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NVIDIA
Merlin PyTorch
Container
NVIDIA
NVIDIA
Merlin PyTorch

The Merlin PyTorch container allows users to do preprocessing and feature engineering with NVTabular, and then train a deep-learning based recommender system model with PyTorch, and serve the trained model on Triton Inference Server.

LayerLabelCreated
sha256:a26dd31695a2831f024876cb8b412e73e1140088bcb7334fa93b1b4d5b8c42b7RUN
HUGECTR_DEV_MODE=false HUGECTR_VER=v23.09.00 _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git pip install --no-cache-dir matplotlib
09/29/2023 2:49 PM UTC
sha256:bb7773ca3e66d9fec8f718f8073bf33e00bfbb9c1c2aed1e98d593f26f73d828RUN
HUGECTR_DEV_MODE=false HUGECTR_VER=v23.09.00 _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git ln -s /opt/tritonserver/backends/pytorch/* /usr/local/lib/
09/29/2023 2:49 PM UTC
sha256:a7a008b7df9019c330f54dfd66784291377800d5de67e6b50586e59ec336befaRUN
HUGECTR_DEV_MODE=false HUGECTR_VER=v23.09.00 _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git if [ "$HUGECTR_DEV_MODE" == "false" ]; then export HUGECTR_HOME=/usr/local/hugectr &&
  rm -rf ${HUGECTR_HOME}/lib/libgmock* ${HUGECTR_HOME}/lib/pkgconfig/gmock* ${HUGECTR_HOME}/include/gmock &&
  rm -rf ${HUGECTR_HOME}/lib/libgtest* ${HUGECTR_HOME}/lib/pkgconfig/gtest* ${HUGECTR_HOME}/include/gtest &&
  git clone --branch ${HUGECTR_VER} --depth 1 --recurse-submodules --shallow-submodules https://${_CI_JOB_TOKEN}${_HUGECTR_REPO} /hugectr &&
  pushd /hugectr/hps_torch/ &&
  pip --no-cache-dir install ninja &&
  TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 9.0" python setup.py install &&
  popd &&
  rm -rf /hugectr ; fi
09/29/2023 2:49 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
HUGECTR_VER=main
09/29/2023 2:47 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
_CI_JOB_TOKEN=
09/29/2023 2:47 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
_HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git
09/29/2023 2:47 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
HUGECTR_DEV_MODE=false
09/29/2023 2:47 PM UTC
sha256:3418e0ccc87f19c7d9adfb9c54f49e40ba8336e8e7cb5f07569957067e7abf7aCOPY
--chown=1000:1000dir:1a5ca6dfe8eada207b7ef8e793a3d89c8a45335e87a07bc147d9f535fd1a7426 in /usr/local/lib/python3.10/dist-packages/torch.egg-info/
09/29/2023 2:47 PM UTC
sha256:059f9f98481c507e6b10bc6953e3878557a1babd08e11951a0984fcddd9dd1beCOPY
--chown=1000:1000dir:aa26a6b9ed90d8a30bd0209a98ead8506ba8005252f79b13314c46afe5dac6aa in /usr/local/lib/python3.10/dist-packages/numpy.dist-info/
09/29/2023 2:46 PM UTC
sha256:df996c13946b5817fab57a48819bd366d6f72779027af657d41f341469ef654bCOPY
--chown=1000:1000dir:7b4ffac94789f98e1ca57dc46d652ac800ab9018d6f0d8fe9197c71468fe53a7 in /usr/local/lib/python3.10/dist-packages/numba.dist-info/
09/29/2023 2:46 PM UTC
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