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

.github/workflows/docker.yml

@@ -25,15 +25,38 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - context: "machine-learning"
+          - image: immich-machine-learning
-            file: "machine-learning/Dockerfile"
+            context: machine-learning
-            image: "immich-machine-learning"
+            file: machine-learning/Dockerfile
-            platforms: "linux/amd64,linux/arm64"
+            platforms: linux/amd64,linux/arm64
-          - context: "."
+            device: cpu
-            file: "server/Dockerfile"
-            image: "immich-server"
-            platforms: "linux/arm64,linux/amd64"
 
+          - image: immich-machine-learning
+            context: machine-learning
+            file: machine-learning/Dockerfile
+            platforms: linux/amd64
+            device: cuda
+            suffix: -cuda
+
+          - image: immich-machine-learning
+            context: machine-learning
+            file: machine-learning/Dockerfile
+            platforms: linux/amd64
+            device: openvino
+            suffix: -openvino
+          
+          - image: immich-machine-learning
+            context: machine-learning
+            file: machine-learning/Dockerfile
+            platforms: linux/arm64
+            device: armnn
+            suffix: -armnn
+
+          - image: immich-server
+            context: .
+            file: server/Dockerfile
+            platforms: linux/amd64,linux/arm64
+            device: cpu
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -79,12 +102,12 @@ jobs:
             name=altran1502/${{matrix.image}},enable=${{ github.event_name == 'release' }}
           tags: |
             # Tag with branch name
-            type=ref,event=branch
+            type=ref,event=branch,suffix=${{ matrix.suffix }}
             # Tag with pr-number
-            type=ref,event=pr
+            type=ref,event=pr,suffix=${{ matrix.suffix }}
             # Tag with git tag on release
-            type=ref,event=tag
+            type=ref,event=tag,suffix=${{ matrix.suffix }}
-            type=raw,value=release,enable=${{ github.event_name == 'release' }}
+            type=raw,value=release,enable=${{ github.event_name == 'release' }},suffix=${{ matrix.suffix }}
 
       - name: Determine build cache output
         id: cache-target
@@ -106,5 +129,7 @@ jobs:
           push: ${{ !github.event.pull_request.head.repo.fork }}
           cache-from: type=registry,ref=ghcr.io/${{ github.repository_owner }}/immich-build-cache:${{matrix.image}}
           cache-to: ${{ steps.cache-target.outputs.cache-to }}
+          build-args: |
+            DEVICE=${{ matrix.device }}
           tags: ${{ steps.metadata.outputs.tags }}
           labels: ${{ steps.metadata.outputs.labels }}

.github/workflows/prepare-release.yml

@@ -83,5 +83,6 @@ jobs:
           files: |
             docker/docker-compose.yml
             docker/example.env
-            docker/hwaccel.yml
+            docker/hwaccel.ml.yml
+            docker/hwaccel.transcoding.yml
             *.apk

.github/workflows/test.yml

@@ -225,7 +225,7 @@ jobs:
           cache: "poetry"
       - name: Install dependencies
         run: |
-          poetry install --with dev
+          poetry install --with dev --with cpu
       - name: Lint with ruff
         run: |
           poetry run ruff check --output-format=github app export

docker/docker-compose.dev.yml

@@ -44,8 +44,8 @@ services:
     command: [ "/usr/src/app/bin/immich-dev", "microservices" ]
     <<: *server-common
     # extends:
-    #   file: hwaccel.yml
+    #   file: hwaccel.transcoding.yml
-    #   service: hwaccel
+    #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
     ports:
       - 9231:9230
     depends_on:
@@ -79,9 +79,14 @@ services:
   immich-machine-learning:
     container_name: immich_machine_learning
     image: immich-machine-learning-dev:latest
+    # extends:
+    #   file: hwaccel.ml.yml
+    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
     build:
       context: ../machine-learning
       dockerfile: Dockerfile
+      args:
+        - DEVICE=cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
     ports:
       - 3003:3003
     volumes:

docker/docker-compose.prod.yml

@@ -30,8 +30,8 @@ services:
     command: [ "./start-microservices.sh" ]
     <<: *server-common
     # extends:
-    #   file: hwaccel.yml
+    #   file: hwaccel.transcoding.yml
-    #   service: hwaccel
+    #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
     depends_on:
       - redis
       - database
@@ -40,9 +40,14 @@ services:
   immich-machine-learning:
     container_name: immich_machine_learning
     image: immich-machine-learning:latest
+    # extends:
+    #   file: hwaccel.ml.yml
+    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
     build:
       context: ../machine-learning
       dockerfile: Dockerfile
+      args:
+        - DEVICE=cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
     volumes:
       - model-cache:/cache
     env_file:

docker/docker-compose.yml

@@ -30,9 +30,9 @@ services:
   immich-microservices:
     container_name: immich_microservices
     image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
-    # extends:
+    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
-    #   file: hwaccel.yml
+    #   file: hwaccel.transcoding.yml 
-    #   service: hwaccel
+    #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
     command: [ "start.sh", "microservices" ]
     volumes:
       - ${UPLOAD_LOCATION}:/usr/src/app/upload
@@ -46,7 +46,12 @@ services:
 
   immich-machine-learning:
     container_name: immich_machine_learning
+    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
+    # Example tag: ${IMMICH_VERSION:-release}-cuda
     image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
+    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
+    #   file: hwaccel.ml.yml
+    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
     volumes:
       - model-cache:/cache
     env_file:

docker/hwaccel-rkmpp.yml

@@ -1,24 +0,0 @@
-version: "3.8"
-
-# Hardware acceleration for transcoding using RKMPP for Rockchip SOCs
-# This is only needed if you want to use hardware acceleration for transcoding.
-# Supported host OS is Ubuntu Jammy 22.04 with custom ffmpeg from ppa:liujianfeng1994/rockchip-multimedia
-
-services:
-  hwaccel:
-    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
-      - systempaths=unconfined
-      - apparmor=unconfined
-    group_add:
-      - video
-    devices:
-      - /dev/rga:/dev/rga
-      - /dev/dri:/dev/dri
-      - /dev/dma_heap:/dev/dma_heap
-      - /dev/mpp_service:/dev/mpp_service
-    volumes:
-      - /usr/bin/ffmpeg:/usr/bin/ffmpeg_mpp:ro
-      - /lib/aarch64-linux-gnu:/lib/ffmpeg-mpp:ro
-      - /lib/aarch64-linux-gnu/libblas.so.3:/lib/ffmpeg-mpp/libblas.so.3:ro # symlink is resolved by mounting
-      - /lib/aarch64-linux-gnu/liblapack.so.3:/lib/ffmpeg-mpp/liblapack.so.3:ro # symlink is resolved by mounting
-      - /lib/aarch64-linux-gnu/pulseaudio/libpulsecommon-15.99.so:/lib/ffmpeg-mpp/libpulsecommon-15.99.so:ro

docker/hwaccel.ml.yml

@@ -0,0 +1,47 @@
+version: "3.8"
+
+# Configurations for hardware-accelerated machine learning
+
+# If using Unraid or another platform that doesn't allow multiple Compose files,
+# you can inline the config for a backend by copying its contents 
+# into the immich-machine-learning service in the docker-compose.yml file.
+
+# See https://immich.app/docs/features/ml-hardware-acceleration for info on usage.
+
+services:
+  armnn:
+    devices:
+      - /dev/mali0:/dev/mali0
+    volumes:
+      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
+      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
+
+  cpu:
+
+  cuda:
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities:
+                - gpu
+                - compute
+                - video
+
+  openvino:
+    device_cgroup_rules:
+      - "c 189:* rmw"
+    devices:
+      - /dev/dri:/dev/dri
+    volumes:
+      - /dev/bus/usb:/dev/bus/usb
+
+  openvino-wsl:
+    devices:
+      - /dev/dri:/dev/dri
+      - /dev/dxg:/dev/dxg
+    volumes:
+      - /dev/bus/usb:/dev/bus/usb
+      - /usr/lib/wsl:/usr/lib/wsl

docker/hwaccel.transcoding.yml

@@ -0,0 +1,59 @@
+version: "3.8"
+
+# Configurations for hardware-accelerated transcoding 
+
+# If using Unraid or another platform that doesn't allow multiple Compose files,
+# you can inline the config for a backend by copying its contents 
+# into the immich-microservices service in the docker-compose.yml file.
+
+# See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding.
+
+services:
+  cpu:
+
+  nvenc:
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities:
+                - gpu
+                - compute
+                - video
+
+  quicksync:
+    devices:
+      - /dev/dri:/dev/dri
+
+  rkmpp:
+    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
+      - systempaths=unconfined
+      - apparmor=unconfined
+    group_add:
+      - video
+    devices:
+      - /dev/rga:/dev/rga
+      - /dev/dri:/dev/dri
+      - /dev/dma_heap:/dev/dma_heap
+      - /dev/mpp_service:/dev/mpp_service
+    volumes:
+      - /usr/bin/ffmpeg:/usr/bin/ffmpeg_mpp:ro
+      - /lib/aarch64-linux-gnu:/lib/ffmpeg-mpp:ro
+      - /lib/aarch64-linux-gnu/libblas.so.3:/lib/ffmpeg-mpp/libblas.so.3:ro # symlink is resolved by mounting
+      - /lib/aarch64-linux-gnu/liblapack.so.3:/lib/ffmpeg-mpp/liblapack.so.3:ro # symlink is resolved by mounting
+      - /lib/aarch64-linux-gnu/pulseaudio/libpulsecommon-15.99.so:/lib/ffmpeg-mpp/libpulsecommon-15.99.so:ro
+
+  vaapi:
+    devices:
+      - /dev/dri:/dev/dri
+
+  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
+    devices:
+      - /dev/dri:/dev/dri
+    volumes:
+      - /usr/lib/wsl:/usr/lib/wsl
+    environment:
+      - LD_LIBRARY_PATH=/usr/lib/wsl/lib
+      - LIBVA_DRIVER_NAME=d3d12

docker/hwaccel.yml

@@ -1,22 +0,0 @@
-version: "3.8"
-
-# Hardware acceleration for transcoding - Optional
-# This is only needed if you want to use hardware acceleration for transcoding.
-# Depending on your hardware, you should uncomment the relevant lines below.
-
-services:
-  hwaccel:
-    # devices:
-    #   - /dev/dri:/dev/dri  # If using Intel QuickSync or VAAPI
-    # volumes:
-    #   - /usr/lib/wsl:/usr/lib/wsl # If using VAAPI in WSL2
-    # environment:
-    #   - LD_LIBRARY_PATH=/usr/lib/wsl/lib # If using VAAPI in WSL2
-    #   - LIBVA_DRIVER_NAME=d3d12 # If using VAAPI in WSL2
-    # deploy: # Uncomment this section if using NVIDIA GPU
-    #   resources:
-    #     reservations:
-    #       devices:
-    #         - driver: nvidia
-    #           count: 1
-    #           capabilities: [gpu,video]

docker/mlaccel-armnn.yml

@@ -1,11 +0,0 @@
-version: "3.8"
-
-# ML acceleration on supported Mali ARM GPUs using ARM-NN
-
-services:
-  mlaccel:
-    devices:
-      - /dev/mali0:/dev/mali0
-    volumes:
-      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
-      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)

machine-learning/Dockerfile

@@ -1,43 +1,74 @@
-FROM python:3.11-bookworm@sha256:497c00ec2cff14316a6859c4e30fc88e7ab1f11dd254fb43b8f4b201ca657596 as builder
+ARG DEVICE=cpu
 
+FROM python:3.11-bookworm@sha256:ba7a7ac30c38e119c4304f98ef0e188f90f4f67a958bb6899da9defb99bfb471 as builder-cpu
+
+FROM openvino/ubuntu22_runtime:2023.1.0 as builder-openvino
+USER root
+RUN apt-get update && apt-get install -y --no-install-recommends python3-dev
+
+FROM builder-cpu as builder-cuda
+
+FROM builder-cpu as builder-armnn
+
+ENV ARMNN_PATH=/opt/armnn
+COPY ann /opt/ann
+RUN mkdir /opt/armnn && \
+    curl -SL "https://github.com/ARM-software/armnn/releases/download/v23.11/ArmNN-linux-aarch64.tar.gz" | tar -zx -C /opt/armnn && \
+    cd /opt/ann && \
+    sh build.sh
+
+FROM builder-${DEVICE} as builder
+
+ARG DEVICE
 ENV PYTHONDONTWRITEBYTECODE=1 \
   PYTHONUNBUFFERED=1 \
-  PIP_NO_CACHE_DIR=true
+  PIP_NO_CACHE_DIR=true \
+  VIRTUAL_ENV="/opt/venv" \
+  PATH="/opt/venv/bin:${PATH}"
 
 RUN pip install --upgrade pip && pip install poetry
 RUN poetry config installer.max-workers 10 && \
-  poetry config virtualenvs.create false
+    poetry config virtualenvs.create false
-RUN python -m venv /opt/venv
+RUN python3 -m venv /opt/venv
-ENV VIRTUAL_ENV="/opt/venv" PATH="/opt/venv/bin:${PATH}"
 
 COPY poetry.lock pyproject.toml ./
-RUN poetry install --sync --no-interaction --no-ansi --no-root --only main
+RUN poetry install --sync --no-interaction --no-ansi --no-root --with ${DEVICE} --without dev
 
+FROM python:3.11-slim-bookworm@sha256:cfd7ed5c11a88ce533d69a1da2fd932d647f9eb6791c5b4ddce081aedf7f7876 as prod-cpu
 
-ARG TARGETPLATFORM
+FROM openvino/ubuntu22_runtime:2023.1.0 as prod-openvino
-ENV ARMNN_PATH=/opt/armnn
+USER root
-COPY ann /opt/ann
-RUN if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
-    mkdir /opt/armnn && \
-    curl -SL "https://github.com/ARM-software/armnn/releases/download/v23.11/ArmNN-linux-aarch64.tar.gz" | tar -zx -C /opt/armnn && \
-    cd /opt/ann && \
-    sh build.sh; \
-  else \
-    mkdir /opt/armnn; \
-  fi
 
+FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 as prod-cuda
 
-FROM python:3.11-slim-bookworm@sha256:637774748f62b832dc11e7b286e48cd716727ed04b45a0322776c01bc526afc3
+COPY --from=builder-cuda /usr/local/bin/python3 /usr/local/bin/python3
-ARG TARGETPLATFORM
+COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11
-RUN apt-get update && apt-get install -y --no-install-recommends tini libmimalloc2.0 && rm -rf /var/lib/apt/lists/*
+COPY --from=builder-cuda /usr/local/lib/libpython3.11.so /usr/local/lib/libpython3.11.so
 
-RUN if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
+FROM prod-cpu as prod-armnn
-    apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopencl1 mesa-opencl-icd && \
+
+ENV LD_LIBRARY_PATH=/opt/armnn
+
+RUN apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopencl1 mesa-opencl-icd && \
     rm -rf /var/lib/apt/lists/* && \
     mkdir --parents /etc/OpenCL/vendors && \
-    echo "/usr/lib/libmali.so" > /etc/OpenCL/vendors/mali.icd && \
+    echo "/usr/lib/libmali.so" > /etc/OpenCL/vendors/mali.icd
-    mkdir /opt/armnn; \
+
-  fi
+COPY --from=builder-armnn \
+      /opt/armnn/libarmnn.so.?? \
+      /opt/armnn/libarmnnOnnxParser.so.?? \
+      /opt/armnn/libarmnnDeserializer.so.?? \
+      /opt/armnn/libarmnnTfLiteParser.so.?? \
+      /opt/armnn/libprotobuf.so.?.??.?.? \
+      /opt/ann/libann.s[o] \
+      /opt/ann/build.sh \
+      /opt/armnn/
+
+FROM prod-${DEVICE} as prod
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends tini libmimalloc2.0 && \
+    rm -rf /var/lib/apt/lists/*
 
 WORKDIR /usr/src/app
 ENV NODE_ENV=production \
@@ -45,8 +76,7 @@ ENV NODE_ENV=production \
   PYTHONDONTWRITEBYTECODE=1 \
   PYTHONUNBUFFERED=1 \
   PATH="/opt/venv/bin:$PATH" \
-  PYTHONPATH=/usr/src \
+  PYTHONPATH=/usr/src
-  LD_LIBRARY_PATH=/opt/armnn
 
 # prevent core dumps
 RUN echo "hard core 0" >> /etc/security/limits.conf && \
@@ -54,10 +84,8 @@ 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 --from=builder /opt/armnn/libarmnn.so.?? /opt/armnn/libarmnnOnnxParser.so.?? /opt/armnn/libarmnnDeserializer.so.?? /opt/armnn/libarmnnTfLiteParser.so.?? /opt/armnn/libprotobuf.so.?.??.?.? /opt/ann/libann.s[o] /opt/ann/build.sh /opt/armnn
 COPY ann/ann.py /usr/src/ann/ann.py
 COPY start.sh log_conf.json ./
 COPY app .
-
 ENTRYPOINT ["tini", "--"]
 CMD ["./start.sh"]

machine-learning/README.md

@@ -6,10 +6,11 @@
 # Setup
 
 This project uses [Poetry](https://python-poetry.org/docs/#installation), so be sure to install it first.
-Running `poetry install --no-root --with dev` will install everything you need in an isolated virtual environment.
+Running `poetry install --no-root --with dev --with cpu` will install everything you need in an isolated virtual environment.
+CUDA and OpenVINO are supported as acceleration APIs. To use them, you can replace `--with cpu` with either of `--with cuda` or `--with openvino`.
 
 To add or remove dependencies, you can use the commands `poetry add $PACKAGE_NAME` and `poetry remove $PACKAGE_NAME`, respectively.
-Be sure to commit the `poetry.lock` and `pyproject.toml` files to reflect any changes in dependencies.
+Be sure to commit the `poetry.lock` and `pyproject.toml` files with `poetry lock --no-update` to reflect any changes in dependencies.
 
 
 # Load Testing

machine-learning/app/config.py

@@ -24,8 +24,8 @@ class Settings(BaseSettings):
     workers: int = 1
     test_full: bool = False
     request_threads: int = os.cpu_count() or 4
-    model_inter_op_threads: int = 1
+    model_inter_op_threads: int = 0
-    model_intra_op_threads: int = 2
+    model_intra_op_threads: int = 0
     ann: bool = True
 
     class Config:

machine-learning/app/conftest.py

@@ -93,3 +93,15 @@ def clip_tokenizer_cfg() -> dict[str, Any]:
         "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

machine-learning/app/main.py

@@ -131,7 +131,7 @@ async def load(model: InferenceModel) -> InferenceModel:
             await loop.run_in_executor(thread_pool, _load)
         return model
     except (OSError, InvalidProtobuf, BadZipFile, NoSuchFile):
-        log.warn(
+        log.warning(
             (
                 f"Failed to load {model.model_type.replace('_', ' ')} model '{model.model_name}'."
                 "Clearing cache and retrying."

machine-learning/app/models/base.py

@@ -11,6 +11,7 @@ from huggingface_hub import snapshot_download
 from typing_extensions import Buffer
 
 import ann.ann
+from app.models.constants import SUPPORTED_PROVIDERS
 
 from ..config import get_cache_dir, get_hf_model_name, log, settings
 from ..schemas import ModelType
@@ -24,36 +25,17 @@ class InferenceModel(ABC):
         self,
         model_name: str,
         cache_dir: Path | str | None = None,
-        inter_op_num_threads: int = settings.model_inter_op_threads,
+        providers: list[str] | None = None,
-        intra_op_num_threads: int = settings.model_intra_op_threads,
+        provider_options: list[dict[str, Any]] | None = None,
+        sess_options: ort.SessionOptions | None = None,
         **model_kwargs: Any,
     ) -> None:
-        self.model_name = model_name
         self.loaded = False
-        self._cache_dir = Path(cache_dir) if cache_dir is not None else None
+        self.model_name = model_name
-        self.providers = model_kwargs.pop("providers", ["CPUExecutionProvider"])
+        self.cache_dir = Path(cache_dir) if cache_dir is not None else self.cache_dir_default
-        #  don't pre-allocate more memory than needed
+        self.providers = providers if providers is not None else self.providers_default
-        self.provider_options = model_kwargs.pop(
+        self.provider_options = provider_options if provider_options is not None else self.provider_options_default
-            "provider_options", [{"arena_extend_strategy": "kSameAsRequested"}] * len(self.providers)
+        self.sess_options = sess_options if sess_options is not None else self.sess_options_default
-        )
-        log.debug(
-            (
-                f"Setting '{self.model_name}' execution providers to {self.providers} "
-                "in descending order of preference"
-            ),
-        )
-        log.debug(f"Setting execution provider options to {self.provider_options}")
-        self.sess_options = PicklableSessionOptions()
-        # avoid thread contention between models
-        if inter_op_num_threads > 1:
-            self.sess_options.execution_mode = ort.ExecutionMode.ORT_PARALLEL
-
-        log.debug(f"Setting execution_mode to {self.sess_options.execution_mode.name}")
-        log.debug(f"Setting inter_op_num_threads to {inter_op_num_threads}")
-        log.debug(f"Setting intra_op_num_threads to {intra_op_num_threads}")
-        self.sess_options.inter_op_num_threads = inter_op_num_threads
-        self.sess_options.intra_op_num_threads = intra_op_num_threads
-        self.sess_options.enable_cpu_mem_arena = False
 
     def download(self) -> None:
         if not self.cached:
@@ -95,33 +77,9 @@ class InferenceModel(ABC):
     def _load(self) -> None:
         ...
 
-    @property
-    def model_type(self) -> ModelType:
-        return self._model_type
-
-    @property
-    def cache_dir(self) -> Path:
-        return self._cache_dir if self._cache_dir is not None else get_cache_dir(self.model_name, self.model_type)
-
-    @cache_dir.setter
-    def cache_dir(self, cache_dir: Path) -> None:
-        self._cache_dir = cache_dir
-
-    @property
-    def cached(self) -> bool:
-        return self.cache_dir.exists() and any(self.cache_dir.iterdir())
-
-    @classmethod
-    def from_model_type(cls, model_type: ModelType, model_name: str, **model_kwargs: Any) -> InferenceModel:
-        subclasses = {subclass._model_type: subclass for subclass in cls.__subclasses__()}
-        if model_type not in subclasses:
-            raise ValueError(f"Unsupported model type: {model_type}")
-
-        return subclasses[model_type](model_name, **model_kwargs)
-
     def clear_cache(self) -> None:
         if not self.cache_dir.exists():
-            log.warn(
+            log.warning(
                 f"Attempted to clear cache for model '{self.model_name}', but cache directory does not exist",
             )
             return
@@ -132,7 +90,7 @@ class InferenceModel(ABC):
             log.info(f"Cleared cache directory for model '{self.model_name}'.")
             rmtree(self.cache_dir)
         else:
-            log.warn(
+            log.warning(
                 (
                     f"Encountered file instead of directory at cache path "
                     f"for '{self.model_name}'. Removing file and replacing with a directory."
@@ -156,6 +114,107 @@ class InferenceModel(ABC):
             raise ValueError(f"the file model_path='{model_path}' does not exist")
         return session
 
+    @property
+    def model_type(self) -> ModelType:
+        return self._model_type
+
+    @property
+    def cache_dir(self) -> Path:
+        return self._cache_dir
+
+    @cache_dir.setter
+    def cache_dir(self, cache_dir: Path) -> None:
+        self._cache_dir = cache_dir
+
+    @property
+    def cache_dir_default(self) -> Path:
+        return get_cache_dir(self.model_name, self.model_type)
+
+    @property
+    def cached(self) -> bool:
+        return self.cache_dir.exists() and any(self.cache_dir.iterdir())
+
+    @property
+    def providers(self) -> list[str]:
+        return self._providers
+
+    @providers.setter
+    def providers(self, providers: list[str]) -> None:
+        log.debug(
+            (f"Setting '{self.model_name}' execution providers to {providers}, " "in descending order of preference"),
+        )
+        self._providers = providers
+
+    @property
+    def providers_default(self) -> list[str]:
+        available_providers = set(ort.get_available_providers())
+        log.debug(f"Available ORT providers: {available_providers}")
+        return [provider for provider in SUPPORTED_PROVIDERS if provider in available_providers]
+
+    @property
+    def provider_options(self) -> list[dict[str, Any]]:
+        return self._provider_options
+
+    @provider_options.setter
+    def provider_options(self, provider_options: list[dict[str, Any]]) -> None:
+        log.debug(f"Setting execution provider options to {provider_options}")
+        self._provider_options = provider_options
+
+    @property
+    def provider_options_default(self) -> list[dict[str, Any]]:
+        options = []
+        for provider in self.providers:
+            match provider:
+                case "CPUExecutionProvider" | "CUDAExecutionProvider":
+                    option = {"arena_extend_strategy": "kSameAsRequested"}
+                case "OpenVINOExecutionProvider":
+                    try:
+                        device_ids: list[str] = ort.capi._pybind_state.get_available_openvino_device_ids()
+                        log.debug(f"Available OpenVINO devices: {device_ids}")
+                        gpu_devices = [device_id for device_id in device_ids if device_id.startswith("GPU")]
+                        option = {"device_id": gpu_devices[0]} if gpu_devices else {}
+                    except AttributeError as e:
+                        log.warning("Failed to get OpenVINO device IDs. Using default options.")
+                        log.error(e)
+                        option = {}
+                case _:
+                    option = {}
+            options.append(option)
+        return options
+
+    @property
+    def sess_options(self) -> ort.SessionOptions:
+        return self._sess_options
+
+    @sess_options.setter
+    def sess_options(self, sess_options: ort.SessionOptions) -> None:
+        log.debug(f"Setting execution_mode to {sess_options.execution_mode.name}")
+        log.debug(f"Setting inter_op_num_threads to {sess_options.inter_op_num_threads}")
+        log.debug(f"Setting intra_op_num_threads to {sess_options.intra_op_num_threads}")
+        self._sess_options = sess_options
+
+    @property
+    def sess_options_default(self) -> ort.SessionOptions:
+        sess_options = PicklableSessionOptions()
+        sess_options.enable_cpu_mem_arena = False
+
+        # avoid thread contention between models
+        if settings.model_inter_op_threads > 0:
+            sess_options.inter_op_num_threads = settings.model_inter_op_threads
+        # these defaults work well for CPU, but bottleneck GPU
+        elif settings.model_inter_op_threads == 0 and self.providers == ["CPUExecutionProvider"]:
+            sess_options.inter_op_num_threads = 1
+
+        if settings.model_intra_op_threads > 0:
+            sess_options.intra_op_num_threads = settings.model_intra_op_threads
+        elif settings.model_intra_op_threads == 0 and self.providers == ["CPUExecutionProvider"]:
+            sess_options.intra_op_num_threads = 2
+
+        if sess_options.inter_op_num_threads > 1:
+            sess_options.execution_mode = ort.ExecutionMode.ORT_PARALLEL
+
+        return sess_options
+
 
 # HF deep copies configs, so we need to make session options picklable
 class PicklableSessionOptions(ort.SessionOptions):  # type: ignore[misc]

machine-learning/app/models/clip.py

@@ -23,7 +23,7 @@ class BaseCLIPEncoder(InferenceModel):
     def __init__(
         self,
         model_name: str,
-        cache_dir: str | None = None,
+        cache_dir: Path | str | None = None,
         mode: Literal["text", "vision"] | None = None,
         **model_kwargs: Any,
     ) -> None:
@@ -136,7 +136,7 @@ class OpenCLIPEncoder(BaseCLIPEncoder):
     def __init__(
         self,
         model_name: str,
-        cache_dir: str | None = None,
+        cache_dir: Path | str | None = None,
         mode: Literal["text", "vision"] | None = None,
         **model_kwargs: Any,
     ) -> None:

machine-learning/app/models/constants.py

@@ -51,6 +51,13 @@ _INSIGHTFACE_MODELS = {
 }
 
 
+SUPPORTED_PROVIDERS = [
+    "CUDAExecutionProvider",
+    "OpenVINOExecutionProvider",
+    "CPUExecutionProvider",
+]
+
+
 def is_openclip(model_name: str) -> bool:
     return clean_name(model_name) in _OPENCLIP_MODELS
 

machine-learning/app/schemas.py

@@ -1,4 +1,4 @@
-from enum import StrEnum
+from enum import Enum
 from typing import Any, Protocol, TypedDict, TypeGuard
 
 import numpy as np
@@ -21,7 +21,7 @@ class BoundingBox(TypedDict):
     y2: int
 
 
-class ModelType(StrEnum):
+class ModelType(str, Enum):
     CLIP = "clip"
     FACIAL_RECOGNITION = "facial-recognition"
 

machine-learning/app/test_main.py

@@ -7,12 +7,13 @@ from unittest import mock
 
 import cv2
 import numpy as np
+import onnxruntime as ort
 import pytest
 from fastapi.testclient import TestClient
 from PIL import Image
 from pytest_mock import MockerFixture
 
-from .config import settings
+from .config import log, settings
 from .models.base import InferenceModel, PicklableSessionOptions
 from .models.cache import ModelCache
 from .models.clip import OpenCLIPEncoder
@@ -20,6 +21,221 @@ from .models.facial_recognition import FaceRecognizer
 from .schemas import ModelType
 
 
+class TestBase:
+    CPU_EP = ["CPUExecutionProvider"]
+    CUDA_EP = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+    OV_EP = ["OpenVINOExecutionProvider", "CPUExecutionProvider"]
+    CUDA_EP_OUT_OF_ORDER = ["CPUExecutionProvider", "CUDAExecutionProvider"]
+    TRT_EP = ["TensorrtExecutionProvider", "CUDAExecutionProvider", "CPUExecutionProvider"]
+
+    @pytest.mark.providers(CPU_EP)
+    def test_sets_cpu_provider(self, providers: list[str]) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.providers == self.CPU_EP
+
+    @pytest.mark.providers(CUDA_EP)
+    def test_sets_cuda_provider_if_available(self, providers: list[str]) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.providers == self.CUDA_EP
+
+    @pytest.mark.providers(OV_EP)
+    def test_sets_openvino_provider_if_available(self, providers: list[str]) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.providers == self.OV_EP
+
+    @pytest.mark.providers(CUDA_EP_OUT_OF_ORDER)
+    def test_sets_providers_in_correct_order(self, providers: list[str]) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.providers == self.CUDA_EP
+
+    @pytest.mark.providers(TRT_EP)
+    def test_ignores_unsupported_providers(self, providers: list[str]) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.providers == self.CUDA_EP
+
+    def test_sets_provider_kwarg(self) -> None:
+        providers = ["CUDAExecutionProvider"]
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=providers)
+
+        assert encoder.providers == providers
+
+    def test_sets_default_provider_options(self) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"])
+
+        assert encoder.provider_options == [
+            {},
+            {"arena_extend_strategy": "kSameAsRequested"},
+        ]
+
+    def test_sets_provider_options_kwarg(self) -> None:
+        encoder = OpenCLIPEncoder(
+            "ViT-B-32__openai",
+            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
+            provider_options=[],
+        )
+
+        assert encoder.provider_options == []
+
+    def test_sets_default_sess_options(self) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.sess_options.execution_mode == ort.ExecutionMode.ORT_SEQUENTIAL
+        assert encoder.sess_options.inter_op_num_threads == 1
+        assert encoder.sess_options.intra_op_num_threads == 2
+        assert encoder.sess_options.enable_cpu_mem_arena is False
+
+    def test_sets_default_sess_options_does_not_set_threads_if_non_cpu_and_default_threads(self) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+
+        assert encoder.sess_options.inter_op_num_threads == 0
+        assert encoder.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.models.base.settings", autospec=True)
+        mock_settings.model_inter_op_threads = 2
+        mock_settings.model_intra_op_threads = 4
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+
+        assert encoder.sess_options.inter_op_num_threads == 2
+        assert encoder.sess_options.intra_op_num_threads == 4
+
+    def test_sets_sess_options_kwarg(self) -> None:
+        sess_options = ort.SessionOptions()
+        encoder = OpenCLIPEncoder(
+            "ViT-B-32__openai",
+            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
+            provider_options=[],
+            sess_options=sess_options,
+        )
+
+        assert sess_options is encoder.sess_options
+
+    def test_sets_default_cache_dir(self) -> None:
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+
+        assert encoder.cache_dir == Path("/cache/clip/ViT-B-32__openai")
+
+    def test_sets_cache_dir_kwarg(self) -> None:
+        cache_dir = Path("/test_cache")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+
+        assert encoder.cache_dir == cache_dir
+
+    def test_casts_cache_dir_string_to_path(self) -> None:
+        cache_dir = "/test_cache"
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+
+        assert encoder.cache_dir == Path(cache_dir)
+
+    def test_clear_cache(self, mocker: MockerFixture) -> None:
+        mock_rmtree = mocker.patch("app.models.base.rmtree", autospec=True)
+        mock_rmtree.avoids_symlink_attacks = True
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.exists.return_value = True
+        mock_cache_dir.is_dir.return_value = True
+        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
+        info = mocker.spy(log, "info")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder.clear_cache()
+
+        mock_rmtree.assert_called_once_with(encoder.cache_dir)
+        info.assert_called_once()
+
+    def test_clear_cache_warns_if_path_does_not_exist(self, mocker: MockerFixture) -> None:
+        mock_rmtree = mocker.patch("app.models.base.rmtree", autospec=True)
+        mock_rmtree.avoids_symlink_attacks = True
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.exists.return_value = False
+        mock_cache_dir.is_dir.return_value = True
+        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
+        warning = mocker.spy(log, "warning")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder.clear_cache()
+
+        mock_rmtree.assert_not_called()
+        warning.assert_called_once()
+
+    def test_clear_cache_raises_exception_if_vulnerable_to_symlink_attack(self, mocker: MockerFixture) -> None:
+        mock_rmtree = mocker.patch("app.models.base.rmtree", autospec=True)
+        mock_rmtree.avoids_symlink_attacks = False
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.exists.return_value = True
+        mock_cache_dir.is_dir.return_value = True
+        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        with pytest.raises(RuntimeError):
+            encoder.clear_cache()
+
+        mock_rmtree.assert_not_called()
+
+    def test_clear_cache_replaces_file_with_dir_if_path_is_file(self, mocker: MockerFixture) -> None:
+        mock_rmtree = mocker.patch("app.models.base.rmtree", autospec=True)
+        mock_rmtree.avoids_symlink_attacks = True
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.exists.return_value = True
+        mock_cache_dir.is_dir.return_value = False
+        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
+        warning = mocker.spy(log, "warning")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder.clear_cache()
+
+        mock_rmtree.assert_not_called()
+        mock_cache_dir.unlink.assert_called_once()
+        mock_cache_dir.mkdir.assert_called_once()
+        warning.assert_called_once()
+
+    def test_make_session_return_ann_if_available(self, mocker: MockerFixture) -> None:
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.is_file.return_value = True
+        mock_cache_dir.with_suffix.return_value = mock_cache_dir
+        mocker.patch.object(settings, "ann", True)
+        mocker.patch("ann.ann.is_available", True)
+        mock_session = mocker.patch("app.models.base.AnnSession")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder._make_session(mock_cache_dir)
+
+        mock_session.assert_called_once()
+
+    def test_make_session_return_ort_if_available_and_ann_is_not(self, mocker: MockerFixture) -> None:
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.is_file.return_value = True
+        mock_cache_dir.with_suffix.return_value = mock_cache_dir
+        mocker.patch.object(settings, "ann", False)
+        mocker.patch("ann.ann.is_available", False)
+        mock_session = mocker.patch("app.models.base.ort.InferenceSession")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder._make_session(mock_cache_dir)
+
+        mock_session.assert_called_once()
+
+    def test_make_session_raises_exception_if_path_does_not_exist(self, mocker: MockerFixture) -> None:
+        mock_cache_dir = mocker.Mock()
+        mock_cache_dir.is_file.return_value = False
+        mock_cache_dir.with_suffix.return_value = mock_cache_dir
+        mocker.patch("ann.ann.is_available", False)
+        mock_ann = mocker.patch("app.models.base.ort.InferenceSession")
+        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        with pytest.raises(ValueError):
+            encoder._make_session(mock_cache_dir)
+
+        mock_ann.assert_not_called()
+        mock_ort.assert_not_called()
+
+
 class TestCLIP:
     embedding = np.random.rand(512).astype(np.float32)
     cache_dir = Path("test_cache")
@@ -41,7 +257,7 @@ class TestCLIP:
         mocked.run.return_value = [[self.embedding]]
         mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)
 
-        clip_encoder = OpenCLIPEncoder("ViT-B-32::openai", cache_dir="test_cache", mode="vision")
+        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="vision")
         embedding = clip_encoder.predict(pil_image)
 
         assert clip_encoder.mode == "vision"
@@ -66,7 +282,7 @@ class TestCLIP:
         mocked.run.return_value = [[self.embedding]]
         mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)
 
-        clip_encoder = OpenCLIPEncoder("ViT-B-32::openai", cache_dir="test_cache", mode="text")
+        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
         embedding = clip_encoder.predict("test search query")
 
         assert clip_encoder.mode == "text"
@@ -166,7 +382,7 @@ class TestEndpoints:
         pil_image.save(byte_image, format="jpeg")
         response = deployed_app.post(
             "http://localhost:3003/predict",
-            data={"modelName": "ViT-B-32::openai", "modelType": "clip", "options": json.dumps({"mode": "vision"})},
+            data={"modelName": "ViT-B-32__openai", "modelType": "clip", "options": json.dumps({"mode": "vision"})},
             files={"image": byte_image.getvalue()},
         )
         assert response.status_code == 200
@@ -176,7 +392,7 @@ class TestEndpoints:
         response = deployed_app.post(
             "http://localhost:3003/predict",
             data={
-                "modelName": "ViT-B-32::openai",
+                "modelName": "ViT-B-32__openai",
                 "modelType": "clip",
                 "text": "test search query",
                 "options": json.dumps({"mode": "text"}),

machine-learning/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "aiocache"
@@ -42,24 +42,25 @@ tests = ["pytest"]
 
 [[package]]
 name = "anyio"
-version = "3.7.1"
+version = "4.2.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
+    {file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
-    {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
+    {file = "anyio-4.2.0.tar.gz", hash = "sha256:e1875bb4b4e2de1669f4bc7869b6d3f54231cdced71605e6e64c9be77e3be50f"},
 ]
 
 [package.dependencies]
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (<0.22)"]
+trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "black"
@@ -506,63 +507,63 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "coverage"
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 [package.dependencies]
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 [[package]]
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-    {file = "ruff-0.1.11-py3-none-win32.whl", hash = "sha256:9b8f397902f92bc2e70fb6bebfa2139008dc72ae5177e66c383fa5426cb0bf2c"},
+    {file = "ruff-0.1.13-py3-none-win32.whl", hash = "sha256:a623349a505ff768dad6bd57087e2461be8db58305ebd5577bd0e98631f9ae69"},
-    {file = "ruff-0.1.11-py3-none-win_amd64.whl", hash = "sha256:eb85ee287b11f901037a6683b2374bb0ec82928c5cbc984f575d0437979c521a"},
+    {file = "ruff-0.1.13-py3-none-win_amd64.whl", hash = "sha256:f988746e3c3982bea7f824c8fa318ce7f538c4dfefec99cd09c8770bd33e6539"},
-    {file = "ruff-0.1.11-py3-none-win_arm64.whl", hash = "sha256:97ce4d752f964ba559c7023a86e5f8e97f026d511e48013987623915431c7ea9"},
+    {file = "ruff-0.1.13-py3-none-win_arm64.whl", hash = "sha256:6bbbc3042075871ec17f28864808540a26f0f79a4478c357d3e3d2284e832998"},
-    {file = "ruff-0.1.11.tar.gz", hash = "sha256:f9d4d88cb6eeb4dfe20f9f0519bd2eaba8119bde87c3d5065c541dbae2b5a2cb"},
+    {file = "ruff-0.1.13.tar.gz", hash = "sha256:e261f1baed6291f434ffb1d5c6bd8051d1c2a26958072d38dfbec39b3dda7352"},
 ]
 
 [[package]]
@@ -3357,13 +3420,13 @@ anyio = ">=3.0.0"
 
 [[package]]
 name = "wcwidth"
-version = "0.2.12"
+version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
 files = [
-    {file = "wcwidth-0.2.12-py2.py3-none-any.whl", hash = "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c"},
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
-    {file = "wcwidth-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
 ]
 
 [[package]]
@@ -3538,4 +3601,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "740b00511f571e142cd28496382b44ed4b91bf8aa08ac4140e8d731597fc42f7"
+content-hash = "c982d5c5fee76ca102d823010a538f287ac98583f330ebee3c0775c5f42f117d"

machine-learning/pyproject.toml

@@ -8,7 +8,6 @@ packages = [{include = "app"}]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<3.12"
-onnxruntime = "^1.15.0"
 insightface = ">=0.7.3,<1.0"
 opencv-python-headless = ">=4.7.0.72,<5.0"
 pillow = ">=9.5.0,<11.0"
@@ -36,6 +35,30 @@ pytest-cov = ">=4.1.0"
 ruff = ">=0.0.272"
 pytest-mock = ">=3.11.1"
 
+[tool.poetry.group.cpu]
+optional = true
+
+[tool.poetry.group.cpu.dependencies]
+onnxruntime = "^1.15.0"
+
+[tool.poetry.group.cuda]
+optional = true
+
+[tool.poetry.group.cuda.dependencies]
+onnxruntime-gpu = "^1.15.0"
+
+[tool.poetry.group.openvino]
+optional = true
+
+[tool.poetry.group.openvino.dependencies]
+onnxruntime-openvino = ">=1.15.0,<1.16.0"
+
+[tool.poetry.group.armnn]
+optional = true
+
+[tool.poetry.group.armnn.dependencies]
+onnxruntime = "^1.15.0"
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
@@ -67,3 +90,6 @@ select = ["E", "F", "I"]
 [tool.black]
 line-length = 120
 target-version = ['py311']
+
+[tool.pytest.ini_options]
+markers = ["providers"]