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‎.bazelrc‎

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@@ -1,4 +1,4 @@
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build --cxxopt=--std=c++17
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build --cxxopt=--std=c++20
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build --copt=-I.
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# Bazel does not support including its cc_library targets as system
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# headers. We work around this for generated code

‎.ci/docker/almalinux/Dockerfile‎

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@@ -53,7 +53,6 @@ ENV CUDA_VERSION=${CUDA_VERSION}
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# Make things in our path by default
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ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
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FROM cuda as cuda12.6
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RUN bash ./install_cuda.sh 12.6
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ENV DESIRED_CUDA=12.6
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RUN bash ./install_cuda.sh 13.0
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ENV DESIRED_CUDA=13.0
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FROM cuda as cuda13.2
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RUN bash ./install_cuda.sh 13.2
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ENV DESIRED_CUDA=13.2
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FROM ${ROCM_IMAGE} as rocm_base
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ARG DEVTOOLSET_VERSION=13
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ENV LC_ALL en_US.UTF-8
@@ -101,6 +104,7 @@ COPY --from=cuda12.6 /usr/local/cuda-12.6 /usr/local/cuda-12.6
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COPY --from=cuda12.8 /usr/local/cuda-12.8 /usr/local/cuda-12.8
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COPY --from=cuda12.9 /usr/local/cuda-12.9 /usr/local/cuda-12.9
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COPY --from=cuda13.0 /usr/local/cuda-13.0 /usr/local/cuda-13.0
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COPY --from=cuda13.2 /usr/local/cuda-13.2 /usr/local/cuda-13.2
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# Final step
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FROM ${BASE_TARGET} as final

‎.ci/docker/build.sh‎

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@@ -195,12 +195,16 @@ case "$tag" in
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NINJA_VERSION=1.9.0
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TRITON=yes
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;;
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pytorch-linux-noble-xpu-n-py3 | pytorch-linux-noble-xpu-n-py3-inductor-benchmarks)
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pytorch-linux-noble-xpu-n-py3 | pytorch-linux-noble-xpu-n-py3-client | pytorch-linux-noble-xpu-n-py3-inductor-benchmarks)
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ANACONDA_PYTHON_VERSION=3.10
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GCC_VERSION=13
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VISION=yes
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XPU_VERSION=2025.3
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XPU_DRIVER_TYPE=LTS
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if [[ $tag =~ "client" ]]; then
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XPU_DRIVER_TYPE=CLIENT
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else
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XPU_DRIVER_TYPE=LTS
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fi
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NINJA_VERSION=1.9.0
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TRITON=yes
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if [[ $tag =~ "benchmarks" ]]; then

‎.ci/docker/ci_commit_pins/nccl.txt‎

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v2.29.3-1
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v2.29.7-1

‎.ci/docker/ci_commit_pins/torchbench.txt‎

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7be477a510cdbe9543b2f11357598db51c22e94e
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0fff8bf35400ec7b733d5080628fc79551205e36

‎.ci/docker/ci_commit_pins/triton-xpu.txt‎

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307748db7742a0f8259a7ea0336909eb55d2051a
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33f782efa9464adebb448ea1f1df1a64ec37ceb0

‎.ci/docker/common/install_cuda.sh‎

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@@ -111,7 +111,7 @@ function install_126 {
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}
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function install_129 {
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CUDNN_VERSION=9.17.1.4
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CUDNN_VERSION=9.20.0.48
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echo "Installing CUDA 12.9.1 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
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# install CUDA 12.9.1 in the same container
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install_cuda 12.9.1 cuda_12.9.1_575.57.08_linux
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}
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function install_128 {
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CUDNN_VERSION=9.19.0.56
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CUDNN_VERSION=9.20.0.48
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echo "Installing CUDA 12.8.1 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
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# install CUDA 12.8.1 in the same container
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install_cuda 12.8.1 cuda_12.8.1_570.124.06_linux
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}
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function install_130 {
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CUDNN_VERSION=9.19.0.56
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echo "Installing CUDA 13.0 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
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CUDNN_VERSION=9.20.0.48
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echo "Installing CUDA 13.0 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.8.0"
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# install CUDA 13.0 in the same container
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install_cuda 13.0.2 cuda_13.0.2_580.95.05_linux
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ldconfig
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}
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function install_132 {
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CUDNN_VERSION=9.20.0.48
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echo "Installing CUDA 13.2 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.8.0"
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# install CUDA 13.2 in the same container
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install_cuda 13.2.0 cuda_13.2.0_595.45.04_linux
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# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
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install_cudnn 13 $CUDNN_VERSION
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install_nvshmem 13 $NVSHMEM_VERSION
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CUDA_VERSION=13.2 bash install_nccl.sh
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CUDA_VERSION=13.2 bash install_cusparselt.sh
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ldconfig
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}
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# idiomatic parameter and option handling in sh
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while test $# -gt 0
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do
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;;
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13.0|13.0.*) install_130;
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;;
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13.2|13.2.*) install_132;
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;;
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*) echo "bad argument $1"; exit 1
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;;
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esac

‎.ci/docker/requirements-docs.txt‎

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#Description: This is used to generate PyTorch docs
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#Pinned versions: 7.2.6
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pytorch_sphinx_theme2==0.4.3
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pytorch_sphinx_theme2==0.4.6
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#Description: This is needed to generate PyTorch docs
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#Pinned versions: 0.4.3
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#Pinned versions: 0.4.6
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# TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
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# but it doesn't seem to work and hangs around idly. The initial thought that it is probably

‎.ci/lumen_cli/cli/build_cli/register_build.py‎

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import argparse
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from __future__ import annotations
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import argparse # noqa: TC003
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import logging
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from cli.lib.common.cli_helper import register_targets, RichHelp, TargetSpec

‎.ci/lumen_cli/cli/lib/common/cli_helper.py‎

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"""
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from __future__ import annotations
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import argparse
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from abc import ABC, abstractmethod
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from collections.abc import Callable # Python 3.11+
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from typing import Any, Required, TypedDict
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except ImportError:
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from collections.abc import Callable
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from collections.abc import Callable # noqa: TC003
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from typing import Any, TypedDict
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from typing_extensions import Required # Fallback for Python <3.11

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