 @@ from PIL import Image
from pytest import MonkeyPatch
from pytest_mock import MockerFixture
from app.main import load, preload_models
from app.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
from app.models.clip.visual import OpenClipVisualEncoder
from app.models.facial_recognition.detection import FaceDetector
from app.models.facial_recognition.recognition import FaceRecognizer
from app.sessions.ann import AnnSession
from app.sessions.ort import OrtSession
from app.sessions.rknn import RknnSession, run_inference
from .config import Settings, settings
from .models.base import InferenceModel
from .models.cache import ModelCache
from .schemas import ModelFormat, ModelTask, ModelType
from immich_ml.config import Settings, settings
from immich_ml.main import load, preload_models
from immich_ml.models.base import InferenceModel
from immich_ml.models.cache import ModelCache
from immich_ml.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
from immich_ml.models.clip.visual import OpenClipVisualEncoder
from immich_ml.models.facial_recognition.detection import FaceDetector
from immich_ml.models.facial_recognition.recognition import FaceRecognizer
from immich_ml.schemas import ModelFormat, ModelTask, ModelType
from immich_ml.sessions.ann import AnnSession
from immich_ml.sessions.ort import OrtSession
from immich_ml.sessions.rknn import RknnSession, run_inference
class TestBase:
@ -47,7 +46,7 @@ class TestBase:
def test_sets_default_model_format(self, mocker: MockerFixture) -> None:
mocker.patch.object(settings, "ann", True)
mocker.patch("ann.ann.is_available", False)
mocker.patch("immich_ml.sessions.ann.loader.is_available", False)
encoder = OpenClipTextualEncoder("ViT-B-32__openai")
@ -55,7 +54,7 @@ class TestBase:
def test_sets_default_model_format_to_armnn_if_available(self, path: mock.Mock, mocker: MockerFixture) -> None:
mocker.patch.object(settings, "ann", True)
mocker.patch("ann.ann.is_available", True)
mocker.patch("immich_ml.sessions.ann.loader.is_available", True)
path.suffix = ".armnn"
encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=path)
@ -64,7 +63,7 @@ class TestBase:
def test_sets_model_format_kwarg(self, mocker: MockerFixture) -> None:
mocker.patch.object(settings, "ann", False)
mocker.patch("ann.ann.is_available", False)
mocker.patch("immich_ml.sessions.ann.loader.is_available", False)
encoder = OpenClipTextualEncoder("ViT-B-32__openai", model_format=ModelFormat.ARMNN)
@ -72,7 +71,7 @@ class TestBase:
def test_sets_default_model_format_to_rknn_if_available(self, mocker: MockerFixture) -> None:
mocker.patch.object(settings, "rknn", True)
mocker.patch("app.sessions.rknn.is_available", True)
mocker.patch("immich_ml.sessions.rknn.is_available", True)
encoder = OpenClipTextualEncoder("ViT-B-32__openai")
@ -294,7 +293,7 @@ class TestOrtSession:
assert session.sess_options.intra_op_num_threads == 0
def test_sets_default_sess_options_sets_threads_if_non_cpu_and_set_threads(self, mocker: MockerFixture) -> None:
mock_settings = mocker.patch("app.sessions.ort.settings", autospec=True)
mock_settings = mocker.patch("immich_ml.sessions.ort.settings", autospec=True)
mock_settings.model_inter_op_threads = 2
mock_settings.model_intra_op_threads = 4
@ -373,8 +372,8 @@ class TestRknnSession:
def test_creates_rknn_session(self, rknn_session: mock.Mock, info: mock.Mock, mocker: MockerFixture) -> None:
model_path = mock.MagicMock(spec=Path)
tpe = 1
mocker.patch("app.sessions.rknn.soc_name", "rk3566")
mocker.patch("app.sessions.rknn.is_available", True)
mocker.patch("immich_ml.sessions.rknn.soc_name", "rk3566")
mocker.patch("immich_ml.sessions.rknn.is_available", True)
RknnSession(model_path)
rknn_session.assert_called_once_with(model_path=model_path.as_posix(), tpes=tpe, func=run_inference)
@ -384,7 +383,7 @@ class TestRknnSession:
def test_run_rknn(self, rknn_session: mock.Mock, mocker: MockerFixture) -> None:
rknn_session.return_value.load.return_value = 123
np_spy = mocker.spy(np, "ascontiguousarray")
mocker.patch("app.sessions.rknn.soc_name", "rk3566")
mocker.patch("immich_ml.sessions.rknn.soc_name", "rk3566")
session = RknnSession(Path("ViT-B-32__openai"))
[input1, input2] = [np.random.rand(1, 3, 224, 224).astype(np.float32) for _ in range(2)]
input_feed = {"input.1": input1, "input.2": input2}
@ -434,7 +433,7 @@ class TestCLIP:
mocked = mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
mocked.run.return_value = [[self.embedding]]
mocker.patch("app.models.clip.textual.Tokenizer.from_file", autospec=True)
mocker.patch("immich_ml.models.clip.textual.Tokenizer.from_file", autospec=True)
clip_encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache")
embedding_str = clip_encoder.predict("test search query")
@ -454,7 +453,7 @@ class TestCLIP:
mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
mock_tokenizer = mocker.patch("app.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_tokenizer = mocker.patch("immich_ml.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_ids = [randint(0, 50000) for _ in range(77)]
mock_tokenizer.encode.return_value = SimpleNamespace(ids=mock_ids)
@ -480,7 +479,7 @@ class TestCLIP:
mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
mock_tokenizer = mocker.patch("app.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_tokenizer = mocker.patch("immich_ml.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_ids = [randint(0, 50000) for _ in range(77)]
mock_tokenizer.encode.return_value = SimpleNamespace(ids=mock_ids)
@ -505,7 +504,7 @@ class TestCLIP:
mocker.patch.object(MClipTextualEncoder, "model_cfg", clip_model_cfg)
mocker.patch.object(MClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
mock_tokenizer = mocker.patch("app.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_tokenizer = mocker.patch("immich_ml.models.clip.textual.Tokenizer.from_file", autospec=True).return_value
mock_ids = [randint(0, 50000) for _ in range(77)]
mock_attention_mask = [randint(0, 1) for _ in range(77)]
mock_tokenizer.encode.return_value = SimpleNamespace(ids=mock_ids, attention_mask=mock_attention_mask)
@ -597,12 +596,12 @@ class TestFaceRecognition:
def test_recognition_adds_batch_axis_for_ort(
self, ort_session: mock.Mock, path: mock.Mock, mocker: MockerFixture
) -> None:
onnx = mocker.patch("app.models.facial_recognition.recognition.onnx", autospec=True)
onnx = mocker.patch("immich_ml.models.facial_recognition.recognition.onnx", autospec=True)
update_dims = mocker.patch(
"app.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
"immich_ml.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
)
mocker.patch("app.models.base.InferenceModel.download")
mocker.patch("app.models.facial_recognition.recognition.ArcFaceONNX")
mocker.patch("immich_ml.models.base.InferenceModel.download")
mocker.patch("immich_ml.models.facial_recognition.recognition.ArcFaceONNX")
ort_session.return_value.get_inputs.return_value = [SimpleNamespace(name="input.1", shape=(1, 3, 224, 224))]
ort_session.return_value.get_outputs.return_value = [SimpleNamespace(name="output.1", shape=(1, 800))]
path.return_value.__truediv__.return_value.__truediv__.return_value.suffix = ".onnx"
@ -631,12 +630,12 @@ class TestFaceRecognition:
def test_recognition_does_not_add_batch_axis_if_exists(
self, ort_session: mock.Mock, path: mock.Mock, mocker: MockerFixture
) -> None:
onnx = mocker.patch("app.models.facial_recognition.recognition.onnx", autospec=True)
onnx = mocker.patch("immich_ml.models.facial_recognition.recognition.onnx", autospec=True)
update_dims = mocker.patch(
"app.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
"immich_ml.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
)
mocker.patch("app.models.base.InferenceModel.download")
mocker.patch("app.models.facial_recognition.recognition.ArcFaceONNX")
mocker.patch("immich_ml.models.base.InferenceModel.download")
mocker.patch("immich_ml.models.facial_recognition.recognition.ArcFaceONNX")
path.return_value.__truediv__.return_value.__truediv__.return_value.suffix = ".onnx"
inputs = [SimpleNamespace(name="input.1", shape=("batch", 3, 224, 224))]
@ -655,12 +654,12 @@ class TestFaceRecognition:
def test_recognition_does_not_add_batch_axis_for_armnn(
self, ann_session: mock.Mock, path: mock.Mock, mocker: MockerFixture
) -> None:
onnx = mocker.patch("app.models.facial_recognition.recognition.onnx", autospec=True)
onnx = mocker.patch("immich_ml.models.facial_recognition.recognition.onnx", autospec=True)
update_dims = mocker.patch(
"app.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
"immich_ml.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
)
mocker.patch("app.models.base.InferenceModel.download")
mocker.patch("app.models.facial_recognition.recognition.ArcFaceONNX")
mocker.patch("immich_ml.models.base.InferenceModel.download")
mocker.patch("immich_ml.models.facial_recognition.recognition.ArcFaceONNX")
path.return_value.__truediv__.return_value.__truediv__.return_value.suffix = ".armnn"
inputs = [SimpleNamespace(name="input.1", shape=("batch", 3, 224, 224))]
@ -679,12 +678,12 @@ class TestFaceRecognition:
def test_recognition_does_not_add_batch_axis_for_openvino(
self, ort_session: mock.Mock, path: mock.Mock, mocker: MockerFixture
) -> None:
onnx = mocker.patch("app.models.facial_recognition.recognition.onnx", autospec=True)
onnx = mocker.patch("immich_ml.models.facial_recognition.recognition.onnx", autospec=True)
update_dims = mocker.patch(
"app.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
"immich_ml.models.facial_recognition.recognition.update_inputs_outputs_dims", autospec=True
)
mocker.patch("app.models.base.InferenceModel.download")
mocker.patch("app.models.facial_recognition.recognition.ArcFaceONNX")
mocker.patch("immich_ml.models.base.InferenceModel.download")
mocker.patch("immich_ml.models.facial_recognition.recognition.ArcFaceONNX")
path.return_value.__truediv__.return_value.__truediv__.return_value.suffix = ".onnx"
inputs = [SimpleNamespace(name="input.1", shape=("batch", 3, 224, 224))]
@ -733,13 +732,13 @@ class TestCache:
)
assert len(model_cache.cache._cache) == 2
@mock.patch("app.models.cache.OptimisticLock", autospec=True)
@mock.patch("immich_ml.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()
await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
mock_lock_cls.return_value.__aenter__.return_value.cas.assert_called_with(mock.ANY, ttl=100)
@mock.patch("app.models.cache.SimpleMemoryCache.expire")
@mock.patch("immich_ml.models.cache.SimpleMemoryCache.expire")
async def test_revalidate_get(self, mock_cache_expire: mock.Mock, mock_get_model: mock.Mock) -> None:
model_cache = ModelCache(revalidate=True)
await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
@ -784,7 +783,7 @@ class TestCache:
assert settings.preload.clip.visual == "ViT-B-32__openai"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)
monkeypatch.setattr("immich_ml.main.model_cache", model_cache)
await preload_models(settings.preload)
mock_get_model.assert_has_calls(
@ -807,7 +806,7 @@ class TestCache:
assert settings.preload.facial_recognition.recognition == "buffalo_s"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)
monkeypatch.setattr("immich_ml.main.model_cache", model_cache)
await preload_models(settings.preload)
mock_get_model.assert_has_calls(
@ -832,7 +831,7 @@ class TestCache:
assert settings.preload.facial_recognition.detection == "buffalo_s"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)
monkeypatch.setattr("immich_ml.main.model_cache", model_cache)
await preload_models(settings.preload)
mock_get_model.assert_has_calls(

298
machine-learning/uv.lock generated
View File

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