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PyTorch
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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.

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09/17/2025 7:07 PM UTC
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09/17/2025 7:07 PM UTC
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com.nvidia.build.id=210907837
09/17/2025 7:07 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=210907837
09/17/2025 7:07 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID=210907837
09/17/2025 7:07 PM UTC
sha256:d0b2d1c6ead79d0775ce77066a6a5f3bf5989ba02cf9f7a64a27cffc1b8c467aRUN
NVIDIA_PYTORCH_VERSION=25.09 PYTORCH_BUILD_VERSION=2.9.0a0+50eac81 NVFUSER_BUILD_VERSION=a71c674 TARGETARCH=amd64 PYVER=3.12 L4T=0 ENABLE_MITMPROXY=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali cd /opt/pytorch/pytorch/ &&
  sed -i "s#    if (props.computeMode != cudaComputeModeDefault) {#    int computeMode = -1;\n    TP_CUDA_CHECK(cudaDeviceGetAttribute(\&computeMode, cudaDevAttrComputeMode, device.index));\n    if (computeMode != cudaComputeModeDefault) {#g" ./third_party/tensorpipe/tensorpipe/channel/cuda_ipc/context_impl.cc &&
  cd -
09/17/2025 7:07 PM UTC
sha256:88f5013807399b192d7187738097e920e03d66a4524ffdf3f43e00f9d7e8d4e3COPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
09/17/2025 7:07 PM UTC
sha256:9f0e62f08c13222cf1473225ed969d032f3f742bbfe06719b367006906ef52c6COPY
constraint.txt /etc/pip/original_constraint.txt
09/17/2025 7:07 PM UTC
sha256:e7251edc54268db8bd528caaebc4e5f72ad8e9309917c5b68431b4d393db8d23COPY
restricted_constraint.txt /etc/pip/constraint.txt
09/17/2025 7:07 PM UTC
sha256:745e034c4c75c000f2be880eb9d49e4ecf43193aa0beace03e7818ed4c74b4f0RUN
NVIDIA_PYTORCH_VERSION=25.09 PYTORCH_BUILD_VERSION=2.9.0a0+50eac81 NVFUSER_BUILD_VERSION=a71c674 TARGETARCH=amd64 PYVER=3.12 L4T=0 ENABLE_MITMPROXY=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali 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
09/17/2025 7:07 PM UTC
...

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