NVIDIA
NVIDIA
Merlin Training
Container
NVIDIA
NVIDIA
Merlin Training

This container allows users to do preprocessing and feature engineering with NVTabular, and then train a deep-learning based recommender system model with HugeCTR.

LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4CONFIG
aa4250c454cd0dacd8073fb04f2891814229e45defd5d69842eddb4c131e592cRUN
/bin/bash -c #(nop) ENTRYPOINT []
09/26/2021 1:14 AM UTC
60e3b60b78d543466db023c739328b8f68dc0db68932fbfe1ca4f544992e1d27RUN
/bin/bash -c #(nop) HEALTHCHECK &{["NONE"] "0s" "0s" "0s" '\x00'}
09/26/2021 1:14 AM UTC
822b6d8755ce300a2a2731e1a94ea518330ca8567f7b3f8f86be8d109a151652RUN
HUGECTR_VER=v3.2 RELEASE=true /bin/bash -c echo $(du -h --max-depth=1 /)
09/26/2021 1:14 AM UTC
422093ca0d0c9a620dfb8273a954afeab3a19b34d212598a6dd5d3c00b408b57RUN
HUGECTR_VER=v3.2 RELEASE=true /bin/bash -c pip install numba numpy --upgrade
09/26/2021 1:14 AM UTC
3fda53b84087f3b62523ccd789d1fddfafccb9bea36be36f52c9a5c7aadfd50bRUN
HUGECTR_VER=v3.2 RELEASE=true /bin/bash -c rm -rf /repos
09/26/2021 1:14 AM UTC
a6ea267abbb3a9f63ff98eb6eb4098dfe971ba024c69418b49889447ecfe8258RUN
/bin/bash -c #(nop) ENV PYTHONPATH=:/usr/local/hugectr/lib
09/26/2021 1:14 AM UTC
c6270890f042fe83bf85e9cf59729ee9005c01f6da3e2660e582c1400761b5b3RUN
/bin/bash -c #(nop) ENV LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/lib:/repos/dist/lib:/usr/local/hugectr/lib PATH=/usr/local/cuda/lib64/:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin:/usr/local/cuda/bin:/usr/lib/x86_64-linux-gnu/:/usr/local/hugectr/bin
09/26/2021 1:14 AM UTC
3ec566ac4b8a88a4ec1795eab323edd0971377d3939876f12e1c59e85740aeb3RUN
HUGECTR_VER=v3.2 RELEASE=true /bin/bash -c rm /usr/local/cuda/lib64/stubs/libcuda.so.1
09/26/2021 1:14 AM UTC
e2aafe816e055a8cc6aee1d41f58b5c3a63d3318c22dc942cabed62d763c073aRUN
HUGECTR_VER=v3.2 RELEASE=true /bin/bash -c cd /var/tmp/HugeCTR &&
  mkdir build &&
  cd build &&
  LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs/:$LD_LIBRARY_PATH &&
  export PATH=$PATH:/usr/local/cuda-${CUDA_SHORT_VERSION}/compat/ &&
  cmake -DCMAKE_CXX_COMPILER=/usr/bin/g++ -DCMAKE_C_COMPILER=/usr/bin/gcc -DCMAKE_BUILD_TYPE=Release -DSM="60;61;70;75;80" -DVAL_MODE=OFF -DENABLE_MULTINODES=ON -DNCCL_A2A=ON .. &&
  make VERBOSE=1 -j$(nproc) &&
  make install &&
  chmod +x /usr/local/hugectr/bin/* &&
  chmod +x /usr/local/hugectr/lib/* &&
  cd /var/tmp/HugeCTR/onnx_converter &&
  python3 setup.py install &&
  rm -rf /var/tmp/HugeCTR
09/26/2021 1:14 AM UTC
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