Google
TensorFlow
Container
Google
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=fe987c8af9aeeceaa9bd118e6594f252ac3e9528
    04/05/2022 5:00 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=35256959
    04/05/2022 5:00 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=35256959
    04/05/2022 5:00 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID
    04/05/2022 5:00 PM UTC
    sha256:37e1881c4f58471434d6a1ad8d7bea244bf5f3ef00a69e9756698abad2bb935bRUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.04-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=fe987c8af9aeeceaa9bd118e6594f252ac3e9528 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 ${_CUDA_COMPAT_PATH}/lib
    04/05/2022 5:00 PM UTC
    sha256:7f6d0523ed0b0e0bc2bf4bdeb10fbc495f5e9bde41484a11f49c0f53507b84e7RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.04-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=fe987c8af9aeeceaa9bd118e6594f252ac3e9528 pip install --no-cache-dir --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple polygraphy==0.33.0
    04/05/2022 5:00 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
    04/05/2022 5:00 PM UTC
    sha256:e22325b292b5dba135d8923876ef354f6dfa0cf53fe6edb573176f2c188a6951RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.04-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=fe987c8af9aeeceaa9bd118e6594f252ac3e9528 URL=$(VERIFY=1 /nvidia/build-scripts/installTRT.sh 2>/dev/null | sed -n "s/^.*\(http.*\)deb.*$/\1/p")tar &&
      FILE=$(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
    04/05/2022 5:00 PM UTC
    sha256:7e05fb2a76df644187c3a001e89c52c2d7bc3f54a742773b852d24ec4962ba80RUN
    TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.04-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=fe987c8af9aeeceaa9bd118e6594f252ac3e9528 cd /workspace/nvidia-examples/tensorrt &&
      patch -i /opt/tensorflow/pycoco_build.patch --strip 1 &&
      rm /opt/tensorflow/pycoco_build.patch
    04/05/2022 5:00 PM UTC
    sha256:8dcb9120b39ada864199c4b65fc331dc5597f3752edfc838f2e6e816023823e3COPY
    pycoco_build.patch /opt/tensorflow/
    04/05/2022 5:00 PM UTC
    ...

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