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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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21bf4d5111495244caf99fd8431eb7ca742b912cf7ea5bed02f8e0ec06a96991RUN
/bin/bash -c #(nop) ENTRYPOINT []
11/04/2021 8:58 AM UTC
627012f218dc1da458208fcd0db9508929a2023d0083fa9b5ae4d358d8090316RUN
/bin/bash -c #(nop) HEALTHCHECK &{["NONE"] "0s" "0s" "0s" '\x00'}
11/04/2021 8:58 AM UTC
fafc79665fe5818af6a8d98916ab0e9dc4e8c2386dc8d183049b13bfe155d217RUN
HUGECTR_VER=v3.2.1 RELEASE=true /bin/bash -c echo $(du -h --max-depth=1 /)
11/04/2021 8:58 AM UTC
40d743c344fdf0644e26bf707996e7f1284fcebb976976ab8afd7194d997f862RUN
HUGECTR_VER=v3.2.1 RELEASE=true /bin/bash -c pip install numba numpy --upgrade
11/04/2021 8:58 AM UTC
6aa5a62445b417d54d7c2d025dbc0b9cb861057fca7f5237485cde38c2180374RUN
HUGECTR_VER=v3.2.1 RELEASE=true /bin/bash -c rm -rf /repos
11/04/2021 8:57 AM UTC
f24f6ea523502d4f31505dbe5b3e95b196f01b40d92528be54d689a8ba3a44d8RUN
HUGECTR_VER=v3.2.1 RELEASE=true /bin/bash -c rm /usr/local/cuda/lib64/stubs/libcuda.so.1
11/04/2021 8:57 AM UTC
5cdd2858b5397537c8558ec4caae799111365a802548eb78b8137628abfb695eRUN
/bin/bash -c #(nop) ENV PYTHONPATH=/hugectr/onnx_converter:/usr/local/hugectr/lib:
11/04/2021 8:57 AM UTC
1f00c0f21e9f47146902435f2bfdf7ae36ae358471bd056102129e00412d8afdRUN
/bin/bash -c #(nop) ENV PYTHONPATH=/usr/local/hugectr/lib:
11/04/2021 8:57 AM UTC
0a6d2aa9d6e71fb7512d28f937b4efee05eb263cf90844a0f406364a5660157aRUN
/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
11/04/2021 8:57 AM UTC
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