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NVIDIA
NVIDIA
Merlin PyTorch Training
Container
NVIDIA
NVIDIA
Merlin PyTorch Training

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

LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4CMD
/bin/bash
02/03/2022 8:25 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4HEALTHCHECK
&{["NONE"] "0s" "0s" "0s" '\x00'}
02/03/2022 8:25 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 echo $(du -h --max-depth=1 /)
02/03/2022 8:25 AM UTC
sha256:508e4040642c63266fafc4705745dbf90bf94e2071f85b75c06904945b5798d3RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 rm -rf /opt/conda/share/jupyter/lab/staging/node_modules/fast-json-patch
02/03/2022 8:25 AM UTC
sha256:233bb7e57e2baf63e791f2e151e55f05c2aa827fc69b5265324c5a599a796aeeRUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 pip install 'websockets>=10.0'
02/03/2022 8:25 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 pip uninstall sqlparse -y
02/03/2022 8:25 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 rm -rf /repos
02/03/2022 8:25 AM UTC
sha256:4d24efecfb140f722f854bc003002bc4dd47b9e1c0a7e0c19b736cd5a2dff988RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 pip install torchmetrics==0.3.2
02/03/2022 8:25 AM UTC
sha256:13060f89a84ec12c95e7f8ba1a2f20e45a5b1950de1278d07a6e20aceafe7828RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 git clone https://github.com/NVIDIA-Merlin/Models.git /models/ &&
  cd /models/; if [ "$RELEASE" == "true" ] &&
  [ ${MODELS_VER} != "vnightly" ] ; then git fetch --all --tags &&
  git checkout tags/${MODELS_VER}; else git checkout main; fi; python setup.py develop --no-deps;
02/03/2022 8:25 AM UTC
sha256:404ce3fd70c116a055acb24ecc7d8cd241ddec7949603e9b393c80cfbbcf76d8RUN
MODELS_VER=vnightly NVTAB_VER=v0.10.0 RELEASE=true TF4REC_VER=v0.1.5 git clone https://github.com/NVIDIA-Merlin/Transformers4Rec.git /transformers4rec &&
  cd /transformers4rec/; if [ "$RELEASE" == "true" ] &&
  [ ${TF4REC_VER} != "vnightly" ] ; then git fetch --all --tags &&
  git checkout tags/${TF4REC_VER}; else git checkout main; fi; pip install -e .[pytorch,nvtabular] --no-deps &&
  python setup.py develop --no-deps
02/03/2022 8:25 AM UTC
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