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TensorFlow

TensorFlow is an open source platform for machine learning. It provides comprehensive tools and libraries in a flexible architecture allowing easy deployment across a variety of platforms and devices.

  • LayerLabelCreated
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    com.nvidia.build.ref=3770a02b3ed640eb4f4f16deff79022940ef7ba4
    11/19/2022 5:31 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_REF
    11/19/2022 5:31 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=48494316
    11/19/2022 5:31 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=48494316
    11/19/2022 5:31 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID
    11/19/2022 5:31 PM UTC
    sha256:9e29fba61c26072042ac417b57388f7dc9f5cd0acf53b1fc280de1ce019c1eb6RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 ln -sf ${_CUDA_COMPAT_PATH}/lib.real ${_CUDA_COMPAT_PATH}/lib &&
      echo ${_CUDA_COMPAT_PATH}/lib > /etc/ld.so.conf.d/00-cuda-compat.conf &&
      ldconfig &&
      rm -f ${_CUDA_COMPAT_PATH}/lib
    11/19/2022 5:31 PM UTC
    sha256:f596ce3e35f5428ffc9a2376eb71bf6dc36d166fd628a8d9c7bdf785389ce0a1RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 pip install --no-cache-dir --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple polygraphy==${POLYGRAPHY_VERSION}
    11/19/2022 5:31 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
    11/19/2022 5:30 PM UTC
    sha256:82ed74fe0d135642861f1ac8b73f5b75cdd3d171653aa3ddfa6c6080618ad539RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 URL=$(VERIFY=1 /nvidia/build-scripts/installTRT.sh 2>/dev/null | sed -n "s/^.*\(http.*\)tar.*$/\1/p")tar &&
      FILE=$(wget -O - $URL 2>/dev/null | sed -n 's/^.*href="\(TensorRT[^"]*\)".*$/\1/p' | grep -v internal) &&
      wget --quiet $URL/$FILE -O - | tar -xz &&
      PY=$(python -c 'import sys; print(str(sys.version_info[0])+str(sys.version_info[1]))') &&
      pip install TensorRT-*/python/tensorrt-*-cp$PY*.whl &&
      pip install TensorRT-*/graphsurgeon/graphsurgeon-*.whl &&
      pip install TensorRT-*/uff/uff-*.whl &&
      mv /usr/src/tensorrt /opt &&
      ln -s /opt/tensorrt /usr/src/tensorrt &&
      rm -r TensorRT-* &&
      UFF_PATH=$(pip show uff | sed -n 's/Location: \(.*\)$/\1/p')/uff &&
      chmod +x ${UFF_PATH}/bin/convert_to_uff.py &&
      ln -sf ${UFF_PATH}/bin/convert_to_uff.py /usr/local/bin/convert-to-uff
    11/19/2022 5:30 PM UTC
    sha256:24b4cf76c2d7793a2b3431489623c0a6a7713e577a57219a46dde870852e6730RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 sed -i "s/NVIDIA_TENSORFLOW_VERSION/$NVIDIA_TENSORFLOW_VERSION/g" docker-examples/* &&
      ln -s /opt/tensorflow/nvidia-examples /workspace/nvidia-examples
    11/19/2022 5:30 PM UTC
    ...

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