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NVIDIA
Merlin Tensorflow Training
Container
NVIDIA
Merlin Tensorflow Training

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

LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENTRYPOINT
["/bin/bash" "-c" "/opt/nvidia/nvidia_entrypoint.sh"]
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4CMD
/bin/bash
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4HEALTHCHECK
&{["NONE"] "0s" "0s" "0s" '\x00'}
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_DISTRIBUTED_EMBEDDINGS=true INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git rm -rf /usr/local/share/jupyter/lab/staging/node_modules/node-fetch
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_DISTRIBUTED_EMBEDDINGS=true INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git rm -rf /usr/local/share/jupyter/lab/staging/node_modules/marked
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_DISTRIBUTED_EMBEDDINGS=true INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git rm -rf /repos
05/12/2022 10:41 AM UTC
sha256:fc49208828736740032cf893622f915b3a1b6f0edb6b6adcba519c595e21a070RUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_DISTRIBUTED_EMBEDDINGS=true INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git if [ "$INSTALL_DISTRIBUTED_EMBEDDINGS" == "true" ]; then git clone https://github.com/NVIDIA-Merlin/distributed-embeddings.git /distributed_embeddings/ &&
  cd /distributed_embeddings &&
  git checkout ${TFDE_VER} &&
  make pip_pkg &&
  pip install artifacts/*.whl &&
  make clean; fi
05/12/2022 10:41 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
INSTALL_DISTRIBUTED_EMBEDDINGS=true
05/12/2022 10:40 AM UTC
sha256:fe7ede1e7aec4de3556bfad00f306952e74dfb919e7a1c4bb7ed65764c5d3784RUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git if [ "$HUGECTR_DEV_MODE" == "false" ]; then git clone https://${_CI_JOB_TOKEN}${_HUGECTR_REPO} build-env &&
  pushd build-env &&
  git checkout ${HUGECTR_VER} &&
  cd sparse_operation_kit &&
  python setup.py install &&
  popd &&
  rm -rf build-env; fi
05/12/2022 10:40 AM UTC
sha256:ba94f1edf56754329aca97610e68e08d0931329edb3b6276765bcfedd13228ecRUN
CORE_VER=v0.3.0 HUGECTR_DEV_MODE=false HUGECTR_VER=v3.6 INSTALL_NVT=true MODELS_VER=v0.4.0 NVTAB_VER=v1.1.1 SYSTEMS_VER=v0.2.0 TF4REC_VER=v0.1.8 TFDE_VER=main _CI_JOB_TOKEN= _HUGECTR_REPO=github.com/NVIDIA-Merlin/HugeCTR.git ln -s /usr/lib/x86_64-linux-gnu/libibverbs.so.1 /usr/lib/x86_64-linux-gnu/libibverbs.so
05/12/2022 10:38 AM UTC
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