Google
Google
TensorFlow
Container
Google
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
8e0a0c8846dff3c2a1613f0b51591d3789dfa23806106cd1ad6210afbe727f07CONFIG
Entrypoint /opt/nvidia/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 6064/tcp, 8888/tcp
11/19/2022 5:31 PM UTC
c8f4cdb512f9a8d0b79ba610be366fa5f96d7c0f34ea48d44d84d8efdb4403b8ARG
NVIDIA_BUILD_REF
11/19/2022 5:31 PM UTC
95504d871247c327c527be6d370e145f31b0c96b3fe07eb6062737269c17812fLABEL
com.nvidia.build.id=48494316
11/19/2022 5:31 PM UTC
a5b9e6650d3a23e6f0236a9abceff6336a23849771b1acf1ccfc287d321e4033ENV
NVIDIA_BUILD_ID=48494316
11/19/2022 5:31 PM UTC
4629a600b56c77da5e6a3154f652a4772535337c70e681e82b3e7caba10eea75ARG
NVIDIA_BUILD_ID
11/19/2022 5:31 PM UTC
16519c27ea491142459cf0a6babd86a9125ecab507c43812a302bcc8c8c5492aRUN
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 ${_CUDA_COMPAT_PATH}/lib
11/19/2022 5:31 PM UTC
e3d827fe543e47a4fe385eefa461dcfbc1d20d7e7ccf627df046adb5e39e9e5dRUN
TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 pip install --no-cache-dir --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple polygraphy==${POLYGRAPHY_VERSION}
11/19/2022 5:31 PM UTC
7e8967b151d0bf2959ca64b178a784d5a69bcaeec5ec891868b5426f88db4f3bENV
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
55dfb65b0ddbc95a28989a8abcd1606d5bae0a1fa8a96dc04d4f480b9bd2d37eRUN
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 ${UFF_PATH}/bin/convert_to_uff.py /usr/local/bin/convert-to-uff
11/19/2022 5:30 PM UTC
f85a828b9d06ad1a02ec0d7f0d499082b45e74c74b33fc541099ec8c454ed738RUN
TARGETARCH=amd64 TENSORFLOW_VERSION=1.15.5 NVIDIA_TENSORFLOW_VERSION=22.11-tf1 PYVER=3.8 BAZEL_VERSION=0.25.3 TFAPI=1 sed -i "s/NVIDIA_TENSORFLOW_VERSION/$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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