| # | |
| # This example Dockerfile illustrates a method to apply | |
| # patches to the source code in NVIDIA's PyTorch | |
| # container image and to rebuild PyTorch. The RUN command | |
| # included below will rebuild PyTorch in the same way as | |
| # it was built in the original image. | |
| # | |
| # By applying customizations through a Dockerfile and | |
| # `docker build` in this manner rather than modifying the | |
| # container interactively, it will be straightforward to | |
| # apply the same changes to later versions of the PyTorch | |
| # container image. | |
| # | |
| # https://docs.docker.com/engine/reference/builder/ | |
| # | |
| FROM nvcr.io/nvidia/pytorch:25.11-py3 | |
| # Bring in changes from outside container to /tmp | |
| # (assumes my-pytorch-modifications.patch is in same directory as Dockerfile) | |
| COPY my-pytorch-modifications.patch /tmp | |
| # Change working directory to PyTorch source path | |
| WORKDIR /opt/pytorch | |
| # Apply modifications | |
| RUN patch -p1 < /tmp/my-pytorch-modifications.patch | |
| # Rebuild PyTorch | |
| RUN cd pytorch && \ | |
| USE_CUPTI_SO=1 \ | |
| USE_KINETO=1 \ | |
| CMAKE_PREFIX_PATH="/usr/local" \ | |
| NCCL_ROOT="/usr" \ | |
| USE_SYSTEM_NCCL=1 \ | |
| USE_UCC=1 \ | |
| USE_SYSTEM_UCC=1 \ | |
| UCC_HOME="/opt/hpcx/ucc" \ | |
| # UCC_DIR is for PyTorch to find ucc-config.cmake | |
| UCC_DIR="/opt/hpcx/ucc/lib/cmake/ucc" \ | |
| UCX_HOME="/opt/hpcx/ucx" \ | |
| UCX_DIR="/opt/hpcx/ucx/lib/cmake/ucx" \ | |
| CFLAGS='-fno-gnu-unique' \ | |
| DEFAULT_INTEL_MKL_DIR="/usr/local" \ | |
| INTEL_MKL_DIR="/usr/local" \ | |
| python setup.py install \ | |
| && python setup.py clean | |
| # Reset default working directory | |
| WORKDIR /workspace | |