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
2024-12-22 01:47:08 +02:00 · 2024-01-21 18:22:39 -05:00 · 2024-01-21 18:22:39 -05:00 · 95cfe22866
commit 95cfe22866
parent 6b419a984c
23 changed files with 962 additions and 460 deletions
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@ -25,15 +25,38 @@ jobs:
      fail-fast: false
      matrix:
        include:
-          - context: "machine-learning"
-            file: "machine-learning/Dockerfile"
-            image: "immich-machine-learning"
-            platforms: "linux/amd64,linux/arm64"
-          - context: "."
-            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,linux/arm64
+            device: cpu

+          - 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=raw,value=release,enable=${{ github.event_name == 'release' }}
+            type=ref,event=tag,suffix=${{ matrix.suffix }}
+            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 }}
--- a/.github/workflows/prepare-release.yml
+++ b/.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
--- a/.github/workflows/test.yml
+++ b/.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
--- a/docker/docker-compose.dev.yml
+++ b/docker/docker-compose.dev.yml
@ -44,8 +44,8 @@ services:
    command: [ "/usr/src/app/bin/immich-dev", "microservices" ]
    <<: *server-common
    # extends:
-    #   file: hwaccel.yml
-    #   service: hwaccel
+    #   file: hwaccel.transcoding.yml
+    #   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:
--- a/docker/docker-compose.prod.yml
+++ b/docker/docker-compose.prod.yml
@ -30,8 +30,8 @@ services:
    command: [ "./start-microservices.sh" ]
    <<: *server-common
    # extends:
-    #   file: hwaccel.yml
-    #   service: hwaccel
+    #   file: hwaccel.transcoding.yml
+    #   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:
--- a/docker/docker-compose.yml
+++ b/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:
-    #   file: hwaccel.yml
-    #   service: hwaccel
+    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
+    #   file: hwaccel.transcoding.yml 
+    #   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:
--- a/docker/hwaccel-rkmpp.yml
+++ b/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
--- a/docker/hwaccel.ml.yml
+++ b/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
--- a/docker/hwaccel.transcoding.yml
+++ b/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
--- a/docker/hwaccel.yml
+++ b/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]
--- a/docker/mlaccel-armnn.yml
+++ b/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)
--- a/machine-learning/Dockerfile
+++ b/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
-RUN python -m venv /opt/venv
-ENV VIRTUAL_ENV="/opt/venv" PATH="/opt/venv/bin:${PATH}"
+    poetry config virtualenvs.create false
+RUN python3 -m venv /opt/venv

 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
-ENV ARMNN_PATH=/opt/armnn
-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 openvino/ubuntu22_runtime:2023.1.0 as prod-openvino
+USER root

+FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 as prod-cuda

-FROM python:3.11-slim-bookworm@sha256:637774748f62b832dc11e7b286e48cd716727ed04b45a0322776c01bc526afc3
-ARG TARGETPLATFORM
-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/bin/python3 /usr/local/bin/python3
+COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11
+COPY --from=builder-cuda /usr/local/lib/libpython3.11.so /usr/local/lib/libpython3.11.so

-RUN if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
-    apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopencl1 mesa-opencl-icd && \
+FROM prod-cpu as prod-armnn
+
+ENV LD_LIBRARY_PATH=/opt/armnn
+
+RUN apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopencl1 mesa-opencl-icd && \
    rm -rf /var/lib/apt/lists/* && \
    mkdir --parents /etc/OpenCL/vendors && \
-    echo "/usr/lib/libmali.so" > /etc/OpenCL/vendors/mali.icd && \
-    mkdir /opt/armnn; \
-  fi
+    echo "/usr/lib/libmali.so" > /etc/OpenCL/vendors/mali.icd
+
+COPY --from=builder-armnn \
+      /opt/armnn/libarmnn.so.?? \
+      /opt/armnn/libarmnnOnnxParser.so.?? \
+      /opt/armnn/libarmnnDeserializer.so.?? \
+      /opt/armnn/libarmnnTfLiteParser.so.?? \
+      /opt/armnn/libprotobuf.so.?.??.?.? \
+      /opt/ann/libann.s[o] \
+      /opt/ann/build.sh \
+      /opt/armnn/
+
+FROM prod-${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 \
-  LD_LIBRARY_PATH=/opt/armnn
+  PYTHONPATH=/usr/src

 # 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"]
--- a/machine-learning/README.md
+++ b/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
@ -20,4 +21,4 @@ You can change the models or adjust options like score thresholds through the Lo

 To get started, you can simply run `locust --web-host 127.0.0.1` and open `localhost:8089` in a browser to access the UI. See the [Locust documentation](https://docs.locust.io/en/stable/index.html) for more info on running Locust. 

-Note that in Locust's jargon, concurrency is measured in `users`, and each user runs one task at a time. To achieve a particular per-endpoint concurrency, multiply that number by the number of endpoints to be queried. For example, if there are 3 endpoints and you want each of them to receive 8 requests at a time, you should set the number of users to 24.
+Note that in Locust's jargon, concurrency is measured in `users`, and each user runs one task at a time. To achieve a particular per-endpoint concurrency, multiply that number by the number of endpoints to be queried. For example, if there are 3 endpoints and you want each of them to receive 8 requests at a time, you should set the number of users to 24.
--- a/machine-learning/app/config.py
+++ b/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_intra_op_threads: int = 2
+    model_inter_op_threads: int = 0
+    model_intra_op_threads: int = 0
    ann: bool = True

    class Config:
--- a/machine-learning/app/conftest.py
+++ b/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
--- a/machine-learning/app/main.py
+++ b/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."
--- a/machine-learning/app/models/base.py
+++ b/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,
-        intra_op_num_threads: int = settings.model_intra_op_threads,
+        providers: list[str] | None = None,
+        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.providers = model_kwargs.pop("providers", ["CPUExecutionProvider"])
-        #  don't pre-allocate more memory than needed
-        self.provider_options = model_kwargs.pop(
-            "provider_options", [{"arena_extend_strategy": "kSameAsRequested"}] * len(self.providers)
-        )
-        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
+        self.model_name = model_name
+        self.cache_dir = Path(cache_dir) if cache_dir is not None else self.cache_dir_default
+        self.providers = providers if providers is not None else self.providers_default
+        self.provider_options = provider_options if provider_options is not None else self.provider_options_default
+        self.sess_options = sess_options if sess_options is not None else self.sess_options_default

    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]
--- a/machine-learning/app/models/clip.py
+++ b/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:
--- a/machine-learning/app/models/constants.py
+++ b/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

--- a/machine-learning/app/schemas.py
+++ b/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"

--- a/machine-learning/app/test_main.py
+++ b/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"}),
--- a/machine-learning/poetry.lock
+++ b/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"},
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 [package.dependencies]
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+    {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-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"},
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {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"
--- a/machine-learning/pyproject.toml
+++ b/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"]