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PyTorch
Container
NVIDIA
PyTorch

PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.

LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.ref=b3f725706edbd7cc21a22384237d38b257704796
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_REF
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.id=76438008
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=76438008
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID
12/05/2023 10:36 PM UTC
sha256:438f8321cc6f5bc0c077fb38dece352d82555b0e2805088715f0873adfe8cc7fCOPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
12/05/2023 10:36 PM UTC
sha256:ef0d164ab90873dcb53408ac1256ee1dc446074d04468a2203273022ccd25235RUN
PYVER=3.10 ln -sf ${_CUDA_COMPAT_PATH}/lib.real ${_CUDA_COMPAT_PATH}/lib &&
  echo ${_CUDA_COMPAT_PATH}/lib > /etc/ld.so.conf.d/00-cuda-compat.conf &&
  ldconfig &&
  rm -f ${_CUDA_COMPAT_PATH}/lib
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
CUDA_MODULE_LOADING=LAZY
12/05/2023 10:36 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
TORCH_CUDNN_V8_API_ENABLED=1
12/05/2023 10:36 PM UTC
sha256:eacb925d795e926ca9d4dc32bbc455a7342d34c35ad1b975dc14bc7a2a8f7ee8RUN
PYVER=3.10 if [ "${L4T}" = "1" ]; then echo "Not installing Transformer Engine in iGPU container until Version variable is set"; else pip install --no-cache-dir --no-build-isolation git+https://github.com/NVIDIA/TransformerEngine.git@release_v${TRANSFORMER_ENGINE_VERSION}; fi
12/05/2023 10:36 PM UTC
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