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NVIDIA
Clara Train SDK
Container
NVIDIA
NVIDIA
Clara Train SDK

This domain optimized developer application framework is based on the open source SDKs of MONAI and NVIDIA FLARE. It brings ease of use and a simple CLI-based interface, allowing to quickly get started with annotating, training, and adapting AI models.

LayerLabelCreated
12432abfffe3ad624b216e75f1c67e1c44fb29e5ef76f11c8f39b617f89ecb0cRUN
/bin/sh
03/21/2022 4:43 PM UTC
c171c1647e71b9499c582a369412ea83d99df2fbd0f9f1a20e8dd8d8274fea0aENV
PATH=/opt/nvidia/medical/aiaa/scripts:/opt/nvidia/medical/tools:/opt/conda/bin:/opt/cmake-3.19.3-Linux-$(uname -m)/bin/:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin:/opt/tools
03/21/2022 4:43 PM UTC
a19c1ab811773367bc637693451ad00f0bc09d09a6a4163ab19a7ed65c1770afENV
PYTHONPATH=:/opt/nvidia/medical
03/21/2022 4:43 PM UTC
6ef6710b395971c11323cfb38bb996a2256d78b55edc6e4ed9c624e3989a1fb6RUN
DEST_DIR=/opt/nvidia/medical NVFLARE_VER=2.0.16 mv ${DEST_DIR}/tools/app_validation/bin/verify ${DEST_DIR}/tools &&
  rm -rf ${DEST_DIR}/tools/app_validation/bin
03/21/2022 4:43 PM UTC
31793f511dcc8f68246491770380fe741c9566e1effabc9cd458963b8f31e07cADD
dir:ea028810dd86bd01fdfb76f944d1089f1894adf54455b99c1baa7ca5fe8cdede in /opt/nvidia/medical/tools/app_validation
03/21/2022 4:43 PM UTC
a67caeca9948bb252d77fda44f9e4961f069a22d2f9119e50ddcf14d169250baADD
dir:5fe215b04e6bd875755b4eb0adca63c52b287afd4c1d09ccc24fd69cd52d190e in /opt/nvidia/medical/tools
03/21/2022 4:43 PM UTC
96a31facaedba0072e4fa473d6118c647d7d1d71b6974710461408abac632bc7COPY
dir:858184d23e0d2beb8cb0e233138032ddd14845b5a455cdcdc6198cc1112c8c99 in ./aiaa/templates
03/21/2022 4:43 PM UTC
9a430c207498ec2e466ce69228d1d2579cdec118b72283d478d0b02fae0b20fdRUN
DEST_DIR=/opt/nvidia/medical NVFLARE_VER=2.0.16 rm -rf ./aiaa/templates
03/21/2022 4:43 PM UTC
eabea94dca410ecb0730267909fb29cbfe9bc56fc8179454309fbef7d15ae076RUN
DEST_DIR=/opt/nvidia/medical NVFLARE_VER=2.0.16 python py2compile.py --package_path dlmed &&
  python py2compile.py --package_path medl &&
  python py2compile.py --package_path aiaa &&
  find . -type d -name __pycache__ -exec rm -r {} \+ &&
  rm py2compile.py
03/21/2022 4:43 PM UTC
4f8d5a17c720766ab179f1a49d297338105a6468b18cfeed5da77d371cfb7154ADD
file:2ede0e34021e7de8ea8568d91bcc5da1c1ce12113887bb6b6a34adc01cd4e302 in .
03/21/2022 4:43 PM UTC
...

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