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7 Commits

Author SHA1 Message Date
764fea0bc7 fix and disable upcast fp32 2025-07-11 12:10:43 -04:00
cb4a36b6f0 enable native matmul = True 2025-07-08 12:28:31 -04:00
b9c496a0ed lint and fix 2025-07-08 00:01:46 -04:00
cb8aa1d37f fix 2025-07-07 18:48:26 -04:00
15a3bcc968 add heuristics 2025-07-07 17:17:59 -04:00
f758d3d518 add ops.dot codegen 2025-07-07 15:24:35 -04:00
499fc5bd4f add ops.dot 2025-07-07 14:22:52 -04:00
1859 changed files with 72817 additions and 62496 deletions

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@ -2,7 +2,7 @@ build --cxxopt=--std=c++17
build --copt=-I.
# Bazel does not support including its cc_library targets as system
# headers. We work around this for generated code
# (e.g. torch/headeronly/macros/cmake_macros.h) by making the generated directory a
# (e.g. c10/macros/cmake_macros.h) by making the generated directory a
# system include path.
build --copt=-isystem --copt bazel-out/k8-fastbuild/bin
build --copt=-isystem --copt bazel-out/darwin-fastbuild/bin

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@ -4,7 +4,7 @@ set -eux -o pipefail
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
if [[ "$GPU_ARCH_VERSION" == *"12.9"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
export TORCH_CUDA_ARCH_LIST="9.0;10.0;12.0"
fi
SCRIPTPATH="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"

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@ -5,7 +5,7 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
if [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
pip install click mock tabulate networkx==2.0
pip -q install "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
pip -q install --user "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
fi
# Skip tests in environments where they are not built/applicable
@ -147,8 +147,8 @@ export DNNL_MAX_CPU_ISA=AVX2
if [[ "${SHARD_NUMBER:-1}" == "1" ]]; then
# TODO(sdym@meta.com) remove this when the linked issue resolved.
# py is temporary until https://github.com/Teemu/pytest-sugar/issues/241 is fixed
pip install py==1.11.0
pip install pytest-sugar
pip install --user py==1.11.0
pip install --user pytest-sugar
# NB: Warnings are disabled because they make it harder to see what
# the actual erroring test is
"$PYTHON" \

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@ -36,104 +36,3 @@ See `build.sh` for valid build environments (it's the giant switch).
# Set flags (see build.sh) and build image
sudo bash -c 'TRITON=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
```
## [Guidance] Adding a New Base Docker Image
### Background
The base Docker images in directory `.ci/docker/` are built by the `docker-builds.yml` workflow. Those images are used throughout the PyTorch CI/CD pipeline. You should only create or modify a base Docker image if you need specific environment changes or dependencies before building PyTorch on CI.
1. **Automatic Rebuilding**:
- The Docker image building process is triggered automatically when changes are made to files in the `.ci/docker/*` directory
- This ensures all images stay up-to-date with the latest dependencies and configurations
2. **Image Reuse in PyTorch Build Workflows** (example: linux-build):
- The images generated by `docker-builds.yml` are reused in `_linux-build.yml` through the `calculate-docker-image` step
- The `_linux-build.yml` workflow:
- Pulls the Docker image determined by the `calculate-docker-image` step
- Runs a Docker container with that image
- Executes `.ci/pytorch/build.sh` inside the container to build PyTorch
3. **Usage in Test Workflows** (example: linux-test):
- The same Docker images are also used in `_linux-test.yml` for running tests
- The `_linux-test.yml` workflow follows a similar pattern:
- It uses the `calculate-docker-image` step to determine which Docker image to use
- It pulls the Docker image and runs a container with that image
- It installs the wheels from the artifacts generated by PyTorch build jobs
- It executes test scripts (like `.ci/pytorch/test.sh` or `.ci/pytorch/multigpu-test.sh`) inside the container
### Understanding File Purposes
#### `.ci/docker/build.sh` vs `.ci/pytorch/build.sh`
- **`.ci/docker/build.sh`**:
- Used for building base Docker images
- Executed by the `docker-builds.yml` workflow to pre-build Docker images for CI
- Contains configurations for different Docker build environments
- **`.ci/pytorch/build.sh`**:
- Used for building PyTorch inside a Docker container
- Called by workflows like `_linux-build.yml` after the Docker container is started
- Builds PyTorch wheels and other artifacts
#### `.ci/docker/ci_commit_pins/` vs `.github/ci_commit_pins`
- **`.ci/docker/ci_commit_pins/`**:
- Used for pinning dependency versions during base Docker image building
- Ensures consistent environments for building PyTorch
- Changes here trigger base Docker image rebuilds
- **`.github/ci_commit_pins`**:
- Used for pinning dependency versions during PyTorch building and tests
- Ensures consistent dependencies for PyTorch across different builds
- Used by build scripts running inside Docker containers
### Step-by-Step Guide for Adding a New Base Docker Image
#### 1. Add Pinned Commits (If Applicable)
We use pinned commits for build stability. The `nightly.yml` workflow checks and updates pinned commits for certain repository dependencies daily.
If your new Docker image needs a library installed from a specific pinned commit or built from source:
1. Add the repository you want to track in `nightly.yml` and `merge-rules.yml`
2. Add the initial pinned commit in `.ci/docker/ci_commit_pins/`. The text filename should match the one defined in step 1
#### 2. Configure the Base Docker Image
1. **Add new Base Docker image configuration** (if applicable):
Add the configuration in `.ci/docker/build.sh`. For example:
```bash
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc11-new1)
CUDA_VERSION=12.8.1
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
NEW_ARG_1=yes
;;
```
2. **Add build arguments to Docker build command**:
If you're introducing a new argument to the Docker build, make sure to add it in the Docker build step in `.ci/docker/build.sh`:
```bash
docker build \
....
--build-arg "NEW_ARG_1=${NEW_ARG_1}"
```
3. **Update Dockerfile logic**:
Update the Dockerfile to use the new argument. For example, in `ubuntu/Dockerfile`:
```dockerfile
ARG NEW_ARG_1
# Set up environment for NEW_ARG_1
RUN if [ -n "${NEW_ARG_1}" ]; then bash ./do_something.sh; fi
```
4. **Add the Docker configuration** in `.github/workflows/docker-builds.yml`:
The `docker-builds.yml` workflow pre-builds the Docker images whenever changes occur in the `.ci/docker/` directory. This includes the
pinned commit updates.

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@ -52,8 +52,6 @@ fi
if [[ "$image" == *-jammy* ]]; then
UBUNTU_VERSION=22.04
elif [[ "$image" == *-noble* ]]; then
UBUNTU_VERSION=24.04
elif [[ "$image" == *ubuntu* ]]; then
extract_version_from_image_name ubuntu UBUNTU_VERSION
fi
@ -91,18 +89,9 @@ tag=$(echo $image | awk -F':' '{print $2}')
# configuration, so we hardcode everything here rather than do it
# from scratch
case "$tag" in
pytorch-linux-jammy-cuda12.4-cudnn9-py3-gcc11)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11)
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
VISION=yes
@ -113,6 +102,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
VISION=yes
@ -124,6 +114,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
VISION=yes
@ -135,6 +126,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.13
GCC_VERSION=9
VISION=yes
@ -146,6 +138,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
VISION=yes
@ -154,18 +147,9 @@ case "$tag" in
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc11-vllm)
CUDA_VERSION=12.8.1
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
VISION=yes
@ -177,6 +161,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
VISION=yes
@ -188,6 +173,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.13
GCC_VERSION=9
VISION=yes
@ -199,6 +185,7 @@ case "$tag" in
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9)
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
VISION=yes
@ -231,12 +218,20 @@ case "$tag" in
VISION=yes
TRITON=yes
;;
pytorch-linux-jammy-rocm-n-py3 | pytorch-linux-noble-rocm-n-py3)
if [[ $tag =~ "jammy" ]]; then
ANACONDA_PYTHON_VERSION=3.10
else
ANACONDA_PYTHON_VERSION=3.12
fi
pytorch-linux-jammy-rocm-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
VISION=yes
ROCM_VERSION=6.3
NINJA_VERSION=1.9.0
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-rocm-n-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
VISION=yes
ROCM_VERSION=6.4
@ -247,19 +242,6 @@ case "$tag" in
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-noble-rocm-alpha-py3)
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
VISION=yes
ROCM_VERSION=7.0
NINJA_VERSION=1.9.0
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950"
;;
pytorch-linux-jammy-xpu-2025.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
@ -276,7 +258,7 @@ case "$tag" in
NINJA_VERSION=1.9.0
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
@ -288,6 +270,7 @@ case "$tag" in
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-clang12)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=12.8.1
CUDNN_VERSION=9
CLANG_VERSION=12
VISION=yes
TRITON=yes
@ -339,8 +322,6 @@ case "$tag" in
GCC_VERSION=11
ACL=yes
VISION=yes
CONDA_CMAKE=yes
OPENBLAS=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
@ -350,8 +331,6 @@ case "$tag" in
GCC_VERSION=11
ACL=yes
VISION=yes
CONDA_CMAKE=yes
OPENBLAS=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
@ -366,6 +345,7 @@ case "$tag" in
fi
if [[ "$image" == *cuda* ]]; then
extract_version_from_image_name cuda CUDA_VERSION
extract_version_from_image_name cudnn CUDNN_VERSION
fi
if [[ "$image" == *rocm* ]]; then
extract_version_from_image_name rocm ROCM_VERSION
@ -417,6 +397,9 @@ docker build \
--build-arg "PYTHON_VERSION=${PYTHON_VERSION}" \
--build-arg "GCC_VERSION=${GCC_VERSION}" \
--build-arg "CUDA_VERSION=${CUDA_VERSION}" \
--build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
--build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
--build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
--build-arg "KATEX=${KATEX:-}" \
--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
@ -434,7 +417,6 @@ docker build \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "UNINSTALL_DILL=${UNINSTALL_DILL}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "OPENBLAS=${OPENBLAS:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
-f $(dirname ${DOCKERFILE})/Dockerfile \

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@ -1 +1 @@
v2.27.5-1
v2.27.3-1

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@ -1 +1 @@
11ec6354315768a85da41032535e3b7b99c5f706
c8757738a7418249896224430ce84888e8ecdd79

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@ -23,10 +23,6 @@ conda_install() {
as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION" $*
}
conda_install_through_forge() {
as_jenkins conda install -c conda-forge -q -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION" $*
}
conda_run() {
as_jenkins conda run -n py_$ANACONDA_PYTHON_VERSION --no-capture-output $*
}

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@ -15,9 +15,6 @@ install_ubuntu() {
elif [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
cmake3="cmake=3.22*"
maybe_libiomp_dev=""
elif [[ "$UBUNTU_VERSION" == "24.04"* ]]; then
cmake3="cmake=3.28*"
maybe_libiomp_dev=""
else
cmake3="cmake=3.5*"
maybe_libiomp_dev="libiomp-dev"

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@ -4,8 +4,12 @@ set -ex
# Optionally install conda
if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download" # @lint-ignore
CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
BASE_URL="https://repo.anaconda.com/miniconda"
CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]] || [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download" # @lint-ignore
CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
fi
MAJOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 1)
MINOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 2)
@ -17,6 +21,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
exit 1
;;
esac
mkdir -p /opt/conda
chown jenkins:jenkins /opt/conda
@ -65,10 +70,10 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
fi
# Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
if [[ $(uname -m) != "aarch64" ]]; then
pip_install mkl==2024.2.0
pip_install mkl-static==2024.2.0
pip_install mkl-include==2024.2.0
if [[ $(uname -m) == "aarch64" ]]; then
conda_install "openblas==0.3.29=*openmp*"
else
conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
fi
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
@ -82,10 +87,6 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
conda_run ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION})
fi
if [[ "$UBUNTU_VERSION" == "24.04"* ]] ; then
conda_install_through_forge libstdcxx-ng=14
fi
# Install some other packages, including those needed for Python test reporting
pip_install -r /opt/conda/requirements-ci.txt

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@ -66,7 +66,7 @@ function do_cpython_build {
ln -s pip3 ${prefix}/bin/pip
fi
# install setuptools since python 3.12 is required to use distutils
${prefix}/bin/pip install wheel==0.45.1 setuptools==80.9.0
${prefix}/bin/pip install wheel==0.34.2 setuptools==68.2.2
local abi_tag=$(${prefix}/bin/python -c "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag; print('{0}{1}-{2}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()))")
ln -sf ${prefix} /opt/python/${abi_tag}
}

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@ -78,19 +78,6 @@ function install_nvshmem {
echo "nvSHMEM ${nvshmem_version} for CUDA ${cuda_major_version} (${arch_path}) installed."
}
function install_124 {
CUDNN_VERSION=9.1.0.70
echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.2"
install_cuda 12.4.1 cuda_12.4.1_550.54.15_linux
install_cudnn 12 $CUDNN_VERSION
CUDA_VERSION=12.4 bash install_nccl.sh
CUDA_VERSION=12.4 bash install_cusparselt.sh
ldconfig
}
function install_126 {
CUDNN_VERSION=9.10.2.21
@ -126,40 +113,6 @@ function install_129 {
ldconfig
}
function prune_124 {
echo "Pruning CUDA 12.4"
#####################################################################################
# CUDA 12.4 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
if [[ -n "$OVERRIDE_GENCODE_CUDNN" ]]; then
export GENCODE_CUDNN=$OVERRIDE_GENCODE_CUDNN
fi
# all CUDA libs except CuDNN and CuBLAS
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 12.4 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-12.4/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
}
function prune_126 {
echo "Pruning CUDA 12.6"
#####################################################################################
@ -216,8 +169,6 @@ function install_128 {
while test $# -gt 0
do
case "$1" in
12.4) install_124; prune_124
;;
12.6|12.6.*) install_126; prune_126
;;
12.8|12.8.*) install_128;

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@ -0,0 +1,24 @@
#!/bin/bash
if [[ -n "${CUDNN_VERSION}" ]]; then
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn
pushd tmp_cudnn
if [[ ${CUDA_VERSION:0:4} == "12.9" || ${CUDA_VERSION:0:4} == "12.8" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.10.2.21_cuda12-archive"
elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.10.2.21_cuda12-archive"
elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"
else
print "Unsupported CUDA version ${CUDA_VERSION}"
exit 1
fi
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
tar xf ${CUDNN_NAME}.tar.xz
cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cudnn
ldconfig
fi

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@ -13,14 +13,6 @@ if [[ ${CUDA_VERSION:0:4} =~ ^12\.[5-9]$ ]]; then
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.7.1.0-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
arch_path='sbsa'
export TARGETARCH=${TARGETARCH:-$(uname -m)}
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
else
echo "Not sure which libcusparselt version to install for this ${CUDA_VERSION}"
fi

View File

@ -4,9 +4,8 @@
set -ex
cd /
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.30}" --depth 1 --shallow-submodules
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.29}" --depth 1 --shallow-submodules
OPENBLAS_CHECKOUT_DIR="OpenBLAS"
OPENBLAS_BUILD_FLAGS="
NUM_THREADS=128
USE_OPENMP=1
@ -14,8 +13,9 @@ NO_SHARED=0
DYNAMIC_ARCH=1
TARGET=ARMV8
CFLAGS=-O3
BUILD_BFLOAT16=1
"
OPENBLAS_CHECKOUT_DIR="OpenBLAS"
make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

View File

@ -8,11 +8,9 @@ ver() {
install_ubuntu() {
apt-get update
# gpg-agent is not available by default
apt-get install -y --no-install-recommends gpg-agent
if [[ $(ver $UBUNTU_VERSION) -ge $(ver 22.04) ]]; then
echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' \
| sudo tee /etc/apt/preferences.d/rocm-pin-600
if [[ $UBUNTU_VERSION == 20.04 ]]; then
# gpg-agent is not available by default on 20.04
apt-get install -y --no-install-recommends gpg-agent
fi
apt-get install -y kmod
apt-get install -y wget
@ -30,25 +28,16 @@ EOF
# we want the patch version of 6.4 instead
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
ROCM_VERSION="${ROCM_VERSION}.2"
fi
# Default url values
rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
# Special case for ROCM_VERSION == 7.0
if [[ $(ver "$ROCM_VERSION") -eq $(ver 7.0) ]]; then
rocm_baseurl="https://repo.radeon.com/rocm/apt/7.0_alpha2"
amdgpu_baseurl="https://repo.radeon.com/amdgpu/30.10_alpha2/ubuntu"
ROCM_VERSION="${ROCM_VERSION}.1"
fi
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
# Add rocm repository
wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
local rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
echo "deb [arch=amd64] ${rocm_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/rocm.list
apt-get update --allow-insecure-repositories
@ -82,33 +71,29 @@ EOF
done
# ROCm 6.3 had a regression where initializing static code objects had significant overhead
# CI no longer builds for ROCm 6.3, but
# ROCm 6.4 did not yet fix the regression, also HIP branch names are different
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.4) ]] && [[ $(ver $ROCM_VERSION) -lt $(ver 7.0) ]]; then
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.4.2) ]]; then
HIP_TAG=rocm-6.4.2
CLR_HASH=74d78ba3ac4bac235d02bcb48511c30b5cfdd457 # branch release/rocm-rel-6.4.2-statco-hotfix
elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.4.1) ]]; then
HIP_TAG=rocm-6.4.1
CLR_HASH=efe6c35790b9206923bfeed1209902feff37f386 # branch release/rocm-rel-6.4.1-statco-hotfix
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.3) ]] && [[ $(ver $ROCM_VERSION) -lt $(ver 7.0) ]]; then
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.4.1) ]]; then
HIP_BRANCH=release/rocm-rel-6.4
VER_STR=6.4
VER_PATCH=.1
elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
HIP_TAG=rocm-6.4.0
CLR_HASH=600f5b0d2baed94d5121e2174a9de0851b040b0c # branch release/rocm-rel-6.4-statco-hotfix
HIP_BRANCH=release/rocm-rel-6.4
VER_STR=6.4
elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
HIP_BRANCH=rocm-6.3.x
VER_STR=6.3
fi
# clr build needs CppHeaderParser but can only find it using conda's python
python -m pip install CppHeaderParser
git clone https://github.com/ROCm/HIP -b $HIP_TAG
/opt/conda/bin/python -m pip install CppHeaderParser
git clone https://github.com/ROCm/HIP -b $HIP_BRANCH
HIP_COMMON_DIR=$(readlink -f HIP)
git clone https://github.com/jeffdaily/clr
pushd clr
git checkout $CLR_HASH
popd
git clone https://github.com/jeffdaily/clr -b release/rocm-rel-${VER_STR}${VER_PATCH}-statco-hotfix
mkdir -p clr/build
pushd clr/build
# Need to point CMake to the correct python installation to find CppHeaderParser
cmake .. -DPython3_EXECUTABLE=/opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}/bin/python3 -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
cmake .. -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
make -j
cp hipamd/lib/libamdhip64.so.6.4.* /opt/rocm/lib/libamdhip64.so.6.4.*
cp hipamd/lib/libamdhip64.so.${VER_STR}.* /opt/rocm/lib/libamdhip64.so.${VER_STR}.*
popd
rm -rf HIP clr
fi

View File

@ -56,10 +56,14 @@ function install_ubuntu() {
function install_rhel() {
. /etc/os-release
if [[ ! " 8.8 8.10 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
echo "RHEL version ${VERSION_ID} not supported"
exit
if [[ "${ID}" == "rhel" ]]; then
if [[ ! " 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
echo "RHEL version ${VERSION_ID} not supported"
exit
fi
elif [[ "${ID}" == "almalinux" ]]; then
# Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
VERSION_ID="8.8"
fi
dnf install -y 'dnf-command(config-manager)'

View File

@ -41,7 +41,7 @@ case ${DOCKER_TAG_PREFIX} in
rocm*)
# we want the patch version of 6.4 instead
if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.1"
fi
BASE_TARGET=rocm
GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete

View File

@ -27,7 +27,5 @@ COPY ./common/install_linter.sh install_linter.sh
RUN bash ./install_linter.sh
RUN rm install_linter.sh
RUN chown -R jenkins:jenkins /var/lib/jenkins/ci_env
USER jenkins
CMD ["bash"]

View File

@ -41,7 +41,7 @@ case ${image} in
GPU_IMAGE=arm64v8/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
MANY_LINUX_VERSION="2_28_aarch64"
OPENBLAS_VERSION="v0.3.30"
OPENBLAS_VERSION="v0.3.29"
;;
manylinuxcxx11-abi-builder:cpu-cxx11-abi)
TARGET=final
@ -77,7 +77,7 @@ case ${image} in
manylinux2_28-builder:rocm*)
# we want the patch version of 6.4 instead
if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.1"
fi
TARGET=rocm_final
MANY_LINUX_VERSION="2_28"

View File

@ -16,7 +16,6 @@ click
#test that import:
coremltools==5.0b5 ; python_version < "3.12"
coremltools==8.3 ; python_version == "3.12"
#Description: Apple framework for ML integration
#Pinned versions: 5.0b5
#test that import:
@ -50,7 +49,7 @@ flatbuffers==24.12.23
hypothesis==5.35.1
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
#Description: advanced library for generating parametrized tests
#Pinned versions: 5.35.1
#Pinned versions: 3.44.6, 4.53.2
#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
junitparser==2.1.1
@ -64,7 +63,6 @@ lark==0.12.0
#test that import:
librosa>=0.6.2 ; python_version < "3.11"
librosa==0.10.2 ; python_version == "3.12"
#Description: A python package for music and audio analysis
#Pinned versions: >=0.6.2
#test that import: test_spectral_ops.py
@ -113,7 +111,6 @@ ninja==1.11.1.3
numba==0.49.0 ; python_version < "3.9"
numba==0.55.2 ; python_version == "3.9"
numba==0.55.2 ; python_version == "3.10"
numba==0.60.0 ; python_version == "3.12"
#Description: Just-In-Time Compiler for Numerical Functions
#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
#test that import: test_numba_integration.py
@ -221,9 +218,9 @@ pygments==2.15.0
#Pinned versions: 2.12.0
#test that import: the doctests
#pyyaml
#PyYAML
#Description: data serialization format
#Pinned versions: 6.0.2
#Pinned versions:
#test that import:
#requests
@ -233,7 +230,7 @@ pygments==2.15.0
#rich
#Description: rich text and beautiful formatting in the terminal
#Pinned versions: 14.1.0
#Pinned versions: 10.9.0
#test that import:
scikit-image==0.19.3 ; python_version < "3.10"
@ -307,7 +304,7 @@ pytest-cpp==2.3.0
#Pinned versions: 2.3.0
#test that import:
z3-solver==4.15.1.0
z3-solver==4.12.6.0
#Description: The Z3 Theorem Prover Project
#Pinned versions:
#test that import:
@ -363,10 +360,10 @@ pwlf==2.2.1
# To build PyTorch itself
pyyaml
astunparse
PyYAML
pyzstd
setuptools>=70.1.0
six
setuptools
scons==4.5.2 ; platform_machine == "aarch64"
@ -389,9 +386,3 @@ tlparse==0.3.30
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"
#Description: required for testing CUDAGraph::raw_cuda_graph(). See https://nvidia.github.io/cuda-python/cuda-bindings/latest/support.html for how this version was chosen. Note "Any fix in the latest bindings would be backported to the prior major version" means that only the newest version of cuda-bindings will get fixes. Depending on the latest version of 12.x is okay because all 12.y versions will be supported via "CUDA minor version compatibility". Pytorch builds against 13.z versions of cuda toolkit work with 12.x versions of cuda-bindings as well because newer drivers work with old toolkits.
#test that import: test_cuda.py
setuptools-git-versioning==2.1.0
scikit-build==0.18.1
pyre-extensions==0.0.32
tabulate==0.9.0
#Description: These package are needed to build FBGEMM and torchrec on PyTorch CI

View File

@ -4,8 +4,8 @@ sphinx==5.3.0
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
# TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
# but it doesn't seem to work and hangs around idly. The initial thought that it is probably
# something related to Docker setup. We can investigate this later.
# but it doesn't seem to work and hangs around idly. The initial thought is probably
# something related to Docker setup. We can investigate this later
sphinxcontrib.katex==0.8.6
#Description: This is used to generate PyTorch docs
@ -59,4 +59,3 @@ sphinx-copybutton==0.5.0
sphinx-design==0.4.0
sphinxcontrib-mermaid==1.0.0
myst-parser==0.18.1
myst-nb

View File

@ -1 +1 @@
3.4.0
3.3.1

View File

@ -147,12 +147,6 @@ RUN if [ -n "${ACL}" ]; then bash ./install_acl.sh; fi
RUN rm install_acl.sh
ENV INSTALLED_ACL ${ACL}
ARG OPENBLAS
COPY ./common/install_openblas.sh install_openblas.sh
RUN if [ -n "${OPENBLAS}" ]; then bash ./install_openblas.sh; fi
RUN rm install_openblas.sh
ENV INSTALLED_OPENBLAS ${OPENBLAS}
# Install ccache/sccache (do this last, so we get priority in PATH)
ARG SKIP_SCCACHE_INSTALL
COPY ./common/install_cache.sh install_cache.sh

View File

@ -97,7 +97,7 @@ if [[ -z "$PYTORCH_ROOT" ]]; then
exit 1
fi
pushd "$PYTORCH_ROOT"
retry pip install -qUr requirements-build.txt
retry pip install -q cmake
python setup.py clean
retry pip install -qr requirements.txt
case ${DESIRED_PYTHON} in

View File

@ -54,13 +54,12 @@ cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
case ${CUDA_VERSION} in
#removing sm_50-sm_60 as these architectures are deprecated in CUDA 12.8/9 and will be removed in future releases
#however we would like to keep sm_70 architecture see: https://github.com/pytorch/pytorch/issues/157517
#removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8/9 and will be removed in future releases
12.8)
TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0"
TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0"
;;
12.9)
TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0+PTX"
TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX"
# WAR to resolve the ld error in libtorch build with CUDA 12.9
if [[ "$PACKAGE_TYPE" == "libtorch" ]]; then
TORCH_CUDA_ARCH_LIST="7.5;8.0;9.0;10.0;12.0+PTX"

View File

@ -92,7 +92,7 @@ if [[ -z "$PYTORCH_ROOT" ]]; then
exit 1
fi
pushd "$PYTORCH_ROOT"
retry pip install -qUr requirements-build.txt
retry pip install -q cmake
python setup.py clean
retry pip install -qr requirements.txt
retry pip install -q numpy==2.0.1
@ -104,7 +104,7 @@ if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
export ROCclr_DIR=/opt/rocm/rocclr/lib/cmake/rocclr
fi
echo "Calling 'python -m pip install .' at $(date)"
echo "Calling setup.py install at $(date)"
if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"
@ -120,7 +120,7 @@ fi
# TODO: Remove this flag once https://github.com/pytorch/pytorch/issues/55952 is closed
CFLAGS='-Wno-deprecated-declarations' \
BUILD_LIBTORCH_CPU_WITH_DEBUG=1 \
python -m pip install --no-build-isolation -v .
python setup.py install
mkdir -p libtorch/{lib,bin,include,share}

View File

@ -19,7 +19,7 @@ git config --global --add safe.directory /var/lib/jenkins/workspace
if [[ "$BUILD_ENVIRONMENT" == *onnx* ]]; then
# TODO: This can be removed later once vision is also part of the Docker image
pip install -q --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"
pip install -q --user --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"
# JIT C++ extensions require ninja, so put it into PATH.
export PATH="/var/lib/jenkins/.local/bin:$PATH"
# NB: ONNX test is fast (~15m) so it's ok to retry it few more times to avoid any flaky issue, we

34
.ci/pytorch/build-mobile.sh Executable file
View File

@ -0,0 +1,34 @@
#!/usr/bin/env bash
# DO NOT ADD 'set -x' not to reveal CircleCI secret context environment variables
set -eu -o pipefail
# This script uses linux host toolchain + mobile build options in order to
# build & test mobile libtorch without having to setup Android/iOS
# toolchain/simulator.
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
# Install torch & torchvision - used to download & trace test model.
# Ideally we should use the libtorch built on the PR so that backward
# incompatible changes won't break this script - but it will significantly slow
# down mobile CI jobs.
# Here we install nightly instead of stable so that we have an option to
# temporarily skip mobile CI jobs on BC-breaking PRs until they are in nightly.
retry pip install --pre torch torchvision \
-f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html \
--progress-bar off
# Run end-to-end process of building mobile library, linking into the predictor
# binary, and running forward pass with a real model.
if [[ "$BUILD_ENVIRONMENT" == *-mobile-custom-build-static* ]]; then
TEST_CUSTOM_BUILD_STATIC=1 test/mobile/custom_build/build.sh
elif [[ "$BUILD_ENVIRONMENT" == *-mobile-lightweight-dispatch* ]]; then
test/mobile/lightweight_dispatch/build.sh
else
TEST_DEFAULT_BUILD=1 test/mobile/custom_build/build.sh
fi
print_sccache_stats

View File

@ -11,6 +11,10 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
if [[ "$BUILD_ENVIRONMENT" == *-mobile-*build* ]]; then
exec "$(dirname "${BASH_SOURCE[0]}")/build-mobile.sh" "$@"
fi
echo "Python version:"
python --version
@ -50,6 +54,9 @@ if [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
export ATEN_THREADING=NATIVE
fi
# Enable LLVM dependency for TensorExpr testing
export USE_LLVM=/opt/llvm
export LLVM_DIR=/opt/llvm/lib/cmake/llvm
if ! which conda; then
# In ROCm CIs, we are doing cross compilation on build machines with
@ -117,8 +124,26 @@ if [[ "$BUILD_ENVIRONMENT" == *libtorch* ]]; then
fi
# Use special scripts for Android builds
if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
export ANDROID_NDK=/opt/ndk
build_args=()
if [[ "${BUILD_ENVIRONMENT}" == *-arm-v7a* ]]; then
build_args+=("-DANDROID_ABI=armeabi-v7a")
elif [[ "${BUILD_ENVIRONMENT}" == *-arm-v8a* ]]; then
build_args+=("-DANDROID_ABI=arm64-v8a")
elif [[ "${BUILD_ENVIRONMENT}" == *-x86_32* ]]; then
build_args+=("-DANDROID_ABI=x86")
elif [[ "${BUILD_ENVIRONMENT}" == *-x86_64* ]]; then
build_args+=("-DANDROID_ABI=x86_64")
fi
if [[ "${BUILD_ENVIRONMENT}" == *vulkan* ]]; then
build_args+=("-DUSE_VULKAN=ON")
fi
build_args+=("-DUSE_LITE_INTERPRETER_PROFILER=OFF")
exec ./scripts/build_android.sh "${build_args[@]}" "$@"
fi
if [[ "$BUILD_ENVIRONMENT" == *vulkan* ]]; then
if [[ "$BUILD_ENVIRONMENT" != *android* && "$BUILD_ENVIRONMENT" == *vulkan* ]]; then
export USE_VULKAN=1
# shellcheck disable=SC1091
source /var/lib/jenkins/vulkansdk/setup-env.sh
@ -189,6 +214,7 @@ if [[ "$BUILD_ENVIRONMENT" == *-clang*-asan* ]]; then
export USE_ASAN=1
export REL_WITH_DEB_INFO=1
export UBSAN_FLAGS="-fno-sanitize-recover=all"
unset USE_LLVM
fi
if [[ "${BUILD_ENVIRONMENT}" == *no-ops* ]]; then
@ -199,7 +225,7 @@ if [[ "${BUILD_ENVIRONMENT}" == *-pch* ]]; then
export USE_PRECOMPILED_HEADERS=1
fi
if [[ "${BUILD_ENVIRONMENT}" != *cuda* ]]; then
if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* ]]; then
export BUILD_STATIC_RUNTIME_BENCHMARK=ON
fi
@ -280,22 +306,6 @@ else
fi
pip_install_whl "$(echo dist/*.whl)"
if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *vision* ]]; then
install_torchvision
fi
if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *audio* ]]; then
install_torchaudio
fi
if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *torchrec* || "${BUILD_ADDITIONAL_PACKAGES:-}" == *fbgemm* ]]; then
install_torchrec_and_fbgemm
fi
if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *torchao* ]]; then
install_torchao
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
echo "Checking that xpu is compiled"
pushd dist/

View File

@ -78,34 +78,6 @@ function pip_install_whl() {
fi
}
function pip_build_and_install() {
local build_target=$1
local wheel_dir=$2
local found_whl=0
for file in "${wheel_dir}"/*.whl
do
if [[ -f "${file}" ]]; then
found_whl=1
break
fi
done
# Build the wheel if it doesn't exist
if [ "${found_whl}" == "0" ]; then
python3 -m pip wheel \
--no-build-isolation \
--no-deps \
--no-use-pep517 \
-w "${wheel_dir}" \
"${build_target}"
fi
for file in "${wheel_dir}"/*.whl
do
pip_install_whl "${file}"
done
}
function pip_install() {
# retry 3 times
@ -152,7 +124,14 @@ function get_pinned_commit() {
function install_torchaudio() {
local commit
commit=$(get_pinned_commit audio)
pip_build_and_install "git+https://github.com/pytorch/audio.git@${commit}" dist/audio
if [[ "$1" == "cuda" ]]; then
# TODO: This is better to be passed as a parameter from _linux-test workflow
# so that it can be consistent with what is set in build
TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
else
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
fi
}
function install_torchtext() {
@ -160,8 +139,8 @@ function install_torchtext() {
local text_commit
data_commit=$(get_pinned_commit data)
text_commit=$(get_pinned_commit text)
pip_build_and_install "git+https://github.com/pytorch/data.git@${data_commit}" dist/data
pip_build_and_install "git+https://github.com/pytorch/text.git@${text_commit}" dist/text
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/data.git@${data_commit}"
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/text.git@${text_commit}"
}
function install_torchvision() {
@ -174,14 +153,7 @@ function install_torchvision() {
echo 'char* dlerror(void) { return "";}'|gcc -fpic -shared -o "${HOME}/dlerror.so" -x c -
LD_PRELOAD=${orig_preload}:${HOME}/dlerror.so
fi
if [[ "${BUILD_ENVIRONMENT}" == *cuda* ]]; then
# Not sure if both are needed, but why not
export FORCE_CUDA=1
export WITH_CUDA=1
fi
pip_build_and_install "git+https://github.com/pytorch/vision.git@${commit}" dist/vision
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/vision.git@${commit}"
if [ -n "${LD_PRELOAD}" ]; then
LD_PRELOAD=${orig_preload}
fi
@ -201,73 +173,25 @@ function install_torchrec_and_fbgemm() {
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]] ; then
# install torchrec first because it installs fbgemm nightly on top of rocm fbgemm
pip_build_and_install "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}" dist/torchrec
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
pip_uninstall fbgemm-gpu-nightly
# Set ROCM_HOME isn't available, use ROCM_PATH if set or /opt/rocm
ROCM_HOME="${ROCM_HOME:-${ROCM_PATH:-/opt/rocm}}"
# Find rocm_version.h header file for ROCm version extract
rocm_version_h="${ROCM_HOME}/include/rocm-core/rocm_version.h"
if [ ! -f "$rocm_version_h" ]; then
rocm_version_h="${ROCM_HOME}/include/rocm_version.h"
fi
# Error out if rocm_version.h not found
if [ ! -f "$rocm_version_h" ]; then
echo "Error: rocm_version.h not found in expected locations." >&2
exit 1
fi
# Extract major, minor and patch ROCm version numbers
MAJOR_VERSION=$(grep 'ROCM_VERSION_MAJOR' "$rocm_version_h" | awk '{print $3}')
MINOR_VERSION=$(grep 'ROCM_VERSION_MINOR' "$rocm_version_h" | awk '{print $3}')
PATCH_VERSION=$(grep 'ROCM_VERSION_PATCH' "$rocm_version_h" | awk '{print $3}')
ROCM_INT=$((MAJOR_VERSION * 10000 + MINOR_VERSION * 100 + PATCH_VERSION))
echo "ROCm version: $ROCM_INT"
export BUILD_ROCM_VERSION="$MAJOR_VERSION.$MINOR_VERSION"
pip_install tabulate # needed for newer fbgemm
pip_install patchelf # needed for rocm fbgemm
pushd /tmp
local wheel_dir=dist/fbgemm_gpu
local found_whl=0
for file in "${wheel_dir}"/*.whl
do
if [[ -f "${file}" ]]; then
found_whl=1
break
fi
done
# Build the wheel if it doesn't exist
if [ "${found_whl}" == "0" ]; then
git clone --recursive https://github.com/pytorch/fbgemm
pushd fbgemm/fbgemm_gpu
git checkout "${fbgemm_commit}"
python setup.py bdist_wheel \
--build-variant=rocm \
-DHIP_ROOT_DIR="${ROCM_PATH}" \
-DCMAKE_C_FLAGS="-DTORCH_USE_HIP_DSA" \
-DCMAKE_CXX_FLAGS="-DTORCH_USE_HIP_DSA"
popd
# Save the wheel before cleaning up
mkdir -p dist/fbgemm_gpu
cp fbgemm/fbgemm_gpu/dist/*.whl dist/fbgemm_gpu
fi
for file in "${wheel_dir}"/*.whl
do
pip_install_whl "${file}"
done
rm -rf fbgemm
git clone --recursive https://github.com/pytorch/fbgemm
pushd fbgemm/fbgemm_gpu
git checkout "${fbgemm_commit}"
python setup.py install \
--package_variant=rocm \
-DHIP_ROOT_DIR="${ROCM_PATH}" \
-DCMAKE_C_FLAGS="-DTORCH_USE_HIP_DSA" \
-DCMAKE_CXX_FLAGS="-DTORCH_USE_HIP_DSA"
popd
rm -rf fbgemm
else
pip_build_and_install "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}" dist/torchrec
pip_build_and_install "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#subdirectory=fbgemm_gpu" dist/fbgemm_gpu
# See https://github.com/pytorch/pytorch/issues/106971
CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 --user "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
fi
}
@ -310,7 +234,7 @@ function checkout_install_torchbench() {
function install_torchao() {
local commit
commit=$(get_pinned_commit torchao)
pip_build_and_install "git+https://github.com/pytorch/ao.git@${commit}" dist/ao
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/ao.git@${commit}"
}
function print_sccache_stats() {

View File

@ -0,0 +1,123 @@
from datetime import datetime, timedelta, timezone
from tempfile import mkdtemp
from cryptography import x509
from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.x509.oid import NameOID
temp_dir = mkdtemp()
print(temp_dir)
def genrsa(path):
key = rsa.generate_private_key(
public_exponent=65537,
key_size=2048,
)
with open(path, "wb") as f:
f.write(
key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.TraditionalOpenSSL,
encryption_algorithm=serialization.NoEncryption(),
)
)
return key
def create_cert(path, C, ST, L, O, key):
subject = issuer = x509.Name(
[
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
]
)
cert = (
x509.CertificateBuilder()
.subject_name(subject)
.issuer_name(issuer)
.public_key(key.public_key())
.serial_number(x509.random_serial_number())
.not_valid_before(datetime.now(timezone.utc))
.not_valid_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc) + timedelta(days=10)
)
.add_extension(
x509.BasicConstraints(ca=True, path_length=None),
critical=True,
)
.sign(key, hashes.SHA256())
)
# Write our certificate out to disk.
with open(path, "wb") as f:
f.write(cert.public_bytes(serialization.Encoding.PEM))
return cert
def create_req(path, C, ST, L, O, key):
csr = (
x509.CertificateSigningRequestBuilder()
.subject_name(
x509.Name(
[
# Provide various details about who we are.
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
]
)
)
.sign(key, hashes.SHA256())
)
with open(path, "wb") as f:
f.write(csr.public_bytes(serialization.Encoding.PEM))
return csr
def sign_certificate_request(path, csr_cert, ca_cert, private_ca_key):
cert = (
x509.CertificateBuilder()
.subject_name(csr_cert.subject)
.issuer_name(ca_cert.subject)
.public_key(csr_cert.public_key())
.serial_number(x509.random_serial_number())
.not_valid_before(datetime.now(timezone.utc))
.not_valid_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc) + timedelta(days=10)
# Sign our certificate with our private key
)
.sign(private_ca_key, hashes.SHA256())
)
with open(path, "wb") as f:
f.write(cert.public_bytes(serialization.Encoding.PEM))
return cert
ca_key = genrsa(temp_dir + "/ca.key")
ca_cert = create_cert(
temp_dir + "/ca.pem",
"US",
"New York",
"New York",
"Gloo Certificate Authority",
ca_key,
)
pkey = genrsa(temp_dir + "/pkey.key")
csr = create_req(
temp_dir + "/csr.csr",
"US",
"California",
"San Francisco",
"Gloo Testing Company",
pkey,
)
cert = sign_certificate_request(temp_dir + "/cert.pem", csr, ca_cert, ca_key)

View File

@ -185,7 +185,7 @@ torchbench_setup_macos() {
}
pip_benchmark_deps() {
python -mpip install --no-input requests cython scikit-learn six
python -mpip install --no-input astunparse requests cython scikit-learn
}

18
.ci/pytorch/run_glootls_test.sh Executable file
View File

@ -0,0 +1,18 @@
#!/bin/bash
CREATE_TEST_CERT="$(dirname "${BASH_SOURCE[0]}")/create_test_cert.py"
TMP_CERT_DIR=$(python "$CREATE_TEST_CERT")
openssl verify -CAfile "${TMP_CERT_DIR}/ca.pem" "${TMP_CERT_DIR}/cert.pem"
export GLOO_DEVICE_TRANSPORT=TCP_TLS
export GLOO_DEVICE_TRANSPORT_TCP_TLS_PKEY=${TMP_CERT_DIR}/pkey.key
export GLOO_DEVICE_TRANSPORT_TCP_TLS_CERT=${TMP_CERT_DIR}/cert.pem
export GLOO_DEVICE_TRANSPORT_TCP_TLS_CA_FILE=${TMP_CERT_DIR}/ca.pem
time python test/run_test.py --include distributed/test_c10d_gloo --verbose -- ProcessGroupGlooTest
unset GLOO_DEVICE_TRANSPORT
unset GLOO_DEVICE_TRANSPORT_TCP_TLS_PKEY
unset GLOO_DEVICE_TRANSPORT_TCP_TLS_CERT
unset GLOO_DEVICE_TRANSPORT_TCP_TLS_CA_FILE

View File

@ -74,13 +74,12 @@ else
fi
# Environment initialization
retry pip install -qUr requirements-build.txt
if [[ "$(uname)" == Darwin ]]; then
# Install the testing dependencies
retry pip install -q future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest
retry pip install -q future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
else
retry pip install -qr requirements.txt || true
retry pip install -q hypothesis protobuf pytest || true
retry pip install -q hypothesis protobuf pytest setuptools || true
numpy_ver=1.15
case "$(python --version 2>&1)" in
*2* | *3.5* | *3.6*)

View File

@ -385,29 +385,6 @@ def smoke_test_compile(device: str = "cpu") -> None:
x_pt2 = torch.compile(model, mode="max-autotune")(x)
def smoke_test_nvshmem() -> None:
if not torch.cuda.is_available():
print("CUDA is not available, skipping NVSHMEM test")
return
# Check if NVSHMEM is compiled in current build
try:
from torch._C._distributed_c10d import _is_nvshmem_available
except ImportError:
# Not built with NVSHMEM support.
# torch is not compiled with NVSHMEM prior to 2.9
if torch.__version__ < "2.9":
return
else:
# After 2.9: NVSHMEM is expected to be compiled in current build
raise RuntimeError("torch not compiled with NVSHMEM") from None
print("torch compiled with NVSHMEM")
# Check if NVSHMEM is available on current system.
print(f"NVSHMEM available at run time: {_is_nvshmem_available()}")
def smoke_test_modules():
cwd = os.getcwd()
for module in MODULES:
@ -502,8 +479,6 @@ def main() -> None:
options.pypi_pkg_check,
)
smoke_test_nvshmem()
if __name__ == "__main__":
main()

View File

@ -165,6 +165,8 @@ elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
# setting PYTHON_TEST_EXTRA_OPTION
export PYTHON_TEST_EXTRA_OPTION="--xpu"
# Disable sccache for xpu test due to flaky issue https://github.com/pytorch/pytorch/issues/143585
sudo rm -rf /opt/cache
fi
if [[ "$TEST_CONFIG" == *crossref* ]]; then
@ -201,7 +203,7 @@ fi
if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
# JIT C++ extensions require ninja.
pip_install "ninja==1.10.2"
pip_install --user "ninja==1.10.2"
# ninja is installed in $HOME/.local/bin, e.g., /var/lib/jenkins/.local/bin for CI user jenkins
# but this script should be runnable by any user, including root
export PATH="$HOME/.local/bin:$PATH"
@ -289,12 +291,6 @@ elif [[ $TEST_CONFIG == 'nogpu_AVX512' ]]; then
export ATEN_CPU_CAPABILITY=avx2
fi
if [[ "${TEST_CONFIG}" == "legacy_nvidia_driver" ]]; then
# Make sure that CUDA can be initialized
(cd test && python -c "import torch; torch.rand(2, 2, device='cuda')")
export USE_LEGACY_DRIVER=1
fi
test_python_legacy_jit() {
time python test/run_test.py --include test_jit_legacy test_jit_fuser_legacy --verbose
assert_git_not_dirty
@ -345,12 +341,6 @@ test_h100_symm_mem() {
assert_git_not_dirty
}
test_h100_cutlass_backend() {
# cutlass backend tests for H100
TORCHINDUCTOR_CUTLASS_DIR=$(realpath "./third_party/cutlass") python test/run_test.py --include inductor/test_cutlass_backend -k "not addmm" $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
TORCHINDUCTOR_CUTLASS_DIR=$(realpath "./third_party/cutlass") python test/run_test.py --include inductor/test_cutlass_evt $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
}
test_lazy_tensor_meta_reference_disabled() {
export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
echo "Testing lazy tensor operations without meta reference"
@ -365,6 +355,7 @@ test_dynamo_wrapped_shard() {
exit 1
fi
python tools/dynamo/verify_dynamo.py
python tools/dynamo/gb_id_mapping.py verify
# PLEASE DO NOT ADD ADDITIONAL EXCLUDES HERE.
# Instead, use @skipIfTorchDynamo on your tests.
time python test/run_test.py --dynamo \
@ -393,10 +384,9 @@ test_einops() {
test_inductor_distributed() {
# Smuggle a few multi-gpu tests here so that we don't have to request another large node
echo "Testing multi_gpu tests in test_torchinductor"
python test/run_test.py -i inductor/test_torchinductor.py -k test_multi_gpu --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_cuda_device --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_replicate_on_devices --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_on_gpu_device1 --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_gpu_device --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_load_package_multiple_gpus --verbose
python test/run_test.py -i distributed/test_c10d_functional_native.py --verbose
python test/run_test.py -i distributed/tensor/test_dtensor_compile.py --verbose
python test/run_test.py -i distributed/tensor/parallel/test_micro_pipeline_tp.py --verbose
@ -448,11 +438,11 @@ test_inductor_aoti() {
python3 tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *sm86* ]]; then
BUILD_COMMAND=(TORCH_CUDA_ARCH_LIST=8.6 USE_FLASH_ATTENTION=OFF python -m pip install --no-build-isolation -v -e .)
BUILD_COMMAND=(TORCH_CUDA_ARCH_LIST=8.6 USE_FLASH_ATTENTION=OFF python setup.py develop)
# TODO: Replace me completely, as one should not use conda libstdc++, nor need special path to TORCH_LIB
TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="/opt/conda/envs/py_3.10/lib:${TORCH_LIB_DIR}:${LD_LIBRARY_PATH}")
else
BUILD_COMMAND=(python -m pip install --no-build-isolation -v -e .)
BUILD_COMMAND=(python setup.py develop)
TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}")
fi
@ -507,7 +497,7 @@ DYNAMO_BENCHMARK_FLAGS=()
pr_time_benchmarks() {
pip_install "fbscribelogger"
pip_install --user "fbscribelogger"
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
@ -928,6 +918,12 @@ test_torchbench_gcp_smoketest(){
popd
}
test_python_gloo_with_tls() {
source "$(dirname "${BASH_SOURCE[0]}")/run_glootls_test.sh"
assert_git_not_dirty
}
test_aten() {
# Test ATen
# The following test(s) of ATen have already been skipped by caffe2 in rocm environment:
@ -974,8 +970,6 @@ test_without_numpy() {
if [[ "${TEST_CONFIG}" == *dynamo_wrapped* ]]; then
python -c "import sys;sys.path.insert(0, 'fake_numpy');import torch;torch.compile(lambda x:print(x))('Hello World')"
fi
# Regression test for https://github.com/pytorch/pytorch/pull/157734 (torch.onnx should be importable without numpy)
python -c "import sys;sys.path.insert(0, 'fake_numpy');import torch; import torch.onnx"
popd
}
@ -1039,10 +1033,20 @@ test_libtorch_api() {
mkdir -p $TEST_REPORTS_DIR
OMP_NUM_THREADS=2 TORCH_CPP_TEST_MNIST_PATH="${MNIST_DIR}" "$TORCH_BIN_DIR"/test_api --gtest_filter='-IMethodTest.*' --gtest_output=xml:$TEST_REPORTS_DIR/test_api.xml
"$TORCH_BIN_DIR"/test_tensorexpr --gtest_output=xml:$TEST_REPORTS_DIR/test_tensorexpr.xml
else
# Exclude IMethodTest that relies on torch::deploy, which will instead be ran in test_deploy
OMP_NUM_THREADS=2 TORCH_CPP_TEST_MNIST_PATH="${MNIST_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_api -k "not IMethodTest"
# On s390x, pytorch is built without llvm.
# Even if it would be built with llvm, llvm currently doesn't support used features on s390x and
# test fails with errors like:
# JIT session error: Unsupported target machine architecture in ELF object pytorch-jitted-objectbuffer
# unknown file: Failure
# C++ exception with description "valOrErr INTERNAL ASSERT FAILED at "/var/lib/jenkins/workspace/torch/csrc/jit/tensorexpr/llvm_jit.h":34, please report a bug to PyTorch. Unexpected failure in LLVM JIT: Failed to materialize symbols: { (main, { func }) }
if [[ "${BUILD_ENVIRONMENT}" != *s390x* ]]; then
python test/run_test.py --cpp --verbose -i cpp/test_tensorexpr
fi
fi
# quantization is not fully supported on s390x yet
@ -1310,13 +1314,10 @@ EOF
# Step 2. Make sure that the public API test "test_correct_module_names" fails when an existing
# file is modified to introduce an invalid public API function.
# The filepath here must not have __all__ defined in it, otherwise the test will pass.
# If your PR introduces __all__ to torch/cuda/streams.py please point this to another file
# that does not have __all__ defined.
EXISTING_FILEPATH="${TORCH_INSTALL_DIR}/cuda/streams.py"
EXISTING_FILEPATH="${TORCH_INSTALL_DIR}/nn/parameter.py"
cp -v "${EXISTING_FILEPATH}" "${EXISTING_FILEPATH}.orig"
echo "${BAD_PUBLIC_FUNC}" >> "${EXISTING_FILEPATH}"
invalid_api="torch.cuda.streams.new_public_func"
invalid_api="torch.nn.parameter.new_public_func"
echo "Appended an invalid public API function to existing file ${EXISTING_FILEPATH}..."
check_public_api_test_fails \
@ -1471,8 +1472,8 @@ test_bazel() {
test_benchmarks() {
if [[ "$BUILD_ENVIRONMENT" == *cuda* && $TEST_CONFIG != *nogpu* ]]; then
pip_install "pytest-benchmark==3.2.3"
pip_install "requests"
pip_install --user "pytest-benchmark==3.2.3"
pip_install --user "requests"
BENCHMARK_DATA="benchmarks/.data"
mkdir -p ${BENCHMARK_DATA}
pytest benchmarks/fastrnns/test_bench.py --benchmark-sort=Name --benchmark-json=${BENCHMARK_DATA}/fastrnns_default.json --fuser=default --executor=default
@ -1550,7 +1551,7 @@ test_executorch() {
test_linux_aarch64() {
python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops test_cpp_extensions_open_device_registration \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
@ -1580,7 +1581,7 @@ test_operator_benchmark() {
test_inductor_set_cpu_affinity
cd benchmarks/operator_benchmark/pt_extension
python -m pip install .
python setup.py install
cd "${TEST_DIR}"/benchmarks/operator_benchmark
$TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
@ -1600,13 +1601,7 @@ if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-baze
fi
if [[ "${TEST_CONFIG}" == *numpy_2* ]]; then
# Install numpy-2.0.2 and compatible scipy & numba versions
# Force re-install of pandas to avoid error where pandas checks numpy version from initial install and fails upon import
TMP_PANDAS_VERSION=$(python -c "import pandas; print(pandas.__version__)" 2>/dev/null)
if [ -n "$TMP_PANDAS_VERSION" ]; then
python -m pip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0 pandas=="$TMP_PANDAS_VERSION" --force-reinstall
else
python -m pip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0
fi
python -mpip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0
python test/run_test.py --include dynamo/test_functions.py dynamo/test_unspec.py test_binary_ufuncs.py test_fake_tensor.py test_linalg.py test_numpy_interop.py test_tensor_creation_ops.py test_torch.py torch_np/test_basic.py
elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
test_linux_aarch64
@ -1660,19 +1655,23 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
id=$((SHARD_NUMBER-1))
test_dynamo_benchmark timm_models "$id"
elif [[ "${TEST_CONFIG}" == cachebench ]]; then
install_torchaudio
install_torchaudio cuda
install_torchvision
checkout_install_torchbench nanogpt BERT_pytorch resnet50 hf_T5 llama moco
PYTHONPATH=$(pwd)/torchbench test_cachebench
elif [[ "${TEST_CONFIG}" == verify_cachebench ]]; then
install_torchaudio
install_torchaudio cpu
install_torchvision
checkout_install_torchbench nanogpt
PYTHONPATH=$(pwd)/torchbench test_verify_cachebench
elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
install_torchaudio
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
install_torchaudio cpu
else
install_torchaudio cuda
fi
install_torchvision
install_torchao
TORCH_CUDA_ARCH_LIST="8.0;8.6" install_torchao
id=$((SHARD_NUMBER-1))
# https://github.com/opencv/opencv-python/issues/885
pip_install opencv-python==4.8.0.74
@ -1763,8 +1762,6 @@ elif [[ "${TEST_CONFIG}" == h100_distributed ]]; then
test_h100_distributed
elif [[ "${TEST_CONFIG}" == "h100-symm-mem" ]]; then
test_h100_symm_mem
elif [[ "${TEST_CONFIG}" == h100_cutlass_backend ]]; then
test_h100_cutlass_backend
else
install_torchvision
install_monkeytype

View File

@ -1,34 +0,0 @@
# If you want to rebuild, run this with $env:REBUILD=1
# If you want to build with CUDA, run this with $env:USE_CUDA=1
# If you want to build without CUDA, run this with $env:USE_CUDA=0
# Check for setup.py in the current directory
if (-not (Test-Path "setup.py")) {
Write-Host "ERROR: Please run this build script from PyTorch root directory."
exit 1
}
# Get the script's parent directory
$ScriptParentDir = Split-Path -Parent $MyInvocation.MyCommand.Definition
# Set TMP_DIR and convert to Windows path
$env:TMP_DIR = Join-Path (Get-Location) "build\win_tmp"
$env:TMP_DIR_WIN = $env:TMP_DIR # Already in Windows format, no cygpath needed
# Set final package directory with default fallback
if (-not $env:PYTORCH_FINAL_PACKAGE_DIR) {
$env:PYTORCH_FINAL_PACKAGE_DIR = "C:\w\build-results"
}
# Create the final package directory if it doesn't exist
if (-not (Test-Path $env:PYTORCH_FINAL_PACKAGE_DIR)) {
New-Item -Path $env:PYTORCH_FINAL_PACKAGE_DIR -ItemType Directory -Force | Out-Null
}
# Set script helpers directory
$env:SCRIPT_HELPERS_DIR = Join-Path $ScriptParentDir "win-test-helpers\arm64"
# Run the main build script
& "$env:SCRIPT_HELPERS_DIR\build_pytorch.ps1"
Write-Host "BUILD PASSED"

View File

@ -1,24 +0,0 @@
#!/bin/bash
set -ex -o pipefail
SCRIPT_PARENT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
# shellcheck source=./common.sh
source "$SCRIPT_PARENT_DIR/common.sh"
run_tests() {
echo Running smoke_test.py...
python ./.ci/pytorch/smoke_test/smoke_test.py --package torchonly
echo Running test_autograd.oy, test_nn.py, test_torch.py...
cd test
CORE_TEST_LIST=("test_autograd.py" "test_nn.py" "test_modules.py")
for t in "${CORE_TEST_LIST[@]}"; do
echo "Running test: $t"
python "$t" --verbose --save-xml --use-pytest -vvvv -rfEsxXP -p no:xdist
done
}
run_tests
echo "TEST PASSED"

View File

@ -1,98 +0,0 @@
# TODO: we may can use existing build_pytorch.bat for arm64
if ($env:DEBUG -eq "1") {
$env:BUILD_TYPE = "debug"
} else {
$env:BUILD_TYPE = "release"
}
# This inflates our log size slightly, but it is REALLY useful to be
# able to see what our cl.exe commands are. (since you can actually
# just copy-paste them into a local Windows setup to just rebuild a
# single file.)
# log sizes are too long, but leaving this here in case someone wants to use it locally
# $env:CMAKE_VERBOSE_MAKEFILE = "1"
$env:INSTALLER_DIR = Join-Path $env:SCRIPT_HELPERS_DIR "installation-helpers"
cd ..
# Environment variables
$env:SCCACHE_IDLE_TIMEOUT = "0"
$env:SCCACHE_IGNORE_SERVER_IO_ERROR = "1"
$env:CMAKE_BUILD_TYPE = $env:BUILD_TYPE
$env:CMAKE_C_COMPILER_LAUNCHER = "sccache"
$env:CMAKE_CXX_COMPILER_LAUNCHER = "sccache"
$env:libuv_ROOT = Join-Path $env:DEPENDENCIES_DIR "libuv\install"
$env:MSSdk = "1"
if ($env:PYTORCH_BUILD_VERSION) {
$env:PYTORCH_BUILD_VERSION = $env:PYTORCH_BUILD_VERSION
$env:PYTORCH_BUILD_NUMBER = "1"
}
$env:CMAKE_POLICY_VERSION_MINIMUM = "3.5"
# Set BLAS type
if ($env:ENABLE_APL -eq "1") {
$env:BLAS = "APL"
$env:USE_LAPACK = "1"
} elseif ($env:ENABLE_OPENBLAS -eq "1") {
$env:BLAS = "OpenBLAS"
$env:OpenBLAS_HOME = Join-Path $env:DEPENDENCIES_DIR "OpenBLAS\install"
}
# Change to source directory
Set-Location $env:PYTORCH_ROOT
# Copy libuv.dll
Copy-Item -Path (Join-Path $env:libuv_ROOT "lib\Release\uv.dll") -Destination "torch\lib\uv.dll" -Force
# Create virtual environment
python -m venv .venv
.\.venv\Scripts\Activate.ps1
where.exe python
# Python install dependencies
python -m pip install --upgrade pip
pip install setuptools pyyaml
pip install -r requirements.txt
# Set after installing psutil
$env:DISTUTILS_USE_SDK = "1"
# Print all environment variables
Get-ChildItem Env:
# Start and inspect sccache
sccache --start-server
sccache --zero-stats
sccache --show-stats
# Build the wheel
python setup.py bdist_wheel
if ($LASTEXITCODE -ne 0) { exit 1 }
# Install the wheel locally
$whl = Get-ChildItem -Path "dist\*.whl" | Select-Object -First 1
if ($whl) {
python -mpip install --no-index --no-deps $whl.FullName
}
# Copy final wheel
robocopy "dist" "$env:PYTORCH_FINAL_PACKAGE_DIR" *.whl
# Export test times
python tools/stats/export_test_times.py
# Copy additional CI files
robocopy ".additional_ci_files" "$env:PYTORCH_FINAL_PACKAGE_DIR\.additional_ci_files" /E
# Save ninja log
Copy-Item -Path "build\.ninja_log" -Destination $env:PYTORCH_FINAL_PACKAGE_DIR -Force
# Final sccache stats and stop
sccache --show-stats
sccache --stop-server
exit 0

View File

@ -42,7 +42,7 @@ call choco upgrade -y cmake --no-progress --installargs 'ADD_CMAKE_TO_PATH=Syste
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
call pip install mkl==2024.2.0 mkl-static==2024.2.0 mkl-include==2024.2.0
call pip install mkl-include==2021.4.0 mkl-devel==2021.4.0
if errorlevel 1 goto fail
if not errorlevel 0 goto fail

View File

@ -41,7 +41,7 @@ fi
python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
# Install Z3 optional dependency for Windows builds.
python -m pip install z3-solver==4.15.1.0
python -m pip install z3-solver==4.12.2.0
# Install tlparse for test\dynamo\test_structured_trace.py UTs.
python -m pip install tlparse==0.3.30

View File

@ -37,10 +37,10 @@ IF "%CUDA_PATH_V129%"=="" (
)
IF "%BUILD_VISION%" == "" (
set TORCH_CUDA_ARCH_LIST=7.0;7.5;8.0;8.6;9.0;10.0;12.0
set TORCH_CUDA_ARCH_LIST=7.5;8.0;8.6;9.0;10.0;12.0
set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
) ELSE (
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
)
set "CUDA_PATH=%CUDA_PATH_V129%"

View File

@ -148,7 +148,14 @@ if "%NVIDIA_GPU_EXISTS%" == "0" (
goto end
)
cl %PYTORCH_ROOT%\.ci\pytorch\test_example_code\check-torch-cuda.cpp torch_cpu.lib c10.lib torch_cuda.lib /EHsc /std:c++17 /link /INCLUDE:?warp_size@cuda@at@@YAHXZ
set BUILD_SPLIT_CUDA=
if exist "%install_root%\lib\torch_cuda_cu.lib" if exist "%install_root%\lib\torch_cuda_cpp.lib" set BUILD_SPLIT_CUDA=ON
if "%BUILD_SPLIT_CUDA%" == "ON" (
cl %PYTORCH_ROOT%\.ci\pytorch\test_example_code\check-torch-cuda.cpp torch_cpu.lib c10.lib torch_cuda_cu.lib torch_cuda_cpp.lib /EHsc /std:c++17 /link /INCLUDE:?warp_size@cuda@at@@YAHXZ /INCLUDE:?_torch_cuda_cu_linker_symbol_op_cuda@native@at@@YA?AVTensor@2@AEBV32@@Z
) else (
cl %PYTORCH_ROOT%\.ci\pytorch\test_example_code\check-torch-cuda.cpp torch_cpu.lib c10.lib torch_cuda.lib /EHsc /std:c++17 /link /INCLUDE:?warp_size@cuda@at@@YAHXZ
)
.\check-torch-cuda.exe
if ERRORLEVEL 1 exit /b 1

View File

@ -127,7 +127,7 @@ export INSTALL_TEST=0 # dont install test binaries into site-packages
export MACOSX_DEPLOYMENT_TARGET=10.15
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
SETUPTOOLS_PINNED_VERSION="==70.1.0"
SETUPTOOLS_PINNED_VERSION="=46.0.0"
PYYAML_PINNED_VERSION="=5.3"
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
@ -135,7 +135,7 @@ RENAME_WHEEL=true
case $desired_python in
3.13t)
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=68.0.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="=2.1.0"
CONDA_ENV_CREATE_FLAGS="python-freethreading"
@ -145,31 +145,31 @@ case $desired_python in
;;
3.13)
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=68.0.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="=2.1.0"
;;
3.12)
echo "Using 3.12 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=68.0.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="=2.0.2"
;;
3.11)
echo "Using 3.11 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=46.0.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="=2.0.2"
;;
3.10)
echo "Using 3.10 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=46.0.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="=2.0.2"
;;
3.9)
echo "Using 3.9 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
SETUPTOOLS_PINNED_VERSION=">=46.0.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="=2.0.2"
;;
@ -184,8 +184,7 @@ tmp_env_name="wheel_py$python_nodot"
conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
source activate "$tmp_env_name"
retry pip install -r "${pytorch_rootdir}/requirements-build.txt"
pip install "numpy=${NUMPY_PINNED_VERSION}" "pyyaml${PYYAML_PINNED_VERSION}" requests ninja "setuptools${SETUPTOOLS_PINNED_VERSION}" typing-extensions
pip install "numpy=${NUMPY_PINNED_VERSION}" "pyyaml${PYYAML_PINNED_VERSION}" requests ninja "setuptools${SETUPTOOLS_PINNED_VERSION}" typing_extensions
retry pip install -r "${pytorch_rootdir}/requirements.txt" || true
retry brew install libomp

View File

@ -120,7 +120,6 @@ UseTab: Never
Language: ObjC
ColumnLimit: 120
AlignAfterOpenBracket: Align
IndentWidth: 2
ObjCBlockIndentWidth: 2
ObjCSpaceAfterProperty: false
ObjCSpaceBeforeProtocolList: false

View File

@ -61,8 +61,8 @@ You are now all set to start developing with PyTorch in a DevContainer environme
## Step 8: Build PyTorch
To build pytorch from source, simply run:
```bash
python -m pip install --no-build-isolation -v -e .
```
python setup.py develop
```
The process involves compiling thousands of files, and would take a long time. Fortunately, the compiled objects can be useful for your next build. When you modify some files, you only need to compile the changed files the next time.

View File

@ -1,36 +1,14 @@
root = true
[*]
charset = utf-8
end_of_line = lf
insert_final_newline = true
# Python
[*.{py,pyi,py.in,pyi.in}]
[*.py]
indent_style = space
indent_size = 4
# C/C++/CUDA
[*.{cpp,hpp,cxx,cc,c,h,cu,cuh}]
indent_style = space
indent_size = 2
# Objective-C
[*.{mm,m,M}]
indent_style = space
indent_size = 2
# Clang tools
[.clang-{format,tidy}]
indent_style = space
indent_size = 2
# Make
[Makefile]
indent_style = tab
# Batch file
[*.bat]
indent_style = space
indent_size = 2
end_of_line = crlf

View File

@ -7,12 +7,12 @@ max-line-length = 120
# C408 ignored because we like the dict keyword argument syntax
# E501 is not flexible enough, we're using B950 instead
ignore =
E203,E305,E402,E501,E704,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,F824,
E203,E305,E402,E501,E704,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,
# shebang has extra meaning in fbcode lints, so I think it's not worth trying
# to line this up with executable bit
EXE001,
# these ignores are from flake8-bugbear; please fix!
B007,B008,B017,B019,B023,B028,B903,B904,B905,B906,B907,B908,B910
B007,B008,B017,B019,B023,B028,B903,B904,B905,B906,B907
# these ignores are from flake8-comprehensions; please fix!
C407,
# these ignores are from flake8-logging-format; please fix!

View File

@ -57,6 +57,9 @@ self-hosted-runner:
- linux.rocm.gpu.mi300.2
- linux.rocm.gpu.mi300.4
- rocm-docker
# Repo-specific Apple hosted runners
- macos-m1-ultra
- macos-m2-14
# Org wise AWS `mac2.metal` runners (2020 Mac mini hardware powered by Apple silicon M1 processors)
- macos-m1-stable
- macos-m1-13

View File

@ -0,0 +1,78 @@
name: build android
description: build android for a specific arch
inputs:
arch:
description: arch to build
required: true
arch-for-build-env:
description: |
arch to pass to build environment.
This is currently different than the arch name we use elsewhere, which
should be fixed.
required: true
github-secret:
description: github token
required: true
build-environment:
required: true
description: Top-level label for what's being built/tested.
docker-image:
required: true
description: Name of the base docker image to build with.
branch:
required: true
description: What branch we are building on.
outputs:
container_id:
description: Docker container identifier used to build the artifacts
value: ${{ steps.build.outputs.container_id }}
runs:
using: composite
steps:
- name: Build-${{ inputs.arch }}
id: build
shell: bash
env:
BRANCH: ${{ inputs.branch }}
BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-${{ inputs.arch-for-build-env }}-build"
AWS_DEFAULT_REGION: us-east-1
PR_NUMBER: ${{ github.event.pull_request.number }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
SCCACHE_REGION: us-east-1
DOCKER_IMAGE: ${{ inputs.docker-image }}
MATRIX_ARCH: ${{ inputs.arch }}
run: |
# detached container should get cleaned up by teardown_ec2_linux
set -exo pipefail
export container_name
container_name=$(docker run \
-e BUILD_ENVIRONMENT \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e AWS_DEFAULT_REGION \
-e PR_NUMBER \
-e SHA1 \
-e BRANCH \
-e SCCACHE_BUCKET \
-e SCCACHE_REGION \
-e SKIP_SCCACHE_INITIALIZATION=1 \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
--tty \
--detach \
--user jenkins \
-w /var/lib/jenkins/workspace \
"${DOCKER_IMAGE}"
)
git submodule sync && git submodule update -q --init --recursive --depth 1
docker cp "${GITHUB_WORKSPACE}/." "${container_name}:/var/lib/jenkins/workspace"
(echo "sudo chown -R jenkins . && .ci/pytorch/build.sh && find ${BUILD_ROOT} -type f -name "*.a" -or -name "*.o" -delete" | docker exec -u jenkins -i "${container_name}" bash) 2>&1
# Copy install binaries back
mkdir -p "${GITHUB_WORKSPACE}/build_android_install_${MATRIX_ARCH}"
docker cp "${container_name}:/var/lib/jenkins/workspace/build_android/install" "${GITHUB_WORKSPACE}/build_android_install_${MATRIX_ARCH}"
echo "container_id=${container_name}" >> "${GITHUB_OUTPUT}"

View File

@ -70,7 +70,7 @@ runs:
set -eux
# PyYAML 6.0 doesn't work with MacOS x86 anymore
# This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2
python3 -m pip install requests==2.27.1 pyyaml==6.0.2
python3 -m pip install requests==2.27.1 pyyaml==6.0.1
- name: Parse ref
id: parse-ref

View File

@ -126,7 +126,7 @@ runs:
shell: bash
continue-on-error: true
run: |
python3 -m pip install psutil==5.9.8 nvidia-ml-py==11.525.84
python3 -m pip install psutil==5.9.1 nvidia-ml-py==11.525.84
python3 -m tools.stats.monitor > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"

View File

@ -1 +1 @@
f6dfe1231dcdd221a68416e49ab85c2575cbb824
70caf76066ef2c1054d6128b11769dc816a779e7

View File

@ -1 +1 @@
7f1de94a4c2d14f59ad4ca84538c36084ea6b2c8
5fb5024118e9bb9decf96c2b0b1a8f0010bf56be

View File

@ -1 +0,0 @@
8f605ee30912541126c0fe46d0c8c413101b600a

View File

@ -1 +1 @@
29ae4c76c026185f417a25e841d2cd5e65f087a3
1c00dea2c9adb2137903c86b4191e8c247f8fda9

View File

@ -76,7 +76,6 @@
- .github/ci_commit_pins/audio.txt
- .github/ci_commit_pins/vision.txt
- .github/ci_commit_pins/torchdynamo.txt
- .github/ci_commit_pins/vllm.txt
- .ci/docker/ci_commit_pins/triton.txt
approved_by:
- pytorchbot
@ -131,6 +130,21 @@
- Lint
- pull
- name: Mobile
patterns:
- ios/**
- android/**
- test/mobile/**
approved_by:
- linbinyu
- IvanKobzarev
- dreiss
- raziel
mandatory_checks_name:
- EasyCLA
- Lint
- pull
- name: PrimTorch
patterns:
- torch/_meta_registrations.py
@ -477,19 +491,6 @@
- srossross
- chillee
- zou3519
- guilhermeleobas
mandatory_checks_name:
- EasyCLA
- Lint
- pull
- name: Dynamo
patterns:
- torch/_dynamo/**
- torch/csrc/dynamo/**
- test/dynamo/**
approved_by:
- guilhermeleobas
mandatory_checks_name:
- EasyCLA
- Lint

View File

@ -31,9 +31,7 @@ ciflow_push_tags:
- ciflow/pull
- ciflow/h100
- ciflow/h100-distributed
- ciflow/win-arm64
- ciflow/h100-symm-mem
- ciflow/h100-cutlass-backend
retryable_workflows:
- pull
- trunk

View File

@ -1,15 +1,14 @@
# This file is to cache other dependencies not specified elsewhere in:
# requirements.txt
# requirements-build.txt
# requirement.txt
# docs/requirements.txt
# docs/cpp/requirements.txt
# functorch/docs/requirements.txt
# .ci/docker/requirements-ci.txt
boto3==1.35.42
jinja2==3.1.6
lintrunner==0.12.7
lintrunner==0.10.7
ninja==1.10.0.post1
nvidia-ml-py==11.525.84
pyyaml==6.0.2
pyyaml==6.0
requests==2.32.4
rich==14.1.0
rich==10.9.0

View File

@ -2,7 +2,7 @@ boto3==1.35.42
cmake==3.27.*
expecttest==0.3.0
fbscribelogger==0.1.7
filelock==3.13.1
filelock==3.6.0
hypothesis==6.56.4
librosa>=0.6.2
mpmath==1.3.0
@ -16,7 +16,7 @@ packaging==23.1
parameterized==0.8.1
pillow==10.3.0
protobuf==5.29.4
psutil==5.9.8
psutil==5.9.1
pygments==2.15.0
pytest-cpp==2.3.0
pytest-flakefinder==1.1.0
@ -33,4 +33,4 @@ tensorboard==2.13.0
typing-extensions==4.12.2
unittest-xml-reporting<=3.2.0,>=2.0.0
xdoctest==1.1.0
z3-solver==4.15.1.0
z3-solver==4.12.2.0

View File

@ -53,7 +53,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | "
@ -70,7 +70,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | "
@ -87,7 +87,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "

View File

@ -22,7 +22,6 @@ LABEL_CIFLOW_BINARIES = "ciflow/binaries"
LABEL_CIFLOW_PERIODIC = "ciflow/periodic"
LABEL_CIFLOW_BINARIES_LIBTORCH = "ciflow/binaries_libtorch"
LABEL_CIFLOW_BINARIES_WHEEL = "ciflow/binaries_wheel"
LABEL_CIFLOW_ROCM = "ciflow/rocm"
@dataclass
@ -147,35 +146,13 @@ LINUX_BINARY_BUILD_WORFKLOWS = [
),
]
ROCM_SMOKE_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.LINUX,
package_type="manywheel",
build_variant="rocm",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["6.4"],
python_versions=["3.9"],
),
ciflow_config=CIFlowConfig(
labels={
LABEL_CIFLOW_BINARIES,
LABEL_CIFLOW_BINARIES_WHEEL,
LABEL_CIFLOW_ROCM,
},
isolated_workflow=True,
),
branches="main",
),
]
LINUX_BINARY_SMOKE_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.LINUX,
package_type="manywheel",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["12.6", "12.8", "12.9"],
arches=["12.6", "12.8", "12.9", "6.4"],
python_versions=["3.9"],
),
branches="main",
@ -410,11 +387,6 @@ def main() -> None:
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
S390X_BINARY_BUILD_WORKFLOWS,
),
(
# Give rocm it's own workflow file
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
ROCM_SMOKE_WORKFLOWS,
),
(
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
LINUX_BINARY_SMOKE_WORKFLOWS,

View File

@ -2,7 +2,7 @@
set -ex
# Use uv to speed up lintrunner init
python3 -m pip install -U uv==0.8.* setuptools
python3 -m pip install uv==0.1.45 setuptools
CACHE_DIRECTORY="/tmp/.lintbin"
# Try to recover the cached binaries

View File

@ -6,7 +6,7 @@ set -euxo pipefail
cd llm-target-determinator
pip install -q -r requirements.txt
cd ../codellama
pip install --no-build-isolation -v -e .
pip install -e .
pip install numpy==1.26.0
# Run indexer

View File

@ -70,7 +70,7 @@ jobs:
runner: ${{ inputs.runner_prefix }}linux.12xlarge
# TODO: Nightly cpp docs take longer and longer to finish (more than 3h now)
# Let's try to figure out how this can be improved
timeout-minutes: 360
timeout-minutes: 240
- docs_type: python
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 30m to finish python docs unless there are issues

View File

@ -1,43 +0,0 @@
name: Get Changed Files
on:
workflow_call:
outputs:
changed-files:
description: "List of changed files (space-separated) or '*' if not in a PR"
value: ${{ jobs.get-changed-files.outputs.changed-files }}
jobs:
get-changed-files:
runs-on: ubuntu-latest
outputs:
changed-files: ${{ steps.get-files.outputs.changed-files }}
steps:
- name: Get changed files
id: get-files
env:
GH_TOKEN: ${{ github.token }}
run: |
# Check if we're in a pull request context
if [ "${{ github.event_name }}" = "pull_request" ] || [ "${{ github.event_name }}" = "pull_request_target" ]; then
echo "Running in PR context"
# Get the PR number from the github context
PR_NUMBER="${{ github.event.number }}"
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
if [ -z "$CHANGED_FILES" ]; then
echo "No changed files found, setting to '*'"
CHANGED_FILES="*"
fi
echo "Changed files: $CHANGED_FILES"
echo "changed-files=$CHANGED_FILES" >> "$GITHUB_OUTPUT"
else
echo "Not in PR context, setting changed files to '*'"
echo "changed-files=*" >> "$GITHUB_OUTPUT"
fi

View File

@ -16,6 +16,11 @@ on:
type: boolean
default: true
description: If set, upload generated build artifacts.
build-with-debug:
required: false
type: boolean
default: false
description: If set, build in debug mode.
sync-tag:
required: false
type: string
@ -82,6 +87,7 @@ on:
required: false
type: number
default: 1
allow-reuse-old-whl:
description: |
If set, the build try to pull an old wheel from s3 that was built on a
@ -89,13 +95,6 @@ on:
required: false
type: boolean
default: true
build-additional-packages:
description: |
If set, the build job will also builds these packages and saves their
wheels as artifacts
required: false
type: string
default: ""
secrets:
HUGGING_FACE_HUB_TOKEN:
@ -107,6 +106,7 @@ on:
description: |
FB app token to write to scribe endpoint
outputs:
docker-image:
value: ${{ jobs.build.outputs.docker-image }}
@ -131,9 +131,6 @@ jobs:
if: inputs.build-environment != 'linux-s390x-binary-manywheel'
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
instructions: |
Build is done inside the container, to start an interactive session run:
docker exec -it $(docker container ps --format '{{.ID}}') bash
# [pytorch repo ref]
# Use a pytorch/pytorch reference instead of a reference to the local
@ -225,7 +222,7 @@ jobs:
MONITOR_DATA_COLLECT_INTERVAL: ${{ inputs.monitor-data-collect-interval }}
run: |
mkdir -p ../../usage_logs
python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7
python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7
python3 -m tools.stats.monitor \
--log-interval "$MONITOR_LOG_INTERVAL" \
--data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" \
@ -247,6 +244,8 @@ jobs:
env:
BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
BRANCH: ${{ steps.parse-ref.outputs.branch }}
# TODO duplicated
AWS_DEFAULT_REGION: us-east-1
PR_NUMBER: ${{ github.event.pull_request.number }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
# Do not set SCCACHE_S3_KEY_PREFIX to share the cache between all build jobs
@ -258,10 +257,10 @@ jobs:
DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
DOCKER_IMAGE_S390X: ${{ inputs.docker-image-name }}
XLA_CUDA: ${{ contains(inputs.build-environment, 'xla') && '0' || '' }}
DEBUG: ${{ inputs.build-with-debug && '1' || '0' }}
OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.SCRIBE_GRAPHQL_ACCESS_TOKEN }}
BUILD_ADDITIONAL_PACKAGES: ${{ inputs.build-additional-packages }}
run: |
START_TIME=$(date +%s)
if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
@ -293,6 +292,7 @@ jobs:
container_name=$(docker run \
-e BUILD_ENVIRONMENT \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e AWS_DEFAULT_REGION \
-e PR_NUMBER \
-e SHA1 \
-e BRANCH \
@ -307,7 +307,6 @@ jobs:
-e HUGGING_FACE_HUB_TOKEN \
-e SCRIBE_GRAPHQL_ACCESS_TOKEN \
-e USE_SPLIT_BUILD \
-e BUILD_ADDITIONAL_PACKAGES \
--memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
--memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
@ -321,11 +320,6 @@ jobs:
"${USED_IMAGE}" \
${DOCKER_SHELL_CMD}
)
if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
docker exec -t "${container_name}" sh -c "python3 -m pip install -r requirements.txt"
fi
docker exec -t "${container_name}" sh -c '.ci/pytorch/build.sh'
END_TIME=$(date +%s)

View File

@ -164,8 +164,6 @@ jobs:
- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
id: install-nvidia-driver
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
with:
driver-version: ${{ matrix.config == 'legacy_nvidia_driver' && '525.105.17' || '570.133.07' }}
if: ${{ contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' && matrix.runner != 'B200' }}
- name: Setup GPU_FLAG for docker run
@ -205,7 +203,7 @@ jobs:
MONITOR_LOG_INTERVAL: ${{ inputs.monitor-log-interval }}
MONITOR_DATA_COLLECT_INTERVAL: ${{ inputs.monitor-data-collect-interval }}
run: |
python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"

View File

@ -152,14 +152,17 @@ jobs:
env:
OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
run: |
# TODO: Remove me later, and properly activate venv
PATH="$VENV_PATH/bin:$PATH"
export PATH
echo "CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname "$(which conda)")/../"}" >> "${GITHUB_ENV}"
if [[ -n "$CONDA_ENV" ]]; then
# Use binaries under conda environment
export PATH="$CONDA_ENV/bin":$PATH
fi
# NB: Same trick as Linux, there is no need to initialize sccache with the risk of getting
# it hangs or timeout at initialization. The cache will be started automatically
export SKIP_SCCACHE_INITIALIZATION=1
.ci/pytorch/macos-build.sh
${CONDA_RUN} .ci/pytorch/macos-build.sh
- name: Archive artifacts into zip
if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped'

View File

@ -88,13 +88,9 @@ jobs:
pkill "${PROCESS}" || true
done
- name: Clean up brew miniconda, if installed
- name: Clean up leftover miniconda installation
continue-on-error: true
run: |
if brew list miniconda; then
brew uninstall miniconda
echo "REINSTALL_BREW_MINICONDA=1" >> "${GITHUB_ENV}"
fi
run: brew uninstall miniconda || true
- name: Clean up leftover local python3 site-packages on MacOS pet runner
continue-on-error: true
@ -118,12 +114,6 @@ jobs:
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
- name: Setup Python
uses: pytorch/test-infra/.github/actions/setup-python@main
with:
python-version: ${{ inputs.python-version }}
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
- name: Start monitoring script
id: monitor-script
if: ${{ !inputs.disable-monitor }}
@ -136,8 +126,8 @@ jobs:
MONITOR_LOG_INTERVAL: ${{ inputs.monitor-log-interval }}
MONITOR_DATA_COLLECT_INTERVAL: ${{ inputs.monitor-data-collect-interval }}
run: |
"$VENV_PATH/bin/python3" -m pip install psutil==5.9.8 dataclasses_sajson==0.6.7
"$VENV_PATH/bin/python3" -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7
python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
- name: Download build artifacts
@ -152,6 +142,13 @@ jobs:
with:
use-gha: true
- name: Setup Python
uses: pytorch/test-infra/.github/actions/setup-python@main
with:
python-version: ${{ inputs.python-version }}
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
default-packages: ""
- name: Parse ref
id: parse-ref
run: .github/scripts/parse_ref.py
@ -202,7 +199,7 @@ jobs:
set -ex
# TODO: Remove me later, and properly activate venv
PATH="$VENV_PATH/bin:$PATH"
PATH="$(dirname "$(which python)"):$PATH"
export PATH
# Print out some information about the test environment
@ -276,14 +273,6 @@ jobs:
workflow_attempt: ${{github.run_attempt}}
local_path: usage_log.txt
- name: Reinstall brew miniconda, if was installed
if: always()
continue-on-error: true
run: |
if [[ -n "$REINSTALL_BREW_MINICONDA" ]]; then
brew install --cask miniconda
fi
- name: Clean up disk space
if: always()
continue-on-error: true

View File

@ -132,7 +132,7 @@ jobs:
shell: bash
continue-on-error: true
run: |
python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7
python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7
python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
@ -269,8 +269,8 @@ jobs:
# copy test results back to the mounted workspace, needed sudo, resulting permissions were correct
docker exec -t "${{ env.CONTAINER_NAME }}" sh -c "cd ../pytorch && sudo cp -R test/test-reports ../workspace/test"
- name: Change permissions (only needed for MI300 and MI355 kubernetes runners for now)
if: ${{ always() && steps.test.conclusion && (contains(matrix.runner, 'mi300') || contains(matrix.runner, 'mi355')) }}
- name: Change permissions (only needed for MI300 runners for now)
if: ${{ always() && steps.test.conclusion && contains(matrix.runner, 'mi300') }}
run: |
docker exec -t "${{ env.CONTAINER_NAME }}" sh -c "sudo chown -R 1001:1001 test"

View File

@ -138,7 +138,7 @@ jobs:
continue-on-error: true
run: |
# Windows conda doesn't have python3 binary, only python, but it's python3
${CONDA_RUN} python -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
${CONDA_RUN} python -m pip install psutil==5.9.1 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
${CONDA_RUN} python -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"

View File

@ -133,7 +133,7 @@ jobs:
MONITOR_LOG_INTERVAL: ${{ inputs.monitor-log-interval }}
MONITOR_DATA_COLLECT_INTERVAL: ${{ inputs.monitor-data-collect-interval }}
run: |
python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
@ -191,6 +191,9 @@ jobs:
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
SCCACHE_REGION: us-east-1
SCCACHE_S3_KEY_PREFIX: ${{ github.workflow }}
DOCKER_IMAGE: ${{ inputs.docker-image }}
XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: ${{ matrix.mem_leak_check && '1' || '0' }}

View File

@ -50,7 +50,7 @@ jobs:
strategy:
fail-fast: false
matrix:
py_vers: [ "3.9", "3.10", "3.11", "3.12", "3.13", "3.13t", "3.14", "3.14t" ]
py_vers: [ "3.9", "3.10", "3.11", "3.12", "3.13", "3.13t" ]
device: ["cuda", "rocm", "xpu", "aarch64"]
docker-image: ["pytorch/manylinux2_28-builder:cpu"]
include:
@ -126,12 +126,6 @@ jobs:
3.13t)
PYTHON_EXECUTABLE=/opt/python/cp313-cp313t/bin/python
;;
3.14)
PYTHON_EXECUTABLE=/opt/python/cp314-cp314/bin/python
;;
3.14t)
PYTHON_EXECUTABLE=/opt/python/cp314-cp314t/bin/python
;;
*)
echo "Unsupported python version ${PY_VERS}"
exit 1

View File

@ -56,7 +56,7 @@ jobs:
cache: pip
architecture: x64
- run: pip install pyyaml==6.0.2
- run: pip install pyyaml==6.0
shell: bash
- name: Verify mergeability

View File

@ -26,7 +26,7 @@ jobs:
cache: pip
# Not the direct dependencies but the script uses trymerge
- run: pip install pyyaml==6.0.2
- run: pip install pyyaml==6.0
- name: Setup committer id
run: |

View File

@ -50,7 +50,6 @@ jobs:
runner: [linux.12xlarge]
docker-image-name: [
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11,
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc11-vllm,
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks,
pytorch-linux-jammy-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks,
pytorch-linux-jammy-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks,
@ -58,14 +57,12 @@ jobs:
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc9-inductor-benchmarks,
pytorch-linux-jammy-cuda12.8-cudnn9-py3.13-gcc9-inductor-benchmarks,
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9,
pytorch-linux-jammy-cuda12.4-cudnn9-py3-gcc11,
pytorch-linux-jammy-py3.9-clang12,
pytorch-linux-jammy-py3.11-clang12,
pytorch-linux-jammy-py3.12-clang12,
pytorch-linux-jammy-py3.13-clang12,
pytorch-linux-jammy-rocm-n-1-py3,
pytorch-linux-jammy-rocm-n-py3,
pytorch-linux-noble-rocm-n-py3,
pytorch-linux-noble-rocm-alpha-py3,
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-clang12,
pytorch-linux-jammy-py3.9-gcc11,
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks,

View File

@ -144,7 +144,7 @@ jobs:
run: |
make -f docker.Makefile "${BUILD_IMAGE_TYPE}-image"
- name: Push nightly tags
if: ${{ github.event.ref == 'refs/heads/nightly' && matrix.image_type == 'runtime' && matrix.platform == 'linux/amd4' }}
if: ${{ github.event.ref == 'refs/heads/nightly' && matrix.image_type == 'runtime' && matrix.build_platforms == 'linux/amd4' }}
run: |
PYTORCH_DOCKER_TAG="${PYTORCH_VERSION}-cuda${CUDA_VERSION_SHORT}-cudnn${CUDNN_VERSION}-runtime"
CUDA_SUFFIX="-cu${CUDA_VERSION}"

View File

@ -136,7 +136,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_9-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -252,7 +252,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -368,7 +368,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -484,7 +484,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -600,7 +600,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -716,7 +716,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -61,7 +61,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_6-test: # Testing
@ -108,7 +108,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_8-test: # Testing
@ -155,7 +155,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_9-test: # Testing
@ -182,3 +182,95 @@ jobs:
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8 and 12.9 build need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-rocm6_4-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.4
GPU_ARCH_VERSION: 6.4
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
use_split_build: False
DESIRED_PYTHON: "3.9"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-rocm6_4
build_environment: linux-binary-manywheel
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-rocm6_4-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_9-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.4
GPU_ARCH_VERSION: 6.4
GPU_ARCH_TYPE: rocm
SKIP_ALL_TESTS: 1
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
use_split_build: False
DESIRED_PYTHON: "3.9"
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- uses: actions/download-artifact@v4.1.7
name: Download Build Artifacts
with:
name: manywheel-py3_9-rocm6_4
path: "${{ runner.temp }}/artifacts/"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: ROCm set GPU_FLAG
run: |
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon" >> "${GITHUB_ENV}"
- name: configure aws credentials
id: aws_creds
if: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/') }}
uses: aws-actions/configure-aws-credentials@v4
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
role-duration-seconds: 18000
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
with:
docker-registry: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/') && '308535385114.dkr.ecr.us-east-1.amazonaws.com' || 'docker.io' }}
docker-image-name: manylinux2_28-builder
custom-tag-prefix: rocm6.4
docker-build-dir: .ci/docker
working-directory: pytorch
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Test Pytorch binary
uses: ./pytorch/.github/actions/test-pytorch-binary
env:
DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Teardown ROCm
uses: ./.github/actions/teardown-rocm

View File

@ -131,7 +131,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_6-test: # Testing
@ -200,7 +200,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_8-test: # Testing
@ -269,7 +269,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_9-test: # Testing
@ -744,7 +744,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_6-test: # Testing
@ -813,7 +813,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_8-test: # Testing
@ -882,7 +882,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_9-test: # Testing
@ -1357,7 +1357,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_6-test: # Testing
@ -1426,7 +1426,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_8-test: # Testing
@ -1563,7 +1563,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_9-test: # Testing
@ -2038,7 +2038,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_6-test: # Testing
@ -2107,7 +2107,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_8-test: # Testing
@ -2176,7 +2176,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_9-test: # Testing
@ -2651,7 +2651,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_6-test: # Testing
@ -2720,7 +2720,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_8-test: # Testing
@ -2789,7 +2789,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_9-test: # Testing
@ -3264,7 +3264,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_6-test: # Testing
@ -3333,7 +3333,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_8-test: # Testing
@ -3402,7 +3402,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_9-test: # Testing

View File

@ -1,137 +0,0 @@
# @generated DO NOT EDIT MANUALLY
# Template is at: .github/templates/linux_binary_build_workflow.yml.j2
# Generation script: .github/scripts/generate_ci_workflows.py
name: linux-binary-manywheel-rocm
on:
push:
branches:
- main
tags:
- 'ciflow/binaries/*'
- 'ciflow/binaries_wheel/*'
- 'ciflow/rocm/*'
workflow_dispatch:
permissions:
id-token: write
env:
# Needed for conda builds
ALPINE_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/tool/alpine"
AWS_DEFAULT_REGION: us-east-1
BINARY_ENV_FILE: /tmp/env
BUILD_ENVIRONMENT: linux-binary-manywheel-rocm
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.pull_request.number }}
PYTORCH_FINAL_PACKAGE_DIR: /artifacts
PYTORCH_ROOT: /pytorch
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
SKIP_ALL_TESTS: 0
concurrency:
group: linux-binary-manywheel-rocm-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
cancel-in-progress: true
jobs:
get-label-type:
if: github.repository_owner == 'pytorch'
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
manywheel-py3_9-rocm6_4-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.4
GPU_ARCH_VERSION: 6.4
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
use_split_build: False
DESIRED_PYTHON: "3.9"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_9-rocm6_4
build_environment: linux-binary-manywheel-rocm
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-rocm6_4-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_9-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.4
GPU_ARCH_VERSION: 6.4
GPU_ARCH_TYPE: rocm
SKIP_ALL_TESTS: 1
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
use_split_build: False
DESIRED_PYTHON: "3.9"
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- uses: actions/download-artifact@v4.1.7
name: Download Build Artifacts
with:
name: manywheel-py3_9-rocm6_4
path: "${{ runner.temp }}/artifacts/"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: ROCm set GPU_FLAG
run: |
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon" >> "${GITHUB_ENV}"
- name: configure aws credentials
id: aws_creds
if: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/') }}
uses: aws-actions/configure-aws-credentials@v4
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
role-duration-seconds: 18000
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
with:
docker-registry: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/') && '308535385114.dkr.ecr.us-east-1.amazonaws.com' || 'docker.io' }}
docker-image-name: manylinux2_28-builder
custom-tag-prefix: rocm6.4
docker-build-dir: .ci/docker
working-directory: pytorch
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Test Pytorch binary
uses: ./pytorch/.github/actions/test-pytorch-binary
env:
DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Teardown ROCm
uses: ./.github/actions/teardown-rocm

View File

@ -1,58 +0,0 @@
name: Limited CI for CUTLASS backend on H100
on:
pull_request:
paths:
- .github/workflows/h100-cutlass-backend.yml
workflow_dispatch:
schedule:
- cron: 22 9 * * * # every 24 hours about 2:22am PDT
push:
tags:
- ciflow/h100-cutlass-backend/*
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions:
id-token: write
contents: read
jobs:
get-label-type:
if: github.repository_owner == 'pytorch'
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-cuda12_8-py3_10-gcc11-sm90-build-cutlass-backend:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm90-cutlass-backend
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm90-cutlass-backend
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '9.0'
test-matrix: |
{ include: [
{ config: "h100_cutlass_backend", shard: 1, num_shards: 1, runner: "linux.aws.h100", owners: ["oncall:pt2"] },
]}
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc11-sm90-test:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm90-cutlass-backend
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_8-py3_10-gcc11-sm90-build-cutlass-backend
with:
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm90-cutlass-backend
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm90-build-cutlass-backend.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm90-build-cutlass-backend.outputs.test-matrix }}
secrets: inherit

View File

@ -15,10 +15,6 @@ concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions:
id-token: write
contents: read
jobs:
get-label-type:

View File

@ -15,10 +15,6 @@ concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions:
id-token: write
contents: read
jobs:
get-label-type:

View File

@ -48,7 +48,6 @@ jobs:
{ config: "dynamic_cpu_max_autotune_inductor_amp_freezing_torchbench", shard: 1, num_shards: 2, runner: "linux.8xlarge.amx" },
{ config: "dynamic_cpu_max_autotune_inductor_amp_freezing_torchbench", shard: 2, num_shards: 2, runner: "linux.8xlarge.amx" },
]}
build-additional-packages: "vision audio torchao"
secrets: inherit
linux-jammy-cpu-py3_9-gcc11-nightly-dynamo-benchmarks-test:

View File

@ -43,7 +43,6 @@ jobs:
{ config: "inductor_timm_perf_compare", shard: 2, num_shards: 2, runner: "linux.aws.a100" },
{ config: "inductor_torchbench_perf_compare", shard: 1, num_shards: 1, runner: "linux.aws.a100" },
]}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
test:

View File

@ -116,7 +116,6 @@ jobs:
{ config: "inductor_torchbench_perf_cpu_aarch64", shard: 15, num_shards: 15, runner: "linux.arm64.m7g.metal" },
]}
selected-test-configs: ${{ inputs.benchmark_configs }}
build-additional-packages: "vision audio torchao"
secrets: inherit

View File

@ -2,7 +2,7 @@ name: inductor-perf-nightly-h100
on:
schedule:
- cron: 15 0,12 * * 1-6
- cron: 15 0,4,8,12,16,20 * * 1-6
- cron: 0 7 * * 0
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
@ -86,11 +86,6 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
# Use a bigger runner here because CUDA_ARCH 9.0 is only built for H100
# or newer GPUs, so it doesn't benefit much from existing compiler cache
# from trunk. Also use a memory-intensive runner here because memory is
# usually the bottleneck
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '9.0'
@ -119,14 +114,13 @@ jobs:
{ config: "inductor_torchbench_perf_cuda_h100", shard: 9, num_shards: 9, runner: "linux.aws.h100" },
]}
selected-test-configs: ${{ inputs.benchmark_configs }}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
test-periodically:
name: cuda12.8-py3.10-gcc9-sm90
uses: ./.github/workflows/_linux-test.yml
needs: build
if: github.event.schedule == '15 0,12 * * 1-6'
if: github.event.schedule == '15 0,4,8,12,16,20 * * 1-6'
with:
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90
dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-cudagraphs_low_precision-true

View File

@ -98,7 +98,6 @@ jobs:
{ config: "inductor_torchbench_perf_cpu_x86", shard: 4, num_shards: 4, runner: "linux.24xl.spr-metal" },
]}
selected-test-configs: ${{ inputs.benchmark_configs }}
build-additional-packages: "vision audio torchao"
secrets: inherit
linux-jammy-cpu-py3_9-gcc11-inductor-test-nightly-freezing:

View File

@ -86,8 +86,6 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
# Every bit to make perf run faster helps
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm80
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
@ -114,7 +112,6 @@ jobs:
{ config: "cachebench", shard: 2, num_shards: 2, runner: "linux.aws.a100" },
]}
selected-test-configs: ${{ inputs.benchmark_configs }}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
test-nightly:

View File

@ -58,7 +58,6 @@ jobs:
{ config: "dynamic_aot_eager_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_aot_eager_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc9-periodic-dynamo-benchmarks-test:
@ -126,7 +125,6 @@ jobs:
{ include: [
{ config: "inductor_torchbench_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.aws.a100" },
]}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc9-inductor-smoke-test:
@ -161,7 +159,6 @@ jobs:
{ config: "cpu_inductor_freezing_avx2_timm", shard: 1, num_shards: 2, runner: "linux.10xlarge.avx2" },
{ config: "cpu_inductor_freezing_avx2_timm", shard: 2, num_shards: 2, runner: "linux.10xlarge.avx2" },
]}
build-additional-packages: "vision audio torchao"
secrets: inherit
linux-jammy-cpu-py3_9-gcc11-periodic-dynamo-benchmarks-test:
@ -198,7 +195,6 @@ jobs:
{ config: "aot_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc9-inductor-test:
@ -244,7 +240,6 @@ jobs:
{ config: "dynamic_cpu_aot_inductor_amp_freezing_torchbench", shard: 1, num_shards: 2, runner: "linux.8xlarge.amx" },
{ config: "dynamic_cpu_aot_inductor_amp_freezing_torchbench", shard: 2, num_shards: 2, runner: "linux.8xlarge.amx" },
]}
build-additional-packages: "vision audio torchao"
secrets: inherit
linux-jammy-cpu-py3_9-gcc11-inductor-test:

View File

@ -7,6 +7,7 @@ on:
- release/*
tags:
- ciflow/inductor-rocm/*
- ciflow/inductor/*
workflow_dispatch:
concurrency:

View File

@ -62,7 +62,6 @@ jobs:
{ config: "inductor_torchbench", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
]}
build-additional-packages: "vision audio fbgemm torchao"
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc9-inductor-test:
@ -95,7 +94,6 @@ jobs:
{ config: "dynamic_cpu_inductor_torchbench", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.8xlarge.amx" },
{ config: "inductor_torchbench_cpu_smoketest_perf", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.24xl.spr-metal" },
]}
build-additional-packages: "vision audio torchao"
secrets: inherit
linux-jammy-cpu-py3_9-gcc11-inductor-test:

View File

@ -27,29 +27,9 @@ jobs:
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
get-changed-files:
if: github.repository_owner == 'pytorch'
name: Get changed files
uses: ./.github/workflows/_get-changed-files.yml
lintrunner-clang:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
needs: [get-label-type, get-changed-files]
# Only run if there are changed files relevant to clangtidy / clangformat
if: |
github.repository_owner == 'pytorch' && (
needs.get-changed-files.outputs.changed-files == '*' ||
contains(needs.get-changed-files.outputs.changed-files, '.h') ||
contains(needs.get-changed-files.outputs.changed-files, '.cpp') ||
contains(needs.get-changed-files.outputs.changed-files, '.cc') ||
contains(needs.get-changed-files.outputs.changed-files, '.cxx') ||
contains(needs.get-changed-files.outputs.changed-files, '.hpp') ||
contains(needs.get-changed-files.outputs.changed-files, '.hxx') ||
contains(needs.get-changed-files.outputs.changed-files, '.cu') ||
contains(needs.get-changed-files.outputs.changed-files, '.cuh') ||
contains(needs.get-changed-files.outputs.changed-files, '.mm') ||
contains(needs.get-changed-files.outputs.changed-files, '.metal')
)
needs: get-label-type
with:
timeout: 120
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
@ -60,61 +40,25 @@ jobs:
submodules: true
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
script: |
CHANGED_FILES="${{ needs.get-changed-files.outputs.changed-files }}"
if [ "$CHANGED_FILES" = "*" ]; then
export ADDITIONAL_LINTRUNNER_ARGS="--take CLANGTIDY,CLANGFORMAT --all-files"
else
export ADDITIONAL_LINTRUNNER_ARGS="--take CLANGTIDY,CLANGFORMAT $CHANGED_FILES"
fi
export ADDITIONAL_LINTRUNNER_ARGS="--take CLANGTIDY,CLANGFORMAT --all-files"
export CLANG=1
.github/scripts/lintrunner.sh
# NOTE: mypy needs its own job because it depends on --all-files, without assessing all files it sometimes
# fails to find types when it should
lintrunner-mypy:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
needs: [get-label-type, get-changed-files]
# Only run if there are changed files relevant to mypy
if: |
github.repository_owner == 'pytorch' && (
needs.get-changed-files.outputs.changed-files == '*' ||
contains(needs.get-changed-files.outputs.changed-files, '.py') ||
contains(needs.get-changed-files.outputs.changed-files, '.pyi')
)
with:
timeout: 120
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
docker-image: ci-image:pytorch-linux-jammy-linter
# NB: A shallow checkout won't work here because calculate-docker-image requires a full checkout
# to run git rev-parse HEAD~:.ci/docker when a new image is needed
fetch-depth: 0
submodules: true
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
script: |
CHANGED_FILES="${{ needs.get-changed-files.outputs.changed-files }}"
echo "Running mypy"
ADDITIONAL_LINTRUNNER_ARGS="--take MYPY --all-files" .github/scripts/lintrunner.sh
lintrunner-noclang:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
needs: [get-label-type, get-changed-files]
needs: get-label-type
with:
timeout: 120
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
docker-image: ci-image:pytorch-linux-jammy-linter
docker-image: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter
# NB: A shallow checkout won't work here because calculate-docker-image requires a full checkout
# to run git rev-parse HEAD~:.ci/docker when a new image is needed
fetch-depth: 0
submodules: true
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
script: |
CHANGED_FILES="${{ needs.get-changed-files.outputs.changed-files }}"
echo "Running all other linters"
if [ "$CHANGED_FILES" = '*' ]; then
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY --all-files" .github/scripts/lintrunner.sh
else
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY ${CHANGED_FILES}" .github/scripts/lintrunner.sh
fi
export ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT --all-files"
.github/scripts/lintrunner.sh
quick-checks:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
@ -317,7 +261,6 @@ jobs:
check-latest: false
cache: pip
cache-dependency-path: |
**/requirements-build.txt
**/requirements.txt
- name: Setup Min Python version
if: matrix.test_type != 'older_python_version'
@ -328,7 +271,6 @@ jobs:
check-latest: false
cache: pip
cache-dependency-path: |
**/requirements-build.txt
**/requirements.txt
- name: Install torch
if: matrix.test_type == 'with_torch'

View File

@ -83,10 +83,6 @@ jobs:
repo-owner: triton-lang
branch: main
pin-folder: .ci/docker/ci_commit_pins
- repo-name: vllm
repo-owner: vllm-project
branch: main
pin-folder: .github/ci_commit_pins
# Allow this to be triggered on either a schedule or on workflow_dispatch to allow for easier testing
if: github.repository_owner == 'pytorch' && (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch')
steps:

View File

@ -51,67 +51,6 @@ jobs:
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-cuda12_4-py3_10-gcc11-sm89-build:
name: linux-jammy-cuda12.4-py3.10-gcc11-sm89
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-cuda12.4-py3.10-gcc11-sm89
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.4-cudnn9-py3-gcc11
cuda-arch-list: 8.9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu" },
]}
secrets: inherit
linux-jammy-cuda12_4-py3_10-gcc11-sm89-test:
name: linux-jammy-cuda12.4-py3.10-gcc11-sm89
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_4-py3_10-gcc11-sm89-build
- target-determination
with:
build-environment: linux-jammy-cuda12.4-py3.10-gcc11-sm89
docker-image: ${{ needs.linux-jammy-cuda12_4-py3_10-gcc11-sm89-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_4-py3_10-gcc11-sm89-build.outputs.test-matrix }}
secrets: inherit
linux-jammy-cuda12_4-py3_10-gcc11-build:
name: linux-jammy-cuda12.4-py3.10-gcc11
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-cuda12.4-py3.10-gcc11
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.4-cudnn9-py3-gcc11
test-matrix: |
{ include: [
{ config: "legacy_nvidia_driver", shard: 1, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "legacy_nvidia_driver", shard: 2, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "legacy_nvidia_driver", shard: 3, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "legacy_nvidia_driver", shard: 4, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "legacy_nvidia_driver", shard: 5, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
]}
secrets: inherit
linux-jammy-cuda12_4-py3_10-gcc11-test:
name: linux-jammy-cuda12.4-py3.10-gcc11
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_4-py3_10-gcc11-build
- target-determination
with:
build-environment: linux-jammy-cuda12.4-py3.10-gcc11
docker-image: ${{ needs.linux-jammy-cuda12_4-py3_10-gcc11-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_4-py3_10-gcc11-build.outputs.test-matrix }}
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc11-build:
name: linux-jammy-cuda12.8-py3.10-gcc11
uses: ./.github/workflows/_linux-build.yml
@ -157,6 +96,7 @@ jobs:
{ config: "multigpu", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.12xlarge.nvidia.gpu", owners: ["oncall:distributed"] },
{ config: "multigpu", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.12xlarge.nvidia.gpu", owners: ["oncall:distributed"] },
]}
build-with-debug: false
secrets: inherit
linux-jammy-cuda12_8-py3_9-gcc9-test:
@ -177,6 +117,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-debug
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9
build-with-debug: true
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },

View File

@ -315,6 +315,21 @@ jobs:
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-build.outputs.test-matrix }}
secrets: inherit
linux-jammy-py3-clang12-mobile-build:
name: linux-jammy-py3-clang12-mobile-build
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3-clang12-mobile-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-clang15-asan
build-generates-artifacts: false
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
]}
secrets: inherit
linux-jammy-cuda12_8-cudnn9-py3_9-clang12-build:
name: linux-jammy-cuda12.8-cudnn9-py3.9-clang12
uses: ./.github/workflows/_linux-build.yml

View File

@ -26,7 +26,7 @@ jobs:
architecture: x64
check-latest: false
cache: pip
- run: pip install pyyaml==6.0.2
- run: pip install pyyaml==6.0
- name: Setup committer id
run: |

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