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NVIDIA
NVIDIA
Merlin Training
Container
NVIDIA
NVIDIA
Merlin Training

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

LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4CONFIG
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65b943445e611a63917da71a67bebd8c15dbabc07e0d37546336cb08ce9baf4cRUN
/bin/bash -c #(nop) ENTRYPOINT []
12/08/2021 2:00 PM UTC
24b4596dfcb97b6070f850e1de93edcc59b8e563e7d4ebb324b267d0607edb38RUN
/bin/bash -c #(nop) HEALTHCHECK &{["NONE"] "0s" "0s" "0s" '\x00'}
12/08/2021 2:00 PM UTC
0870ffb544353e7498791db8109753c280b655b17981b0aa9eceefbd4bc183d2RUN
HUGECTR_VER=v3.3 RELEASE=true /bin/bash -c echo $(du -h --max-depth=1 /)
12/08/2021 2:00 PM UTC
2a567fc3be6f1ad9c2b29ff55529799d16a448bd9cc7eba31b897b59a56c718bRUN
HUGECTR_VER=v3.3 RELEASE=true /bin/bash -c pip install numba numpy --upgrade
12/08/2021 2:00 PM UTC
723fb11979925c1f371911ea9ed30fe9241d8215047b2b185e8c6425b085c8e4RUN
HUGECTR_VER=v3.3 RELEASE=true /bin/bash -c rm -rf /repos
12/08/2021 2:00 PM UTC
4537d9a4330e866446ae70df806ca2386d8e7abc9e1d1d5711c2a52a33f58abeRUN
HUGECTR_VER=v3.3 RELEASE=true /bin/bash -c rm /usr/local/cuda/lib64/stubs/libcuda.so.1
12/08/2021 2:00 PM UTC
43e1361d93ca0869c2b74202b4e798a24f9155bc06f32bfca37b96949b006c11RUN
/bin/bash -c #(nop) ENV PYTHONPATH=/hugectr/onnx_converter:/usr/local/hugectr/lib:
12/08/2021 2:00 PM UTC
ae7510b7dacccd53cf71bd0f4e7fe5efce3bc33c9bd5f47c8f3aae02afe6c10fRUN
/bin/bash -c #(nop) ENV PYTHONPATH=/usr/local/hugectr/lib:
12/08/2021 2:00 PM UTC
483234088ff40bb7989c97dac1f05cf8130b7a06cad56a7285c91af33e86bfa4RUN
/bin/bash -c #(nop) ENV LD_LIBRARY_PATH=/usr/local/hugectr/lib:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/lib:/repos/dist/lib
12/08/2021 2:00 PM UTC
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