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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
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.ref=3e3d2f129b8a553cf8b03befab28c0c18ab28b72
    06/24/2022 6:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=39734918
    06/24/2022 6:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=39734918
    06/24/2022 6:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID
    06/24/2022 6:57 PM UTC
    sha256:637356c88882aa45db87cda729b3191683301e7b64a9b46ba84f0252a791a846RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.9.1 NVIDIA_TENSORFLOW_VERSION=22.06-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=3e3d2f129b8a553cf8b03befab28c0c18ab28b72 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 ${_CUDA_COMPAT_PATH}/lib
    06/24/2022 6:57 PM UTC
    sha256:f3637f6cbb7db2e1f763c7665d04937458075216c0eaabcdaa50004a5c4cf0caRUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.9.1 NVIDIA_TENSORFLOW_VERSION=22.06-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=3e3d2f129b8a553cf8b03befab28c0c18ab28b72 pip install --no-cache-dir --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple polygraphy==0.33.0
    06/24/2022 6:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
    06/24/2022 6:57 PM UTC
    sha256:19d41f8504a36c7e1ef06aafc249a5f643e48fc0241efc6b845ebd9b064aff35RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.9.1 NVIDIA_TENSORFLOW_VERSION=22.06-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=3e3d2f129b8a553cf8b03befab28c0c18ab28b72 URL=$(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 &&
      sed -i 's/from tensorflow import GraphDef/from tensorflow.python import GraphDef/' $UFF_PATH/converters/tensorflow/conversion_helpers.py &&
      chmod +x ${UFF_PATH}/bin/convert_to_uff.py &&
      ln -sf ${UFF_PATH}/bin/convert_to_uff.py /usr/local/bin/convert-to-uff
    06/24/2022 6:57 PM UTC
    sha256:35dd750119068e81a8c56ae35c0774f9c1e98ebfba9906bf658aca56775dd04dCOPY
    nvidia-examples /workspace/nvidia-examples
    06/24/2022 6:57 PM UTC
    sha256:aec61b33b8b8b7d9e26b062c30192213d4a2904d0ed9a01af727a09ac6966312RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.9.1 NVIDIA_TENSORFLOW_VERSION=22.06-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=3e3d2f129b8a553cf8b03befab28c0c18ab28b72 sed -i "s/NVIDIA_TENSORFLOW_VERSION/$NVIDIA_TENSORFLOW_VERSION/g" docker-examples/*
    06/24/2022 6:57 PM UTC
    ...

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