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use 3.12

use 1.19.2
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mertalev 2024-12-19 20:53:40 -05:00
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commit d9a41b8ea0
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3 changed files with 19 additions and 18 deletions
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6
docs/docs/features/ml-hardware-acceleration.md
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@ -11,7 +11,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- ARM NN (Mali) - ARM NN (Mali)
- CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher) - CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher)
- ROCM (AMD GPUs) - ROCm (AMD GPUs)
- OpenVINO (Intel GPUs such as Iris Xe and Arc) - OpenVINO (Intel GPUs such as Iris Xe and Arc)
## Limitations ## Limitations
@ -42,9 +42,9 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The installed driver must be >= 535 (it must support CUDA 12.2). - The installed driver must be >= 535 (it must support CUDA 12.2).
- On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed. - On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
#### ROCM #### ROCm
- The GPU must be supported by ROCM (or use `HSA_OVERRIDE_GFX_VERSION=<a supported version, ie 10.3.0>`) - The GPU must be supported by ROCm. If it isn't officially supported, you can attempt to use the `HSA_OVERRIDE_GFX_VERSION` environmental variable: `HSA_OVERRIDE_GFX_VERSION=<a supported version, e.g. 10.3.0>`.
#### OpenVINO #### OpenVINO

24
machine-learning/Dockerfile
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@ -17,11 +17,11 @@ RUN mkdir /opt/armnn && \
# Warning: 26.3Gb of disk space required to pull this image # Warning: 26.3Gb of disk space required to pull this image
# https://github.com/microsoft/onnxruntime/blob/main/dockerfiles/Dockerfile.rocm # https://github.com/microsoft/onnxruntime/blob/main/dockerfiles/Dockerfile.rocm
FROM rocm/dev-ubuntu-22.04:6.1.2-complete as builder-rocm FROM rocm/dev-ubuntu-24.04:6.2.4-complete AS builder-rocm
WORKDIR /code WORKDIR /code
RUN apt-get update && apt-get install -y --no-install-recommends wget git python3.10-venv RUN apt-get update && apt-get install -y --no-install-recommends wget git python3.12-venv
# Install same version as the Dockerfile provided by onnxruntime # Install same version as the Dockerfile provided by onnxruntime
RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.27.3/cmake-3.27.3-linux-x86_64.sh && \ RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.27.3/cmake-3.27.3-linux-x86_64.sh && \
chmod +x cmake-3.27.3-linux-x86_64.sh && \ chmod +x cmake-3.27.3-linux-x86_64.sh && \
@ -32,21 +32,17 @@ RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.27.3/cmake-3.
ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:${PATH} ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:${PATH}
# Prepare onnxruntime repository & build onnxruntime # Prepare onnxruntime repository & build onnxruntime
RUN git clone --single-branch --branch v1.18.1 --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime # Note: cannot upgrade from 1.19.2 as of writing until upstream updates the ROCm CI
RUN git clone --single-branch --branch v1.19.2 --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime
WORKDIR /code/onnxruntime WORKDIR /code/onnxruntime
# EDIT PR # Fix for multi-threading based on comments in https://github.com/microsoft/onnxruntime/pull/19567
# While there's still this PR open, we need to compile on the branch of the PR
# https://github.com/microsoft/onnxruntime/pull/19567
COPY ./0001-fix-avoid-race-condition-for-rocm-conv-algo-caching.patch /tmp/ COPY ./0001-fix-avoid-race-condition-for-rocm-conv-algo-caching.patch /tmp/
RUN git apply /tmp/0001-fix-avoid-race-condition-for-rocm-conv-algo-caching.patch RUN git apply /tmp/0001-fix-avoid-race-condition-for-rocm-conv-algo-caching.patch
# END EDIT PR
RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh
# I ran into a compilation error when parallelizing the build # Note: the `parallel` setting uses a substantial amount of RAM
# I used 12 threads to build onnxruntime, but it needs more than 16GB of RAM, and that's the amount of RAM I have on my machine RUN ./build.sh --allow_running_as_root --config Release --build_wheel --update --build --parallel 13 --cmake_extra_defines\
# I lowered the number of threads to 8, and it worked ONNXRUNTIME_VERSION=1.19.2 --use_rocm --rocm_home=/opt/rocm
# Even with 12 threads, the compilation took more than 1,5 hours to fail
RUN ./build.sh --allow_running_as_root --config Release --build_wheel --update --build --parallel 9 --cmake_extra_defines\
ONNXRUNTIME_VERSION=1.18.1 --use_rocm --rocm_home=/opt/rocm
RUN mv /code/onnxruntime/build/Linux/Release/dist/*.whl /opt/ RUN mv /code/onnxruntime/build/Linux/Release/dist/*.whl /opt/
FROM builder-${DEVICE} AS builder FROM builder-${DEVICE} AS builder
@ -117,7 +113,7 @@ COPY --from=builder-armnn \
/opt/ann/build.sh \ /opt/ann/build.sh \
/opt/armnn/ /opt/armnn/
FROM rocm/dev-ubuntu-22.04:6.1.2-complete AS prod-rocm FROM rocm/dev-ubuntu-24.04:6.2.4-complete AS prod-rocm
FROM prod-${DEVICE} AS prod FROM prod-${DEVICE} AS prod

7
machine-learning/app/models/constants.py
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@ -63,7 +63,12 @@ _INSIGHTFACE_MODELS = {
} }
SUPPORTED_PROVIDERS = ["CUDAExecutionProvider", "ROCMExecutionProvider", "OpenVINOExecutionProvider", "CPUExecutionProvider"] SUPPORTED_PROVIDERS = [
"CUDAExecutionProvider",
"ROCMExecutionProvider",
"OpenVINOExecutionProvider",
"CPUExecutionProvider",
]
def get_model_source(model_name: str) -> ModelSource | None: def get_model_source(model_name: str) -> ModelSource | None: