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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:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) CMD ["/bin/bash"]
11/04/2021 7:28 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) ENTRYPOINT []
11/04/2021 7:28 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
/bin/bash -c #(nop) HEALTHCHECK &{["NONE"] "0s" "0s" "0s" '\x00'}
11/04/2021 7:28 PM UTC
sha256:9c40c7a7d2778a2751276ef41511f2ffe1450386d87b37af6aafd6365d35c13dRUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c echo $(du -h --max-depth=1 /)
11/04/2021 7:28 PM UTC
sha256:4cc43076215263fbb86010f1ff5430233d433bcf1681ee89b8e08ab6fe5ac762RUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c rm -rf /repos
11/04/2021 7:27 PM UTC
sha256:64ebfa45bfe6925a57619350259f86d1fae0ac0337676e5a09e08b9499e9e3f2RUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c rm -rf /opt/conda/share/jupyter/lab/staging/node_modules/fast-json-patch
11/04/2021 7:27 PM UTC
sha256:aaa0386116617396361893883d544bef37211153ca8d9a06c1780a0899141e65RUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c pip install 'websockets>=10.0'
11/04/2021 7:27 PM UTC
sha256:c955e2b77f756ce2aaa54c321691650fdc29762c3257faab1966bd6ae3e87f88RUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c pip uninstall sqlparse -y
11/04/2021 7:27 PM UTC
sha256:50d2b03be68a505b7e64bfd7ed9c689a0895e24ce2702132a1d78eb7dac3f41fRUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c pip install torchmetrics==0.3.2
11/04/2021 7:27 PM UTC
sha256:2055e6f67d391f3e78922ee8abd6ebb0f753a450bf6d0c8708e679e6c672c378RUN
CUDF_VER=v21.08.03 NVTAB_VER=v0.7.1 RELEASE=true RMM_VER=v21.08.02 TF4REC_VER=vnightly /bin/bash -c pip install dask==2021.07.1 distributed==2021.07.1 dask[dataframe]==2021.07.1 dask-cuda
11/04/2021 7:26 PM UTC
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