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NVIDIA
NVIDIA
Merlin Tensorflow Training
Container
NVIDIA
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:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) CMD ["/bin/bash"]
04/13/2021 1:37 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) ENTRYPOINT []
04/13/2021 1:37 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) HEALTHCHECK &{["NONE"] "0s" "0s" "0s" '\x00'}
04/13/2021 1:37 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) ENV LD_LIBRARY_PATH=/usr/local/hugectr/lib:/opt/conda/lib:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 LIBRARY_PATH=/usr/local/hugectr/lib:/opt/conda/lib:/usr/local/cuda/lib64/stubs: PYTHONPATH=/usr/local/hugectr/lib:
04/13/2021 1:37 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c echo $(du -h --max-depth=1 /)
04/13/2021 1:37 AM UTC
sha256:427d6d157b095fcc89b8c4ecd2f30226a96e38dd81cfc7871725c65551d63a47RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c source activate ${CONDA_ENV}; conda clean --all -y
04/13/2021 1:37 AM UTC
sha256:8cfa4ffb2a7ed4c46418b6c5779a18bd402e3803397f80ed1e49d0619d0cf703RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c source activate ${CONDA_ENV}; apt update; apt install -y graphviz ;
04/13/2021 1:37 AM UTC
sha256:bb67cb9c3c709a38ab91341d6be9305f1df9168df8dfc989878a98a9bbdd8d06RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c source activate ${CONDA_ENV}; conda env config vars set PYTHONPATH=$PYTHONPATH:/opt/conda/envs/merlin/lib/python3.8/site-packages:/hugectr/tools/embedding_plugin/python:/opt/conda/lib/python3.8/site-packages:/usr/local/lib/python3.8/dist-packages
04/13/2021 1:36 AM UTC
sha256:2807a127c0e7fe4701f8c7b117b587654f9eb3bb13a13c25006e263e388d9ea7RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c source activate ${CONDA_ENV}; conda install -c rapidsai asvdb
04/13/2021 1:36 AM UTC
sha256:e701a036ed4a877b79ebaf8a998a9c26ce4823de001e20818124f7be6fa670d6RUN
CONDA_ENV=merlin HUGECTR_VER=v3.0.1 NVTAB_VER=v0.5.0 RAPIDS_VER=0.18.0 RELEASE=true SM=60;61;70;75;80 /bin/bash -c source activate ${CONDA_ENV}; pip install nvidia-pyindex; pip install tritonclient[all] grpcio-channelz
04/13/2021 1:36 AM UTC
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