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
de9f5ab8a4a5474927fa4b3c506603953f1b98727e0ed9c8ed49b5a0ae5fc505CONFIG
Entrypoint /opt/nvidia/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 6064/tcp, 8888/tcp
05/05/2022 9:16 PM UTC
f54b2fefeafa6e97de7476c22a90afa6f58a001b9c3b33c4dcaa7995afb84cd0LABEL
com.nvidia.build.id=37412675
05/05/2022 9:16 PM UTC
f6f91c0af44aa9ca6ebd693136921e87abe574e17c085572150f3923007d5e05ENV
NVIDIA_BUILD_ID=37412675
05/05/2022 9:16 PM UTC
f7f2f8800cb8f353682305172e9439f0fdd6502aee404b133de0adafcc7ff67eARG
NVIDIA_BUILD_ID
05/05/2022 9:16 PM UTC
26317e8f1f588d9567e48bded2de2fcb0e297209b773be376899fbfbafc488b9RUN
TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.05-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=21d9e994c6341e6af2929ed5385f70d5c8980907 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 ${_CUDA_COMPAT_PATH}/lib
05/05/2022 9:16 PM UTC
9907a934f905ffd0a7ee4750ba375260ff8f79395aa80a6b0e74fe1f811d6269RUN
TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.05-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=21d9e994c6341e6af2929ed5385f70d5c8980907 pip install --no-cache-dir --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple polygraphy==0.33.0
05/05/2022 9:16 PM UTC
865bdcd7b6812c3a1e64ce6b5b3a483e7a97efdcdc5346cd30d0df2942e4a441ENV
PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
05/05/2022 9:16 PM UTC
9471fa7e8c959cd35099089983f893d7f43c0bf590df79a23e75b3cfb125df83RUN
TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.05-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=21d9e994c6341e6af2929ed5385f70d5c8980907 URL=$(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 ${UFF_PATH}/bin/convert_to_uff.py /usr/local/bin/convert-to-uff
05/05/2022 9:16 PM UTC
b58a7a324fbeea3558f3a8d70175cfbce97b469464d1dce18cda4b8bc69c58b3COPY
nvidia-examples /workspace/nvidia-examples
05/05/2022 9:15 PM UTC
24605eeef09742235232b1a3256f367f1f1504a24e7466c2ba383c437db7eb11RUN
TARGETARCH=amd64 TENSORFLOW_VERSION=2.8.0 NVIDIA_TENSORFLOW_VERSION=22.05-tf2 PYVER=3.8 BAZEL_VERSION=5.0.0 TFAPI=2 BAZEL_CACHE= NVIDIA_BUILD_REF=21d9e994c6341e6af2929ed5385f70d5c8980907 sed -i "s/NVIDIA_TENSORFLOW_VERSION/$NVIDIA_TENSORFLOW_VERSION/g" docker-examples/*
05/05/2022 9:15 PM UTC
...

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