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Author SHA1 Message Date
3e099a62b0 update config 2024-06-10 16:35:55 -07:00
2743 changed files with 72261 additions and 102137 deletions

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@ -1,5 +1,5 @@
0.6b
manylinux_2_17
rocm6.1
7f07e8a1cb1f99627eb6d77f5c0e9295c775f3c7
77c29fa3f3b614e187d7213d745e989a92708cee2bc6020419ab49019af399d1
rocm6
04b5df8c8123f90cba3ede7e971e6fbc6040d506
3db6ecbc915893ff967abd6e1b43bd5f54949868873be60dc802086c3863e648

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@ -373,13 +373,6 @@ case "$image" in
CONDA_CMAKE=yes
EXECUTORCH=yes
;;
pytorch-linux-jammy-py3.12-halide)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
HALIDE=yes
;;
pytorch-linux-focal-linter)
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
# We will need to update mypy version eventually, but that's for another day. The task
@ -497,7 +490,6 @@ docker build \
--build-arg "DOCS=${DOCS}" \
--build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "HALIDE=${HALIDE}" \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \

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@ -1 +1 @@
c572f9e509b5ec5d56f4d218271e36269bba244f
d4b3e5cc607e97afdba79dc90f8ef968142f347c

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@ -1 +0,0 @@
340136fec6d3ebc73e7a19eba1663e9b0ba8ab2d

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@ -1 +1 @@
21eae954efa5bf584da70324b640288c3ee7aede
01cbe5045a6898c9a925f01435c8277b2fe6afcc

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@ -1 +1 @@
1b2f15840e0d70eec50d84c7a0575cb835524def
b8c64f64c18d8cac598b3adb355c21e7439c21de

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@ -1 +1 @@
dedb7bdf339a3546896d4820366ca562c586bfa0
45fff310c891f5a92d55445adf8cc9d29df5841e

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@ -9,7 +9,7 @@ TARBALL='aotriton.tar.bz2'
read -d "\n" VER MANYLINUX ROCMBASE PINNED_COMMIT SHA256 < aotriton_version.txt || true
ARCH=$(uname -m)
AOTRITON_INSTALL_PREFIX="$1"
AOTRITON_URL="https://github.com/ROCm/aotriton/releases/download/${VER}/aotriton-${VER}-${MANYLINUX}_${ARCH}-${ROCMBASE}-shared.tar.bz2"
AOTRITON_URL="https://github.com/ROCm/aotriton/releases/download/${VER}/aotriton-${VER}-${MANYLINUX}_${ARCH}-${ROCMBASE}.tar.bz2"
cd "${AOTRITON_INSTALL_PREFIX}"
# Must use -L to follow redirects

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@ -85,7 +85,7 @@ fi
else
CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.12" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.13" ]; then
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.12" ]; then
conda_install numpy=1.26.0 ${CONDA_COMMON_DEPS}
else
conda_install numpy=1.21.2 ${CONDA_COMMON_DEPS}

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@ -37,9 +37,6 @@ install_conda_dependencies() {
install_pip_dependencies() {
pushd executorch/.ci/docker
# Install PyTorch CPU build beforehand to avoid installing the much bigger CUDA
# binaries later, ExecuTorch only needs CPU
pip_install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
# Install all Python dependencies
pip_install -r requirements-ci.txt
popd
@ -47,14 +44,13 @@ install_pip_dependencies() {
setup_executorch() {
pushd executorch
# Setup swiftshader and Vulkan SDK which are required to build the Vulkan delegate
as_jenkins bash .ci/scripts/setup-vulkan-linux-deps.sh
source .ci/scripts/utils.sh
export PYTHON_EXECUTABLE=python
export EXECUTORCH_BUILD_PYBIND=ON
export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
install_flatc_from_source
pip_install .
as_jenkins .ci/scripts/setup-linux.sh cmake
# Make sure that all the newly generate files are owned by Jenkins
chown -R jenkins .
popd
}

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@ -1,46 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
COMMIT=$(get_pinned_commit halide)
test -n "$COMMIT"
# activate conda to populate CONDA_PREFIX
test -n "$ANACONDA_PYTHON_VERSION"
eval "$(conda shell.bash hook)"
conda activate py_$ANACONDA_PYTHON_VERSION
if [ -n "${UBUNTU_VERSION}" ];then
apt update
apt-get install -y lld liblld-15-dev libpng-dev libjpeg-dev libgl-dev \
libopenblas-dev libeigen3-dev libatlas-base-dev libzstd-dev
fi
conda_install numpy scipy imageio cmake ninja
git clone --depth 1 --branch release/16.x --recursive https://github.com/llvm/llvm-project.git
cmake -DCMAKE_BUILD_TYPE=Release \
-DLLVM_ENABLE_PROJECTS="clang" \
-DLLVM_TARGETS_TO_BUILD="X86;NVPTX" \
-DLLVM_ENABLE_TERMINFO=OFF -DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_EH=ON -DLLVM_ENABLE_RTTI=ON -DLLVM_BUILD_32_BITS=OFF \
-S llvm-project/llvm -B llvm-build -G Ninja
cmake --build llvm-build
cmake --install llvm-build --prefix llvm-install
export LLVM_ROOT=`pwd`/llvm-install
export LLVM_CONFIG=$LLVM_ROOT/bin/llvm-config
git clone https://github.com/halide/Halide.git
pushd Halide
git checkout ${COMMIT} && git submodule update --init --recursive
pip_install -r requirements.txt
cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -S . -B build
cmake --build build
test -e ${CONDA_PREFIX}/lib/python3 || ln -s python${ANACONDA_PYTHON_VERSION} ${CONDA_PREFIX}/lib/python3
cmake --install build --prefix ${CONDA_PREFIX}
chown -R jenkins ${CONDA_PREFIX}
popd
rm -rf Halide llvm-build llvm-project llvm-install
python -c "import halide" # check for errors

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@ -33,9 +33,7 @@ pip_install coloredlogs packaging
pip_install onnxruntime==1.18
pip_install onnx==1.16.0
# pip_install "onnxscript@git+https://github.com/microsoft/onnxscript@3e869ef8ccf19b5ebd21c10d3e9c267c9a9fa729" --no-deps
pip_install onnxscript==0.1.0.dev20240613 --no-deps
# required by onnxscript
pip_install ml_dtypes
pip_install onnxscript==0.1.0.dev20240523 --no-deps
# Cache the transformers model to be used later by ONNX tests. We need to run the transformers
# package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/

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@ -85,10 +85,10 @@ librosa>=0.6.2 ; python_version < "3.11"
#Pinned versions:
#test that import:
mypy==1.10.0
mypy==1.9.0
# Pin MyPy version because new errors are likely to appear with each release
#Description: linter
#Pinned versions: 1.10.0
#Pinned versions: 1.9.0
#test that import: test_typing.py, test_type_hints.py
networkx==2.8.8
@ -306,7 +306,7 @@ pywavelets==1.5.0 ; python_version >= "3.12"
#Pinned versions: 1.4.1
#test that import:
lxml==5.0.0
lxml==5.0.0.
#Description: This is a requirement of unittest-xml-reporting
# Python-3.9 binaries

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@ -103,14 +103,6 @@ COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH

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@ -155,14 +155,6 @@ COPY ci_commit_pins/executorch.txt executorch.txt
RUN if [ -n "${EXECUTORCH}" ]; then bash ./install_executorch.sh; fi
RUN rm install_executorch.sh common_utils.sh executorch.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
ARG ONNX
# Install ONNX dependencies
COPY ./common/install_onnx.sh ./common/common_utils.sh ./

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@ -230,10 +230,6 @@ if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* ]]
export BUILD_STATIC_RUNTIME_BENCHMARK=ON
fi
if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
export CMAKE_BUILD_TYPE=RelWithAssert
fi
# Do not change workspace permissions for ROCm CI jobs
# as it can leave workspace with bad permissions for cancelled jobs
if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
@ -288,26 +284,12 @@ else
# Which should be backward compatible with Numpy-1.X
python -mpip install --pre numpy==2.0.0rc1
fi
WERROR=1 python setup.py clean
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
BUILD_LIBTORCH_WHL=1 BUILD_PYTHON_ONLY=0 python setup.py bdist_wheel
BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 python setup.py bdist_wheel --cmake
else
WERROR=1 python setup.py bdist_wheel
fi
WERROR=1 python setup.py bdist_wheel
else
python setup.py clean
if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
source .ci/pytorch/install_cache_xla.sh
fi
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
echo "USE_SPLIT_BUILD cannot be used with xla or rocm"
exit 1
else
python setup.py bdist_wheel
fi
python setup.py bdist_wheel
fi
pip_install_whl "$(echo dist/*.whl)"
@ -346,10 +328,9 @@ else
CUSTOM_OP_TEST="$PWD/test/custom_operator"
python --version
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$CUSTOM_OP_BUILD"
pushd "$CUSTOM_OP_BUILD"
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -362,7 +343,7 @@ else
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$JIT_HOOK_BUILD"
pushd "$JIT_HOOK_BUILD"
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -374,7 +355,7 @@ else
python --version
mkdir -p "$CUSTOM_BACKEND_BUILD"
pushd "$CUSTOM_BACKEND_BUILD"
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd

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@ -56,29 +56,9 @@ function assert_git_not_dirty() {
function pip_install_whl() {
# This is used to install PyTorch and other build artifacts wheel locally
# without using any network connection
# Convert the input arguments into an array
local args=("$@")
# Check if the first argument contains multiple paths separated by spaces
if [[ "${args[0]}" == *" "* ]]; then
# Split the string by spaces into an array
IFS=' ' read -r -a paths <<< "${args[0]}"
# Loop through each path and install individually
for path in "${paths[@]}"; do
echo "Installing $path"
python3 -mpip install --no-index --no-deps "$path"
done
else
# Loop through each argument and install individually
for path in "${args[@]}"; do
echo "Installing $path"
python3 -mpip install --no-index --no-deps "$path"
done
fi
python3 -mpip install --no-index --no-deps "$@"
}
function pip_install() {
# retry 3 times
# old versions of pip don't have the "--progress-bar" flag
@ -208,6 +188,28 @@ function clone_pytorch_xla() {
fi
}
function checkout_install_torchdeploy() {
local commit
commit=$(get_pinned_commit multipy)
pushd ..
git clone --recurse-submodules https://github.com/pytorch/multipy.git
pushd multipy
git checkout "${commit}"
python multipy/runtime/example/generate_examples.py
BUILD_CUDA_TESTS=1 pip install -e .
popd
popd
}
function test_torch_deploy(){
pushd ..
pushd multipy
./multipy/runtime/build/test_deploy
./multipy/runtime/build/test_deploy_gpu
popd
popd
}
function checkout_install_torchbench() {
local commit
commit=$(get_pinned_commit torchbench)
@ -222,8 +224,6 @@ function checkout_install_torchbench() {
# to install and test other models
python install.py --continue_on_fail
fi
echo "Print all dependencies after TorchBench is installed"
python -mpip freeze
popd
}

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@ -18,9 +18,8 @@ time python test/run_test.py --verbose -i distributed/test_c10d_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_nccl
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
time python test/run_test.py --verbose -i distributed/test_cuda_p2p
time python test/run_test.py --verbose -i distributed/test_store
time python test/run_test.py --verbose -i distributed/test_symmetric_memory
time python test/run_test.py --verbose -i distributed/test_pg_wrapper
time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
# FSDP tests

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@ -249,7 +249,9 @@ fi
# This tests that the debug asserts are working correctly.
if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
echo "We are in debug mode: $BUILD_ENVIRONMENT. Expect the python assertion to fail"
(cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
# TODO: Enable the check after we setup the build to run debug asserts without having
# to do a full (and slow) debug build
# (cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
elif [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
# Noop when debug is disabled. Skip bazel jobs because torch isn't available there yet.
echo "We are not in debug mode: $BUILD_ENVIRONMENT. Expect the assertion to pass"
@ -262,6 +264,18 @@ elif [[ $TEST_CONFIG == 'nogpu_AVX512' ]]; then
export ATEN_CPU_CAPABILITY=avx2
fi
# temp workarounds for https://github.com/pytorch/pytorch/issues/126692, remove when fixed
if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
pushd test
CUDA_VERSION=$(python -c "import torch; print(torch.version.cuda)")
if [ "$CUDA_VERSION" == "12.4" ]; then
ISCUDA124="cu124"
else
ISCUDA124=""
fi
popd
fi
test_python_legacy_jit() {
time python test/run_test.py --include test_jit_legacy test_jit_fuser_legacy --verbose
assert_git_not_dirty
@ -275,9 +289,6 @@ test_python_shard() {
# Bare --include flag is not supported and quoting for lint ends up with flag not being interpreted correctly
# shellcheck disable=SC2086
# modify LD_LIBRARY_PATH to ensure it has the conda env.
# This set of tests has been shown to be buggy without it for the split-build
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION
assert_git_not_dirty
@ -336,31 +347,17 @@ test_inductor_distributed() {
assert_git_not_dirty
}
test_inductor_shard() {
if [[ -z "$NUM_TEST_SHARDS" ]]; then
echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
exit 1
fi
test_inductor() {
python tools/dynamo/verify_dynamo.py
python test/run_test.py --inductor \
--include test_modules test_ops test_ops_gradients test_torch \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
python test/run_test.py --inductor --include test_modules test_ops test_ops_gradients test_torch --verbose
# Do not add --inductor for the following inductor unit tests, otherwise we will fail because of nested dynamo state
python test/run_test.py \
--include inductor/test_torchinductor inductor/test_torchinductor_opinfo inductor/test_aot_inductor \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
}
python test/run_test.py --include inductor/test_torchinductor inductor/test_torchinductor_opinfo inductor/test_aot_inductor --verbose
test_inductor_aoti() {
# docker build uses bdist_wheel which does not work with test_aot_inductor
# TODO: need a faster way to build
if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
fi
}
@ -379,7 +376,7 @@ test_inductor_cpp_wrapper_abi_compatible() {
--output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_timm_training.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_timm_training.csv"
}
# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@ -404,7 +401,7 @@ if [[ "${TEST_CONFIG}" == *dynamic* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--dynamic-shapes --dynamic-batch-only)
fi
if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
else
DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
@ -529,10 +526,9 @@ test_single_dynamo_benchmark() {
test_perf_for_dashboard "$suite" \
"${DYNAMO_BENCHMARK_FLAGS[@]}" "$@" "${partition_flags[@]}"
else
if [[ "${TEST_CONFIG}" == *aot_inductor* && "${TEST_CONFIG}" != *cpu_aot_inductor* ]]; then
if [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
# Test AOTInductor with the ABI-compatible mode on CI
# This can be removed once the ABI-compatible mode becomes default.
# For CPU device, we perfer non ABI-compatible mode on CI when testing AOTInductor.
export TORCHINDUCTOR_ABI_COMPATIBLE=1
fi
python "benchmarks/dynamo/$suite.py" \
@ -542,10 +538,10 @@ test_single_dynamo_benchmark() {
--output "$TEST_REPORTS_DIR/${name}_${suite}.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/${TEST_CONFIG}_${name}.csv"
python benchmarks/dynamo/check_graph_breaks.py \
--actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/${TEST_CONFIG}_${name}.csv"
fi
}
@ -554,11 +550,6 @@ test_inductor_micro_benchmark() {
python benchmarks/gpt_fast/benchmark.py --output "${TEST_REPORTS_DIR}/gpt_fast_benchmark.csv"
}
test_inductor_halide() {
python test/run_test.py --include inductor/test_halide.py --verbose
assert_git_not_dirty
}
test_dynamo_benchmark() {
# Usage: test_dynamo_benchmark huggingface 0
TEST_REPORTS_DIR=$(pwd)/test/test-reports
@ -573,15 +564,11 @@ test_dynamo_benchmark() {
elif [[ "${TEST_CONFIG}" == *perf* ]]; then
test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
else
if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
local dt="float32"
if [[ "${TEST_CONFIG}" == *amp* ]]; then
dt="amp"
fi
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
if [[ "${TEST_CONFIG}" == *freezing* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" --freezing "$@"
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 --freezing "$@"
else
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" "$@"
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 "$@"
fi
elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
@ -605,7 +592,7 @@ test_inductor_torchbench_smoketest_perf() {
--bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_torchbench_inference.csv"
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
@ -620,8 +607,13 @@ test_inductor_torchbench_smoketest_perf() {
# https://github.com/pytorch/pytorch/actions/runs/7158691360/job/19491437314,
# and thus we lower its threshold to reduce flakiness. If this continues to be a problem,
# we switch to use some other model.
# lowering threshold from 4.9 to 4.7 for cu124. Will bump it up after cuda 12.4.0->12.4.1 update
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 4.7
# Use 4.7 for cuda 12.4, change back to 4.9 after fixing https://github.com/pytorch/pytorch/issues/126692
if [ "$CUDA_VERSION" == "12.4" ]; then
THRESHOLD=4.7
else
THRESHOLD=4.9
fi
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t $THRESHOLD
# Check memory compression ratio for a few models
for test in hf_Albert timm_vision_transformer; do
@ -640,7 +632,7 @@ test_inductor_torchbench_smoketest_perf() {
--only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_huggingface_training.csv"
done
}
@ -1177,21 +1169,15 @@ test_executorch() {
pushd /executorch
export PYTHON_EXECUTABLE=python
export EXECUTORCH_BUILD_PYBIND=ON
export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
# NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
# from the PR
# NB: We need to build ExecuTorch runner here and not inside the Docker image
# because it depends on PyTorch
# shellcheck disable=SC1091
source .ci/scripts/setup-linux.sh cmake
echo "Run ExecuTorch unit tests"
pytest -v -n auto
# shellcheck disable=SC1091
LLVM_PROFDATA=llvm-profdata-12 LLVM_COV=llvm-cov-12 bash test/run_oss_cpp_tests.sh
source .ci/scripts/utils.sh
build_executorch_runner "cmake"
echo "Run ExecuTorch regression tests for some models"
# NB: This is a sample model, more can be added here
export PYTHON_EXECUTABLE=python
# TODO(huydhn): Add more coverage here using ExecuTorch's gather models script
# shellcheck disable=SC1091
source .ci/scripts/test.sh mv3 cmake xnnpack-quantization-delegation ''
@ -1251,10 +1237,11 @@ elif [[ "$TEST_CONFIG" == distributed ]]; then
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_rpc
fi
elif [[ "$TEST_CONFIG" == deploy ]]; then
checkout_install_torchdeploy
test_torch_deploy
elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
test_inductor_halide
elif [[ "${TEST_CONFIG}" == *inductor-micro-benchmark* ]]; then
test_inductor_micro_benchmark
elif [[ "${TEST_CONFIG}" == *huggingface* ]]; then
@ -1266,14 +1253,13 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
id=$((SHARD_NUMBER-1))
test_dynamo_benchmark timm_models "$id"
elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
install_torchaudio cpu
else
install_torchaudio cuda
fi
install_torchtext
install_torchvision
TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install git+https://github.com/pytorch/ao.git
id=$((SHARD_NUMBER-1))
# https://github.com/opencv/opencv-python/issues/885
pip_install opencv-python==4.8.0.74
@ -1292,7 +1278,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
checkout_install_torchbench
# Do this after checkout_install_torchbench to ensure we clobber any
# nightlies that torchbench may pull in
if [[ "${TEST_CONFIG}" != *cpu_inductor* && "${TEST_CONFIG}" != *cpu_aot_inductor* ]]; then
if [[ "${TEST_CONFIG}" != *cpu_inductor* ]]; then
install_torchrec_and_fbgemm
fi
PYTHONPATH=$(pwd)/torchbench test_dynamo_benchmark torchbench "$id"
@ -1300,19 +1286,17 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper_abi_compatible* ]]; then
install_torchvision
test_inductor_cpp_wrapper_abi_compatible
elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
elif [[ "${TEST_CONFIG}" == *inductor* && "${SHARD_NUMBER}" == 1 ]]; then
install_torchvision
test_inductor_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_inductor_aoti
test_inductor_distributed
fi
elif [[ "${TEST_CONFIG}" == *dynamo* ]]; then
test_inductor
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_dynamo_shard 1
test_aten
elif [[ "${TEST_CONFIG}" == *dynamo* && $SHARD_NUMBER -gt 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_dynamo_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_aten
fi
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python_shard "$SHARD_NUMBER"

View File

@ -97,16 +97,8 @@ if [[ "$PACKAGE_TYPE" == conda ]]; then
)
elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
if [[ "\$BUILD_ENVIRONMENT" != *s390x* ]]; then
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
pkg_no_python="$(ls -1 /final_pkgs/torch_no_python* | sort |tail -1)"
pkg_torch="$(ls -1 /final_pkgs/torch-* | sort |tail -1)"
# todo: after folder is populated use the pypi_pkg channel instead
pip install "\$pkg_no_python" "\$pkg_torch" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}_pypi_pkg"
retry pip install -q numpy protobuf typing-extensions
else
pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
retry pip install -q numpy protobuf typing-extensions
fi
pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
retry pip install -q numpy protobuf typing-extensions
else
pip install "\$pkg"
retry pip install -q numpy protobuf typing-extensions
@ -118,12 +110,6 @@ if [[ "$PACKAGE_TYPE" == libtorch ]]; then
cd /tmp/libtorch
fi
if [[ "$GPU_ARCH_TYPE" == xpu ]]; then
# Workaround for __mkl_tmp_MOD unbound variable issue, refer https://github.com/pytorch/pytorch/issues/130543
set +u
source /opt/intel/oneapi/pytorch-gpu-dev-0.5/oneapi-vars.sh
fi
# Test the package
/builder/check_binary.sh

View File

@ -33,9 +33,9 @@ if [[ -z "$DOCKER_IMAGE" ]]; then
if [[ "$PACKAGE_TYPE" == conda ]]; then
export DOCKER_IMAGE="pytorch/conda-cuda"
elif [[ "$DESIRED_CUDA" == cpu ]]; then
export DOCKER_IMAGE="pytorch/manylinux:cpu"
export DOCKER_IMAGE="pytorch/manylinux-cpu"
else
export DOCKER_IMAGE="pytorch/manylinux-builder:${DESIRED_CUDA:2}"
export DOCKER_IMAGE="pytorch/manylinux-cuda${DESIRED_CUDA:2}"
fi
fi
@ -75,9 +75,9 @@ export PYTORCH_BUILD_NUMBER=1
TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64' and python_version < '3.13'"
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
# Only linux Python < 3.13 are supported wheels for triton
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64' and python_version < '3.13'"
TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton.txt)
@ -87,11 +87,11 @@ if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:
fi
# Set triton via PYTORCH_EXTRA_INSTALL_REQUIREMENTS for triton rocm package
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*rocm.* && $(uname) == "Linux" ]]; then
TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*rocm.* && $(uname) == "Linux" && "$DESIRED_PYTHON" != "3.12" ]]; then
TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}"
if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-rocm.txt)
TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}+${TRITON_SHORTHASH}; ${TRITON_CONSTRAINT}"
TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}+${TRITON_SHORTHASH}"
fi
if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"
@ -100,18 +100,30 @@ if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_B
fi
fi
# Set triton via PYTORCH_EXTRA_INSTALL_REQUIREMENTS for triton xpu package
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* && $(uname) == "Linux" ]]; then
TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}"
if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-xpu.txt)
TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+${TRITON_SHORTHASH}"
fi
if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"
else
export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${PYTORCH_EXTRA_INSTALL_REQUIREMENTS} | ${TRITON_REQUIREMENT}"
JAVA_HOME=
BUILD_JNI=OFF
if [[ "$PACKAGE_TYPE" == libtorch ]]; then
POSSIBLE_JAVA_HOMES=()
POSSIBLE_JAVA_HOMES+=(/usr/local)
POSSIBLE_JAVA_HOMES+=(/usr/lib/jvm/java-8-openjdk-amd64)
POSSIBLE_JAVA_HOMES+=(/Library/Java/JavaVirtualMachines/*.jdk/Contents/Home)
# Add the Windows-specific JNI path
POSSIBLE_JAVA_HOMES+=("$PWD/pytorch/.circleci/windows-jni/")
for JH in "${POSSIBLE_JAVA_HOMES[@]}" ; do
if [[ -e "$JH/include/jni.h" ]] ; then
# Skip if we're not on Windows but haven't found a JAVA_HOME
if [[ "$JH" == "$PWD/pytorch/.circleci/windows-jni/" && "$OSTYPE" != "msys" ]] ; then
break
fi
echo "Found jni.h under $JH"
JAVA_HOME="$JH"
BUILD_JNI=ON
break
fi
done
if [ -z "$JAVA_HOME" ]; then
echo "Did not find jni.h"
fi
fi
cat >"$envfile" <<EOL
@ -124,7 +136,6 @@ export DESIRED_PYTHON="${DESIRED_PYTHON:-}"
export DESIRED_CUDA="$DESIRED_CUDA"
export LIBTORCH_VARIANT="${LIBTORCH_VARIANT:-}"
export BUILD_PYTHONLESS="${BUILD_PYTHONLESS:-}"
export USE_SPLIT_BUILD="${USE_SPLIT_BUILD:-}"
if [[ "${OSTYPE}" == "msys" ]]; then
export LIBTORCH_CONFIG="${LIBTORCH_CONFIG:-}"
if [[ "${LIBTORCH_CONFIG:-}" == 'debug' ]]; then
@ -148,6 +159,8 @@ export TORCH_CONDA_BUILD_FOLDER='pytorch-nightly'
export ANACONDA_USER='pytorch'
export USE_FBGEMM=1
export JAVA_HOME=$JAVA_HOME
export BUILD_JNI=$BUILD_JNI
export PIP_UPLOAD_FOLDER="$PIP_UPLOAD_FOLDER"
export DOCKER_IMAGE="$DOCKER_IMAGE"

View File

@ -25,15 +25,6 @@ if [[ "${DRY_RUN}" = "disabled" ]]; then
AWS_S3_CP="aws s3 cp"
fi
if [[ "${USE_SPLIT_BUILD:-false}" == "true" ]]; then
UPLOAD_SUBFOLDER="${UPLOAD_SUBFOLDER}_pypi_pkg"
fi
# this is special build with all dependencies packaged
if [[ ${BUILD_NAME} == *-full* ]]; then
UPLOAD_SUBFOLDER="${UPLOAD_SUBFOLDER}_full"
fi
# Sleep 2 minutes between retries for conda upload
retry () {
"$@" || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@")

View File

@ -62,6 +62,4 @@ readability-string-compare,
'
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
WarningsAsErrors: '*'
CheckOptions:
misc-header-include-cycle.IgnoredFilesList: 'format.h;ivalue.h;custom_class.h;Dict.h;List.h'
...

View File

@ -40,7 +40,3 @@ e6ec0efaf87703c5f889cfc20b29be455885d58d
a53cda1ddc15336dc1ff0ce1eff2a49cdc5f882e
# 2024-01-02 clangformat: fused adam #116583
9dc68d1aa9e554d09344a10fff69f7b50b2d23a0
# 2024-06-28 enable UFMT in `torch/storage.py`
d80939e5e9337e8078f11489afefec59fd42f93b
# 2024-06-28 enable UFMT in `torch.utils.data`
7cf0b90e49689d45be91aa539fdf54cf2ea8a9a3

View File

@ -47,5 +47,3 @@ self-hosted-runner:
- macos-latest-xlarge
- macos-13-xlarge
- macos-14-xlarge
# Organization-wide Intel hosted XPU runners
- linux.idc.xpu

View File

@ -14,14 +14,12 @@ runs:
- name: Cleans up diskspace
shell: bash
run: |
set -ex
diskspace_cutoff=${{ inputs.diskspace-cutoff }}
docker_root_dir=$(docker info -f '{{.DockerRootDir}}')
diskspace=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //')
diskspace=$(df -H / --output=pcent | sed -n 2p | sed 's/%//' | sed 's/ //')
msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified"
if [[ "$diskspace" -ge "$diskspace_cutoff" ]] ; then
docker system prune -af
diskspace_new=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //')
diskspace_new=$(df -H / --output=pcent | sed -n 2p | sed 's/%//' | sed 's/ //')
if [[ "$diskspace_new" -gt "$diskspace_cutoff" ]] ; then
echo "Error: Available diskspace is less than $diskspace_cutoff percent. Not enough diskspace."
echo "$msg"

View File

@ -52,13 +52,6 @@ inputs:
description: Hugging Face Hub token
required: false
default: ""
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
outputs:
docker-image:
value: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -151,7 +144,6 @@ runs:
DEBUG: ${{ inputs.build-with-debug == 'true' && '1' || '0' }}
OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
HUGGING_FACE_HUB_TOKEN: ${{ inputs.HUGGING_FACE_HUB_TOKEN }}
USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
shell: bash
run: |
# detached container should get cleaned up by teardown_ec2_linux
@ -171,7 +163,6 @@ runs:
-e PR_LABELS \
-e OUR_GITHUB_JOB_ID \
-e HUGGING_FACE_HUB_TOKEN \
-e USE_SPLIT_BUILD \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
@ -192,7 +183,7 @@ runs:
- name: Store PyTorch Build Artifacts on S3
uses: seemethere/upload-artifact-s3@v5
if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped' && inputs.use_split_build != 'true'
if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped'
with:
name: ${{ inputs.build-environment }}
retention-days: 14
@ -200,16 +191,6 @@ runs:
path: artifacts.zip
s3-bucket: ${{ inputs.s3-bucket }}
- name: Store PyTorch Build Artifacts on S3 for split build
uses: seemethere/upload-artifact-s3@v5
if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped' && inputs.use_split_build == 'true'
with:
name: ${{ inputs.build-environment }}-experimental-split-build
retention-days: 14
if-no-files-found: error
path: artifacts.zip
s3-bucket: ${{ inputs.s3-bucket }}
- name: Upload sccache stats
if: steps.build.outcome != 'skipped'
uses: seemethere/upload-artifact-s3@v5

View File

@ -26,7 +26,6 @@ runs:
-e PYTORCH_FINAL_PACKAGE_DIR \
-e PYTORCH_ROOT \
-e SKIP_ALL_TESTS \
-e USE_SPLIT_BUILD \
--tty \
--detach \
-v "${GITHUB_WORKSPACE}/pytorch:/pytorch" \
@ -36,8 +35,7 @@ runs:
"${DOCKER_IMAGE}"
)
echo "CONTAINER_NAME=${container_name}" >> "$GITHUB_ENV"
if [[ "${GPU_ARCH_TYPE}" != "rocm" && "${BUILD_ENVIRONMENT}" != "linux-aarch64-binary-manywheel" && "${BUILD_ENVIRONMENT}" != "linux-s390x-binary-manywheel" && "${GPU_ARCH_TYPE}" != "xpu" ]]; then
if [[ "${GPU_ARCH_TYPE}" != "rocm" && "${BUILD_ENVIRONMENT}" != "linux-aarch64-binary-manywheel" && "${BUILD_ENVIRONMENT}" != "linux-s390x-binary-manywheel" ]]; then
# Propagate download.pytorch.org IP to container. This is only needed on Linux non aarch64 runner
grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" bash -c "/bin/cat >> /etc/hosts"
fi
@ -48,9 +46,10 @@ runs:
docker exec -t "${container_name}" bash -c "source ${BINARY_ENV_FILE} && bash -x /run.sh"
- name: Cleanup docker
if: always() && (env.BUILD_ENVIRONMENT == 'linux-s390x-binary-manywheel' || env.GPU_ARCH_TYPE == 'xpu')
if: always() && env.BUILD_ENVIRONMENT == 'linux-s390x-binary-manywheel'
shell: bash
run: |
# on s390x or xpu stop the container for clean worker stop
# on s390x stop the container for clean worker stop
# ignore expansion of "docker ps -q" since it could be empty
# shellcheck disable=SC2046
docker stop "${{ env.CONTAINER_NAME }}" || true
docker stop $(docker ps -q) || true

View File

@ -1 +1 @@
69b2a0adc2ec03ab99990d7e8be3d4510438c148
b829e936f7cc61b48149f5f957a451a38bf2a178

View File

@ -1 +1 @@
23512dbebd44a11eb84afbf53c3c071dd105297e
d6015d42d9a1834bc7595c4bd6852562fb80b30b

View File

@ -27,9 +27,11 @@
- third_party/onnx
- caffe2/python/onnx/**
approved_by:
- BowenBao
- justinchuby
- liqunfu
- shubhambhokare1
- thiagocrepaldi
- titaiwangms
- wschin
- xadupre
@ -242,7 +244,6 @@
- torch/csrc/xpu/**
- torch/xpu/**
- test/xpu/**
- test/test_xpu.py
- third_party/xpu.txt
- .ci/docker/ci_commit_pins/triton-xpu.txt
approved_by:
@ -286,7 +287,6 @@
- test/cpp/dist_autograd/**
- test/cpp/rpc/**
approved_by:
- wconstab
- mrshenli
- pritamdamania87
- zhaojuanmao
@ -313,25 +313,6 @@
- Lint
- pull
- name: DCP
patterns:
- torch/distributed/checkpoint/**
approved_by:
- LucasLLC
- fegin
- wz337
- saumishr
- daulet-askarov
- pradeepdfb
- kirtiteja
- mhorowitz
- saiteja64
mandatory_checks_name:
- EasyCLA
- Lint
- pull
- name: IDEEP
patterns:
- third_party/ideep
@ -395,21 +376,13 @@
- name: CPU inductor
patterns:
- torch/_inductor/mkldnn_ir.py
- torch/_inductor/mkldnn_lowerings.py
- torch/_inductor/fx_passes/mkldnn_fusion.py
- torch/_inductor/fx_passes/quantization.py
- torch/_inductor/codegen/cpp_prefix.h
- torch/_inductor/codegen/cpp.py
- torch/_inductor/codegen/cpp_utils.py
- torch/_inductor/codegen/cpp_micro_gemm.py
- torch/_inductor/codegen/cpp_template_kernel.py
- torch/_inductor/codegen/cpp_template.py
- torch/_inductor/codegen/cpp_gemm_template.py
- test/inductor/test_mkldnn_pattern_matcher.py
- test/inductor/test_cpu_repro.py
- test/inductor/test_cpu_repo.py
- test/inductor/test_cpu_cpp_wrapper.py
- test/inductor/test_cpu_select_algorithm.py
- aten/src/ATen/cpu/**
- aten/src/ATen/native/quantized/cpu/**
- test/quantization/core/test_quantized_op.py

View File

@ -26,4 +26,3 @@ retryable_workflows:
- windows-binary
labeler_config: labeler.yml
label_to_label_config: label_to_label.yml
mergebot: True

View File

@ -93,8 +93,6 @@ done
# Copy Include Files
cp -r $ROCM_HOME/include/hip $TRITON_ROCM_DIR/include
cp -r $ROCM_HOME/include/roctracer $TRITON_ROCM_DIR/include
cp -r $ROCM_HOME/include/hsa $TRITON_ROCM_DIR/include
# Copy linker
mkdir -p $TRITON_ROCM_DIR/llvm/bin

View File

@ -11,12 +11,8 @@ SCRIPT_DIR = Path(__file__).parent
REPO_DIR = SCRIPT_DIR.parent.parent
def read_triton_pin(device: str = "cuda") -> str:
triton_file = "triton.txt"
if device == "rocm":
triton_file = "triton-rocm.txt"
elif device == "xpu":
triton_file = "triton-xpu.txt"
def read_triton_pin(rocm_hash: bool = False) -> str:
triton_file = "triton.txt" if not rocm_hash else "triton-rocm.txt"
with open(REPO_DIR / ".ci" / "docker" / "ci_commit_pins" / triton_file) as f:
return f.read().strip()
@ -53,7 +49,7 @@ def build_triton(
version: str,
commit_hash: str,
build_conda: bool = False,
device: str = "cuda",
build_rocm: bool = False,
py_version: Optional[str] = None,
release: bool = False,
) -> Path:
@ -73,14 +69,11 @@ def build_triton(
triton_basedir = Path(tmpdir) / "triton"
triton_pythondir = triton_basedir / "python"
triton_repo = "https://github.com/openai/triton"
if device == "rocm":
if build_rocm:
triton_pkg_name = "pytorch-triton-rocm"
elif device == "xpu":
triton_pkg_name = "pytorch-triton-xpu"
triton_repo = "https://github.com/intel/intel-xpu-backend-for-triton"
else:
triton_pkg_name = "pytorch-triton"
check_call(["git", "clone", triton_repo, "triton"], cwd=tmpdir)
check_call(["git", "clone", triton_repo], cwd=tmpdir)
if release:
ver, rev, patch = version.split(".")
check_call(
@ -147,7 +140,7 @@ def build_triton(
expected_version=None,
)
if device == "rocm":
if build_rocm:
check_call(
[f"{SCRIPT_DIR}/amd/package_triton_wheel.sh"],
cwd=triton_basedir,
@ -162,7 +155,7 @@ def build_triton(
whl_path = next(iter((triton_pythondir / "dist").glob("*.whl")))
shutil.copy(whl_path, Path.cwd())
if device == "rocm":
if build_rocm:
check_call(
[f"{SCRIPT_DIR}/amd/patch_triton_wheel.sh", Path.cwd()],
cwd=triton_basedir,
@ -177,19 +170,17 @@ def main() -> None:
parser = ArgumentParser("Build Triton binaries")
parser.add_argument("--release", action="store_true")
parser.add_argument("--build-conda", action="store_true")
parser.add_argument(
"--device", type=str, default="cuda", choices=["cuda", "rocm", "xpu"]
)
parser.add_argument("--build-rocm", action="store_true")
parser.add_argument("--py-version", type=str)
parser.add_argument("--commit-hash", type=str)
parser.add_argument("--triton-version", type=str, default=read_triton_version())
args = parser.parse_args()
build_triton(
device=args.device,
build_rocm=args.build_rocm,
commit_hash=args.commit_hash
if args.commit_hash
else read_triton_pin(args.device),
else read_triton_pin(args.build_rocm),
version=args.triton_version,
build_conda=args.build_conda,
py_version=args.py_version,

View File

@ -3,11 +3,11 @@
import json
import os
import re
from typing import Any, cast, Dict, List, Optional
from typing import Any, Optional
from urllib.error import HTTPError
from github_utils import gh_fetch_url, gh_post_pr_comment, gh_query_issues_by_labels
from github_utils import gh_fetch_url, gh_post_pr_comment
from gitutils import get_git_remote_name, get_git_repo_dir, GitRepo
from trymerge import get_pr_commit_sha, GitHubPR
@ -19,7 +19,6 @@ REQUIRES_ISSUE = {
"critical",
"fixnewfeature",
}
RELEASE_BRANCH_REGEX = re.compile(r"release/(?P<version>.+)")
def parse_args() -> Any:
@ -59,33 +58,6 @@ def get_merge_commit_sha(repo: GitRepo, pr: GitHubPR) -> Optional[str]:
return commit_sha if pr.is_closed() else None
def get_release_version(onto_branch: str) -> Optional[str]:
"""
Return the release version if the target branch is a release branch
"""
m = re.match(RELEASE_BRANCH_REGEX, onto_branch)
return m.group("version") if m else ""
def get_tracker_issues(
org: str, project: str, onto_branch: str
) -> List[Dict[str, Any]]:
"""
Find the tracker issue from the repo. The tracker issue needs to have the title
like [VERSION] Release Tracker following the convention on PyTorch
"""
version = get_release_version(onto_branch)
if not version:
return []
tracker_issues = gh_query_issues_by_labels(org, project, labels=["release tracker"])
if not tracker_issues:
return []
# Figure out the tracker issue from the list by looking at the title
return [issue for issue in tracker_issues if version in issue.get("title", "")]
def cherry_pick(
github_actor: str,
repo: GitRepo,
@ -105,49 +77,17 @@ def cherry_pick(
)
try:
org, project = repo.gh_owner_and_name()
cherry_pick_pr = ""
if not dry_run:
org, project = repo.gh_owner_and_name()
cherry_pick_pr = submit_pr(repo, pr, cherry_pick_branch, onto_branch)
tracker_issues_comments = []
tracker_issues = get_tracker_issues(org, project, onto_branch)
for issue in tracker_issues:
issue_number = int(str(issue.get("number", "0")))
if not issue_number:
continue
msg = f"The cherry pick PR is at {cherry_pick_pr}"
if fixes:
msg += f" and it is linked with issue {fixes}"
elif classification in REQUIRES_ISSUE:
msg += f" and it is recommended to link a {classification} cherry pick PR with an issue"
res = cast(
Dict[str, Any],
post_tracker_issue_comment(
org,
project,
issue_number,
pr.pr_num,
cherry_pick_pr,
classification,
fixes,
dry_run,
),
)
comment_url = res.get("html_url", "")
if comment_url:
tracker_issues_comments.append(comment_url)
msg = f"The cherry pick PR is at {cherry_pick_pr}"
if fixes:
msg += f" and it is linked with issue {fixes}."
elif classification in REQUIRES_ISSUE:
msg += f" and it is recommended to link a {classification} cherry pick PR with an issue."
if tracker_issues_comments:
msg += " The following tracker issues are updated:\n"
for tracker_issues_comment in tracker_issues_comments:
msg += f"* {tracker_issues_comment}\n"
post_pr_comment(org, project, pr.pr_num, msg, dry_run)
post_comment(org, project, pr.pr_num, msg)
finally:
if current_branch:
@ -219,9 +159,7 @@ def submit_pr(
raise RuntimeError(msg) from error
def post_pr_comment(
org: str, project: str, pr_num: int, msg: str, dry_run: bool = False
) -> List[Dict[str, Any]]:
def post_comment(org: str, project: str, pr_num: int, msg: str) -> None:
"""
Post a comment on the PR itself to point to the cherry picking PR when success
or print the error when failure
@ -244,35 +182,7 @@ def post_pr_comment(
comment = "\n".join(
(f"### Cherry picking #{pr_num}", f"{msg}", "", f"{internal_debugging}")
)
return gh_post_pr_comment(org, project, pr_num, comment, dry_run)
def post_tracker_issue_comment(
org: str,
project: str,
issue_num: int,
pr_num: int,
cherry_pick_pr: str,
classification: str,
fixes: str,
dry_run: bool = False,
) -> List[Dict[str, Any]]:
"""
Post a comment on the tracker issue (if any) to record the cherry pick
"""
comment = "\n".join(
(
"Link to landed trunk PR (if applicable):",
f"* https://github.com/{org}/{project}/pull/{pr_num}",
"",
"Link to release branch PR:",
f"* {cherry_pick_pr}",
"",
"Criteria Category:",
" - ".join((classification.capitalize(), fixes.capitalize())),
)
)
return gh_post_pr_comment(org, project, issue_num, comment, dry_run)
gh_post_pr_comment(org, project, pr_num, comment)
def main() -> None:
@ -304,7 +214,7 @@ def main() -> None:
except RuntimeError as error:
if not args.dry_run:
post_pr_comment(org, project, pr_num, str(error))
post_comment(org, project, pr_num, str(error))
else:
raise error

Binary file not shown.

View File

@ -8,7 +8,6 @@ architectures:
* CPU
* Latest CUDA
* Latest ROCM
* Latest XPU
"""
import os
@ -25,7 +24,6 @@ CUDA_ARCHES_CUDNN_VERSION = {"11.8": "9", "12.1": "9", "12.4": "9"}
ROCM_ARCHES = ["6.0", "6.1"]
XPU_ARCHES = ["xpu"]
CPU_CXX11_ABI_ARCH = ["cpu-cxx11-abi"]
@ -50,7 +48,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu11==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"12.1": (
@ -63,7 +61,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"12.4": (
@ -76,7 +74,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
@ -134,8 +132,6 @@ def arch_type(arch_version: str) -> str:
return "cuda"
elif arch_version in ROCM_ARCHES:
return "rocm"
elif arch_version in XPU_ARCHES:
return "xpu"
elif arch_version in CPU_CXX11_ABI_ARCH:
return "cpu-cxx11-abi"
elif arch_version in CPU_AARCH64_ARCH:
@ -160,7 +156,6 @@ WHEEL_CONTAINER_IMAGES = {
gpu_arch: f"pytorch/manylinux-builder:rocm{gpu_arch}-{DEFAULT_TAG}"
for gpu_arch in ROCM_ARCHES
},
"xpu": f"pytorch/manylinux2_28-builder:xpu-{DEFAULT_TAG}",
"cpu": f"pytorch/manylinux-builder:cpu-{DEFAULT_TAG}",
"cpu-cxx11-abi": f"pytorch/manylinuxcxx11-abi-builder:cpu-cxx11-abi-{DEFAULT_TAG}",
"cpu-aarch64": f"pytorch/manylinuxaarch64-builder:cpu-aarch64-{DEFAULT_TAG}",
@ -226,7 +221,6 @@ def translate_desired_cuda(gpu_arch_type: str, gpu_arch_version: str) -> str:
"cuda": f"cu{gpu_arch_version.replace('.', '')}",
"cuda-aarch64": "cu124",
"rocm": f"rocm{gpu_arch_version}",
"xpu": "xpu",
}.get(gpu_arch_type, gpu_arch_version)
@ -331,13 +325,13 @@ def generate_wheels_matrix(
package_type = "manywheel"
if python_versions is None:
python_versions = FULL_PYTHON_VERSIONS + ["3.13"]
python_versions = FULL_PYTHON_VERSIONS
if arches is None:
# Define default compute archivectures
arches = ["cpu"]
if os == "linux":
arches += CPU_CXX11_ABI_ARCH + CUDA_ARCHES + ROCM_ARCHES + XPU_ARCHES
arches += CPU_CXX11_ABI_ARCH + CUDA_ARCHES + ROCM_ARCHES
elif os == "windows":
arches += CUDA_ARCHES
elif os == "linux-aarch64":
@ -353,6 +347,10 @@ def generate_wheels_matrix(
for python_version in python_versions:
for arch_version in arches:
gpu_arch_type = arch_type(arch_version)
# Disable py3.12 builds for ROCm because of triton dependency
# on llnl-hatchet, which doesn't have py3.12 wheels available
if gpu_arch_type == "rocm" and python_version == "3.12":
continue
gpu_arch_version = (
""
if arch_version == "cpu"
@ -360,16 +358,9 @@ def generate_wheels_matrix(
or arch_version == "cpu-aarch64"
or arch_version == "cpu-s390x"
or arch_version == "cuda-aarch64"
or arch_version == "xpu"
else arch_version
)
# TODO: Enable python 3.13 on rocm, xpu, aarch64, windows
if (
gpu_arch_type in ["rocm", "xpu"] or os != "linux"
) and python_version == "3.13":
continue
# 12.1 linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
if (
arch_version in ["12.4", "12.1", "11.8"]
@ -399,49 +390,6 @@ def generate_wheels_matrix(
),
}
)
if arch_version != "cuda-aarch64":
ret.append(
{
"python_version": python_version,
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"use_split_build": "True",
"devtoolset": "",
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"pytorch_extra_install_requirements": (
PYTORCH_EXTRA_INSTALL_REQUIREMENTS[arch_version] # fmt: skip
if os != "linux-aarch64"
else ""
),
"build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-split".replace( # noqa: B950
".", "_"
),
}
)
# Special build building to use on Colab. PyThon 3.10 for 12.1 CUDA
if python_version == "3.10" and arch_version == "12.1":
ret.append(
{
"python_version": python_version,
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"use_split_build": "False",
"devtoolset": "",
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"pytorch_extra_install_requirements": "",
"build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-full".replace( # noqa: B950
".", "_"
),
}
)
else:
ret.append(
{
@ -452,9 +400,7 @@ def generate_wheels_matrix(
gpu_arch_type, gpu_arch_version
),
"devtoolset": (
"cxx11-abi"
if arch_version in ["cpu-cxx11-abi", "xpu"]
else ""
"cxx11-abi" if arch_version == "cpu-cxx11-abi" else ""
),
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,

99
.github/scripts/get_workflow_type.py vendored Normal file
View File

@ -0,0 +1,99 @@
import json
from argparse import ArgumentParser
from typing import Any
from github import Auth, Github
from github.Issue import Issue
WORKFLOW_TYPE_LABEL = "label"
WORKFLOW_TYPE_RG = "rg"
WORKFLOW_TYPE_BOTH = "both"
def parse_args() -> Any:
parser = ArgumentParser("Get dynamic rollout settings")
parser.add_argument("--github-token", type=str, required=True, help="GitHub token")
parser.add_argument(
"--github-repo",
type=str,
required=False,
default="pytorch/test-infra",
help="GitHub repo to get the issue",
)
parser.add_argument(
"--github-issue", type=int, required=True, help="GitHub issue umber"
)
parser.add_argument(
"--github-user", type=str, required=True, help="GitHub username"
)
parser.add_argument(
"--github-branch", type=str, required=True, help="Current GitHub branch"
)
return parser.parse_args()
def get_gh_client(github_token: str) -> Github:
auth = Auth.Token(github_token)
return Github(auth=auth)
def get_issue(gh: Github, repo: str, issue_num: int) -> Issue:
repo = gh.get_repo(repo)
return repo.get_issue(number=issue_num)
def is_exception_branch(branch: str) -> bool:
return branch.split("/")[0] in {"main", "nightly", "release", "landchecks"}
def get_workflow_type(issue: Issue, username: str) -> str:
user_list = issue.get_comments()[0].body.split("\r\n")
try:
run_option = issue.get_comments()[1].body.split("\r\n")[0]
except Exception as e:
run_option = "single"
if user_list[0] == "!":
# Use old runners for everyone
return WORKFLOW_TYPE_LABEL
elif user_list[1] == "*":
if run_option == WORKFLOW_TYPE_BOTH:
# Use ARC runners and old runners for everyone
return WORKFLOW_TYPE_BOTH
else:
# Use only ARC runners for everyone
return WORKFLOW_TYPE_RG
elif username in user_list:
if run_option == WORKFLOW_TYPE_BOTH:
# Use ARC runners and old runners for a specific user
return WORKFLOW_TYPE_BOTH
else:
# Use only ARC runners for a specific user
return WORKFLOW_TYPE_RG
else:
# Use old runners by default
return WORKFLOW_TYPE_LABEL
def main() -> None:
args = parse_args()
if is_exception_branch(args.github_branch):
output = {"workflow_type": WORKFLOW_TYPE_LABEL}
else:
try:
gh = get_gh_client(args.github_token)
issue = get_issue(gh, args.github_repo, args.github_issue)
output = {"workflow_type": get_workflow_type(issue, args.github_user)}
except Exception as e:
output = {"workflow_type": WORKFLOW_TYPE_LABEL}
json_output = json.dumps(output)
print(json_output)
if __name__ == "__main__":
main()

View File

@ -202,12 +202,3 @@ def gh_update_pr_state(org: str, repo: str, pr_num: int, state: str = "open") ->
)
else:
raise
def gh_query_issues_by_labels(
org: str, repo: str, labels: List[str], state: str = "open"
) -> List[Dict[str, Any]]:
url = f"{GITHUB_API_URL}/repos/{org}/{repo}/issues"
return gh_fetch_json(
url, method="GET", params={"labels": ",".join(labels), "state": state}
)

Binary file not shown.

View File

@ -29,7 +29,6 @@ python3 -m tools.pyi.gen_pyi \
--native-functions-path aten/src/ATen/native/native_functions.yaml \
--tags-path aten/src/ATen/native/tags.yaml \
--deprecated-functions-path "tools/autograd/deprecated.yaml"
python3 torch/utils/data/datapipes/gen_pyi.py
RC=0
# Run lintrunner on all files

View File

@ -1,210 +0,0 @@
# flake8: noqa: G004
import logging
import os
from argparse import ArgumentParser
from logging import LogRecord
from typing import Any, Iterable
from github import Auth, Github
from github.Issue import Issue
WORKFLOW_LABEL_META = "" # use meta runners
WORKFLOW_LABEL_LF = "lf." # use runners from the linux foundation
GITHUB_OUTPUT = os.getenv("GITHUB_OUTPUT", "")
GH_OUTPUT_KEY_LABEL_TYPE = "label-type"
class ColorFormatter(logging.Formatter):
"""Color codes the log messages based on the log level"""
COLORS = {
"WARNING": "\033[33m", # Yellow
"ERROR": "\033[31m", # Red
"CRITICAL": "\033[31m", # Red
"INFO": "\033[0m", # Reset
"DEBUG": "\033[0m", # Reset
}
def format(self, record: LogRecord) -> str:
log_color = self.COLORS.get(record.levelname, "\033[0m") # Default to reset
record.msg = f"{log_color}{record.msg}\033[0m"
return super().format(record)
handler = logging.StreamHandler()
handler.setFormatter(ColorFormatter(fmt="%(levelname)-8s: %(message)s"))
log = logging.getLogger(os.path.basename(__file__))
log.addHandler(handler)
log.setLevel(logging.INFO)
def set_github_output(key: str, value: str) -> None:
"""
Defines outputs of the github action that invokes this script
"""
if not GITHUB_OUTPUT:
# See https://github.blog/changelog/2022-10-11-github-actions-deprecating-save-state-and-set-output-commands/ for deprecation notice
log.warning(
"No env var found for GITHUB_OUTPUT, you must be running this code locally. Falling back to the deprecated print method."
)
print(f"::set-output name={key}::{value}")
return
with open(GITHUB_OUTPUT, "a") as f:
log.info(f"Setting output: {key}='{value}'")
f.write(f"{key}={value}\n")
def parse_args() -> Any:
parser = ArgumentParser("Get dynamic rollout settings")
parser.add_argument("--github-token", type=str, required=True, help="GitHub token")
parser.add_argument(
"--github-issue-repo",
type=str,
required=False,
default="pytorch/test-infra",
help="GitHub repo to get the issue",
)
parser.add_argument(
"--github-repo",
type=str,
required=True,
help="GitHub repo where CI is running",
)
parser.add_argument(
"--github-issue", type=int, required=True, help="GitHub issue number"
)
parser.add_argument(
"--github-actor", type=str, required=True, help="GitHub triggering_actor"
)
parser.add_argument(
"--github-issue-owner", type=str, required=True, help="GitHub issue owner"
)
parser.add_argument(
"--github-branch", type=str, required=True, help="Current GitHub branch or tag"
)
parser.add_argument(
"--github-ref-type",
type=str,
required=True,
help="Current GitHub ref type, branch or tag",
)
return parser.parse_args()
def get_gh_client(github_token: str) -> Github:
auth = Auth.Token(github_token)
return Github(auth=auth)
def get_issue(gh: Github, repo: str, issue_num: int) -> Issue:
repo = gh.get_repo(repo)
return repo.get_issue(number=issue_num)
def get_potential_pr_author(
gh: Github, repo: str, username: str, ref_type: str, ref_name: str
) -> str:
# If the trigger was a new tag added by a bot, this is a ciflow case
# Fetch the actual username from the original PR. The PR number is
# embedded in the tag name: ciflow/<name>/<pr-number>
if username == "pytorch-bot[bot]" and ref_type == "tag":
split_tag = ref_name.split("/")
if (
len(split_tag) == 3
and split_tag[0] == "ciflow"
and split_tag[2].isnumeric()
):
pr_number = split_tag[2]
try:
repository = gh.get_repo(repo)
pull = repository.get_pull(number=int(pr_number))
except Exception as e:
raise Exception( # noqa: TRY002
f"issue with pull request {pr_number} from repo {repository}"
) from e
return pull.user.login
# In all other cases, return the original input username
return username
def is_exception_branch(branch: str) -> bool:
return branch.split("/")[0] in {"main", "nightly", "release", "landchecks"}
def get_workflow_type(issue: Issue, workflow_requestors: Iterable[str]) -> str:
try:
first_comment = issue.get_comments()[0].body.strip("\n\t ")
if first_comment[0] == "!":
log.info("LF Workflows are disabled for everyone. Using meta runners.")
return WORKFLOW_LABEL_META
elif first_comment[0] == "*":
log.info("LF Workflows are enabled for everyone. Using LF runners.")
return WORKFLOW_LABEL_LF
else:
all_opted_in_users = {
usr_raw.strip("\n\t@ ") for usr_raw in first_comment.split()
}
opted_in_requestors = {
usr for usr in workflow_requestors if usr in all_opted_in_users
}
if opted_in_requestors:
log.info(
f"LF Workflows are enabled for {', '.join(opted_in_requestors)}. Using LF runners."
)
return WORKFLOW_LABEL_LF
else:
log.info(
f"LF Workflows are disabled for {', '.join(workflow_requestors)}. Using meta runners."
)
return WORKFLOW_LABEL_META
except Exception as e:
log.error(
f"Failed to get determine workflow type. Falling back to meta runners. Exception: {e}"
)
return WORKFLOW_LABEL_META
def main() -> None:
args = parse_args()
if args.github_ref_type == "branch" and is_exception_branch(args.github_branch):
log.info(f"Exception branch: '{args.github_branch}', using meta runners")
label_type = WORKFLOW_LABEL_META
else:
try:
gh = get_gh_client(args.github_token)
# The default issue we use - https://github.com/pytorch/test-infra/issues/5132
issue = get_issue(gh, args.github_issue_repo, args.github_issue)
username = get_potential_pr_author(
gh,
args.github_repo,
args.github_actor,
args.github_ref_type,
args.github_branch,
)
label_type = get_workflow_type(
issue,
(
args.github_issue_owner,
username,
),
)
except Exception as e:
log.error(
f"Failed to get issue. Falling back to meta runners. Exception: {e}"
)
label_type = WORKFLOW_LABEL_META
set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, label_type)
if __name__ == "__main__":
main()

View File

@ -2,7 +2,7 @@
set -eoux pipefail
SYNC_BRANCH=pytorch-stable-prototype
SYNC_BRANCH=fbcode/pytorch-stable-prototype
git config user.email "fake@example.com"
git config user.name "PyTorch Stable Bot"
@ -11,9 +11,7 @@ git fetch origin main
git fetch origin "$SYNC_BRANCH"
git checkout "$SYNC_BRANCH"
# Using a hardcoded SHA here is a massive speedup as we can skip the entire history of the pytorch GitHub repo.
# This specific SHA was chosen as it was before the "branch point" of the stable branch
for SHA in $(git log ba3b05fdf37ddbc3c301294d6a560a816335e717..origin/main --pretty="%h" --reverse -- torch/distributed torch/csrc/distributed test/distributed test/cpp/c10d benchmarks/distributed)
for SHA in $(git log 4333e122d4b74cdf84351ed2907045c6a767b4cd..origin/main --pretty="%h" --reverse -- torch/distributed torch/csrc/distributed test/distributed test/cpp/c10d benchmarks/distributed)
do
# `git merge-base --is-ancestor` exits with code 0 if the given SHA is an ancestor, and non-0 otherwise
if git merge-base --is-ancestor $SHA HEAD || [[ $(git log --grep="(cherry picked from commit $SHA") ]]
@ -22,12 +20,7 @@ do
continue
fi
echo "Copying $SHA"
git cherry-pick -x "$SHA" -X theirs
git reset --soft HEAD~1
git add torch/distributed torch/csrc/distributed test/distributed test/cpp/c10d benchmarks/distributed
git checkout .
git commit --reuse-message=HEAD@{1}
git clean -f
git cherry-pick -x "$SHA"
done
if [[ "${WITH_PUSH}" == true ]]; then

View File

@ -41,7 +41,7 @@ def main() -> None:
)
options = parser.parse_args()
tagged_images: Dict[str, bool] = {}
tagged_images: Dict[str, bool] = dict()
platform_images = [
generate_binary_build_matrix.WHEEL_CONTAINER_IMAGES,
generate_binary_build_matrix.LIBTORCH_CONTAINER_IMAGES,

View File

@ -7,7 +7,6 @@ cd llm-target-determinator
pip install -q -r requirements.txt
cd ../codellama
pip install -e .
pip install numpy==1.26.0
# Run indexer
cd ../llm-target-determinator

View File

@ -180,9 +180,6 @@ def mock_gh_get_info() -> Any:
return {
"closed": False,
"isCrossRepository": False,
"headRefName": "foo",
"baseRefName": "bar",
"baseRepository": {"defaultBranchRef": {"name": "bar"}},
"files": {"nodes": [], "pageInfo": {"hasNextPage": False}},
"changedFiles": 0,
}
@ -397,7 +394,6 @@ class TestTryMerge(TestCase):
# self.assertGreater(len(pr.get_checkrun_conclusions()), 3)
self.assertGreater(pr.get_commit_count(), 60)
@skip("GitHub doesn't keep this data anymore")
def test_gql_retrieve_checksuites(self, *args: Any) -> None:
"Fetch comments and conclusions for PR with 60 commits"
pr = GitHubPR("pytorch", "pytorch", 94787)
@ -895,24 +891,6 @@ class TestBypassFailures(TestCase):
self.assertTrue(len(ignorable["FLAKY"]) == 1)
self.assertTrue(len(ignorable["BROKEN_TRUNK"]) == 0)
def test_ignore_failures_older_run_same_workflow(self, *args: Any) -> None:
pr = GitHubPR("pytorch", "pytorch", 129013)
checks = pr.get_checkrun_conclusions()
checks = get_classifications(
pr.pr_num,
pr.project,
checks,
[],
)
pending, failed, ignorable = categorize_checks(
checks,
list(checks.keys()),
)
self.assertTrue(len(pending) == 0)
self.assertTrue(len(failed) == 0)
self.assertTrue(len(ignorable["FLAKY"]) == 2)
self.assertTrue(len(ignorable["UNSTABLE"]) == 13)
@mock.patch("trymerge.read_merge_rules", side_effect=xla_merge_rules)
def test_dont_ignore_flaky_failures(self, *args: Any) -> None:
"""
@ -1041,7 +1019,7 @@ class TestGitHubPRGhstackDependencies(TestCase):
)
@skip(
reason="This test is run against a mutable PR that has changed, so it no longer works. The test should be changed"
reason="This test is run against a mutalbe PR that has changed, so it no longer works. The test should be changed"
)
@mock.patch("trymerge.read_merge_rules")
@mock.patch("trymerge.GitRepo")

View File

@ -81,10 +81,9 @@ JobNameToStateDict = Dict[str, JobCheckState]
class WorkflowCheckState:
def __init__(self, name: str, url: str, run_id: int, status: Optional[str]):
def __init__(self, name: str, url: str, status: Optional[str]):
self.name: str = name
self.url: str = url
self.run_id: int = run_id
self.status: Optional[str] = status
self.jobs: JobNameToStateDict = {}
@ -123,7 +122,6 @@ fragment PRCheckSuites on CheckSuiteConnection {
workflowRun {
workflow {
name
databaseId
}
databaseId
url
@ -514,7 +512,7 @@ def add_workflow_conclusions(
workflows: Dict[str, WorkflowCheckState] = {}
# for the jobs that don't have a workflow
no_workflow_obj: WorkflowCheckState = WorkflowCheckState("", "", 0, None)
no_workflow_obj: WorkflowCheckState = WorkflowCheckState("", "", None)
def add_conclusions(edges: Any) -> None:
for edge_idx, edge in enumerate(edges):
@ -525,30 +523,18 @@ def add_workflow_conclusions(
workflow_obj: WorkflowCheckState = no_workflow_obj
if workflow_run is not None:
# This is the usual workflow run ID we see on GitHub
workflow_run_id = workflow_run["databaseId"]
# While this is the metadata name and ID of the workflow itself
workflow_name = workflow_run["workflow"]["name"]
workflow_id = workflow_run["workflow"]["databaseId"]
workflow_conclusion = node["conclusion"]
# Do not override existing status with cancelled
if workflow_conclusion == "CANCELLED" and workflow_name in workflows:
continue
# Only keep the latest workflow run for each workflow, heuristically,
# it's the run with largest run ID
if (
workflow_id not in workflows
or workflows[workflow_id].run_id < workflow_run_id
):
workflows[workflow_id] = WorkflowCheckState(
if workflow_name not in workflows:
workflows[workflow_name] = WorkflowCheckState(
name=workflow_name,
status=workflow_conclusion,
url=workflow_run["url"],
run_id=workflow_run_id,
)
workflow_obj = workflows[workflow_id]
workflow_obj = workflows[workflow_name]
while checkruns is not None:
for checkrun_node in checkruns["nodes"]:
@ -586,12 +572,12 @@ def add_workflow_conclusions(
# the jobs in but don't put the workflow in. We care more about the jobs in
# the workflow that ran than the container workflow.
res: JobNameToStateDict = {}
for workflow in workflows.values():
for workflow_name, workflow in workflows.items():
if len(workflow.jobs) > 0:
for job_name, job in workflow.jobs.items():
res[job_name] = job
else:
res[workflow.name] = JobCheckState(
res[workflow_name] = JobCheckState(
workflow.name,
workflow.url,
workflow.status,
@ -1177,6 +1163,7 @@ class GitHubPR:
# Finally, upload the record to Rockset. The list of pending and failed
# checks are at the time of the merge
save_merge_record(
collection=ROCKSET_MERGES_COLLECTION,
comment_id=comment_id,
pr_num=self.pr_num,
owner=self.org,
@ -1192,8 +1179,10 @@ class GitHubPR:
merge_base_sha=self.get_merge_base(),
merge_commit_sha=merge_commit_sha,
is_failed=False,
dry_run=dry_run,
skip_mandatory_checks=skip_mandatory_checks,
ignore_current=bool(ignore_current_checks),
workspace=ROCKSET_MERGES_WORKSPACE,
)
else:
print("Missing comment ID or PR number, couldn't upload to Rockset")
@ -1500,6 +1489,7 @@ def checks_to_markdown_bullets(
@retries_decorator()
def save_merge_record(
collection: str,
comment_id: int,
pr_num: int,
owner: str,
@ -1515,44 +1505,59 @@ def save_merge_record(
merge_base_sha: str,
merge_commit_sha: str = "",
is_failed: bool = False,
dry_run: bool = False,
skip_mandatory_checks: bool = False,
ignore_current: bool = False,
error: str = "",
workspace: str = "commons",
) -> None:
"""
This saves the merge records as a json, which can later be uploaded to s3
This saves the merge records into Rockset, so we can query them (for fun and profit)
"""
if dry_run:
# Decide not to save the record to Rockset if dry-run is set to not pollute
# the collection
return
# Prepare the record to be written into Rockset
data = [
{
"comment_id": comment_id,
"pr_num": pr_num,
"owner": owner,
"project": project,
"author": author,
"pending_checks": pending_checks,
"failed_checks": failed_checks,
"ignore_current_checks": ignore_current_checks,
"broken_trunk_checks": broken_trunk_checks,
"flaky_checks": flaky_checks,
"unstable_checks": unstable_checks,
"last_commit_sha": last_commit_sha,
"merge_base_sha": merge_base_sha,
"merge_commit_sha": merge_commit_sha,
"is_failed": is_failed,
"skip_mandatory_checks": skip_mandatory_checks,
"ignore_current": ignore_current,
"error": error,
# This is a unique identifier for the record for deduping purposes
# in rockset. Any unique string would work
"_id": f"{project}-{pr_num}-{comment_id}-{os.environ.get('GITHUB_RUN_ID')}",
}
]
repo_root = Path(__file__).resolve().parent.parent.parent
try:
import rockset # type: ignore[import]
with open(repo_root / "merge_record.json", "w") as f:
json.dump(data, f)
# Prepare the record to be written into Rockset
data = [
{
"comment_id": comment_id,
"pr_num": pr_num,
"owner": owner,
"project": project,
"author": author,
"pending_checks": pending_checks,
"failed_checks": failed_checks,
"ignore_current_checks": ignore_current_checks,
"broken_trunk_checks": broken_trunk_checks,
"flaky_checks": flaky_checks,
"unstable_checks": unstable_checks,
"last_commit_sha": last_commit_sha,
"merge_base_sha": merge_base_sha,
"merge_commit_sha": merge_commit_sha,
"is_failed": is_failed,
"skip_mandatory_checks": skip_mandatory_checks,
"ignore_current": ignore_current,
"error": error,
}
]
client = rockset.RocksetClient(
host="api.usw2a1.rockset.com", api_key=os.environ["ROCKSET_API_KEY"]
)
client.Documents.add_documents(
collection=collection,
data=data,
workspace=workspace,
)
except ModuleNotFoundError:
print("Rockset is missing, no record will be saved")
return
@retries_decorator(rc=[])
@ -2325,15 +2330,6 @@ def main() -> None:
dry_run=args.dry_run,
)
return
if not pr.is_ghstack_pr() and pr.base_ref() != pr.default_branch():
gh_post_pr_comment(
org,
project,
args.pr_num,
f"PR targets {pr.base_ref()} rather than {pr.default_branch()}, refusing merge request",
dry_run=args.dry_run,
)
return
if args.check_mergeability:
if pr.is_ghstack_pr():
@ -2369,6 +2365,7 @@ def main() -> None:
# list of pending and failed checks here, but they are not really
# needed at the moment
save_merge_record(
collection=ROCKSET_MERGES_COLLECTION,
comment_id=args.comment_id,
pr_num=args.pr_num,
owner=org,
@ -2383,9 +2380,11 @@ def main() -> None:
last_commit_sha=pr.last_commit().get("oid", ""),
merge_base_sha=pr.get_merge_base(),
is_failed=True,
dry_run=args.dry_run,
skip_mandatory_checks=args.force,
ignore_current=args.ignore_current,
error=str(e),
workspace=ROCKSET_MERGES_WORKSPACE,
)
else:
print("Missing comment ID or PR number, couldn't upload to Rockset")

View File

@ -81,7 +81,7 @@ jobs:
!{{ config["build_name"] }}-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: !{{ config["build_name"] }}-build
{%- if config["gpu_arch_type"] not in ["rocm", "xpu"] %}
{%- if config["gpu_arch_type"] != "rocm" %}
uses: ./.github/workflows/_binary-test-linux.yml
with:!{{ upload.binary_env_as_input(config) }}
build_name: !{{ config["build_name"] }}
@ -101,40 +101,6 @@ jobs:
{%- endif %}
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
{%- elif config["gpu_arch_type"] == "xpu" %}
runs-on: linux.idc.xpu
timeout-minutes: !{{ common.timeout_minutes }}
!{{ upload.binary_env(config) }}
permissions:
id-token: write
contents: read
steps:
- name: Setup XPU
uses: ./.github/actions/setup-xpu
- name: configure aws credentials
id: aws_creds
uses: aws-actions/configure-aws-credentials@v1.7.0
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v2
- uses: !{{ common.download_artifact_action }}
name: Download Build Artifacts
with:
name: !{{ config["build_name"] }}
path: "${{ runner.temp }}/artifacts/"
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch) }}
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: !{{ config["container_image"] }}
- name: Test Pytorch binary
uses: ./pytorch/.github/actions/test-pytorch-binary
- name: Teardown XPU
uses: ./.github/actions/teardown-xpu
{%- else %}
runs-on: linux.rocm.gpu
timeout-minutes: !{{ common.timeout_minutes }}

View File

@ -30,9 +30,6 @@
{%- if config["devtoolset"] %}
DESIRED_DEVTOOLSET: !{{ config["devtoolset"] }}
{%- endif %}
{%- if config.use_split_build is defined %}
use_split_build: !{{ config["use_split_build"] }}
{%- endif %}
{%- endif %}
{%- if config["package_type"] == "libtorch" %}
{%- if config["libtorch_config"] %}
@ -47,7 +44,6 @@
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.8"
{%- endif %}
{%- else %}
DESIRED_PYTHON: "!{{ config["python_version"] }}"
{%- endif %}

View File

@ -27,11 +27,6 @@ on:
type: string
description: |
A JSON description of what configs to run later on.
runner:
required: false
type: string
default: "linux.large"
description: Runner type
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
@ -39,7 +34,7 @@ env:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: ${{ inputs.runner }}
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
is-test-matrix-empty: ${{ steps.filter.outputs.is-test-matrix-empty }}

View File

@ -21,13 +21,6 @@ on:
default: 210
type: number
description: timeout for the job
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
ALPINE_IMAGE:
required: false
type: string
@ -117,7 +110,6 @@ jobs:
PR_NUMBER: ${{ github.event.pull_request.number }}
PYTORCH_FINAL_PACKAGE_DIR: /artifacts
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
steps:
- name: Make the env permanent during this workflow (but not the secrets)
shell: bash
@ -145,7 +137,6 @@ jobs:
echo "PR_NUMBER=${{ env.PR_NUMBER }}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
echo "SHA1=${{ env.SHA1 }}"
echo "USE_SPLIT_BUILD=${{ env.use_split_build }}"
} >> "${GITHUB_ENV} }}"
- name: List the env
@ -255,7 +246,6 @@ jobs:
-e PYTORCH_ROOT \
-e SKIP_ALL_TESTS \
-e PYTORCH_EXTRA_INSTALL_REQUIREMENTS \
-e USE_SPLIT_BUILD \
--tty \
--detach \
-v "${GITHUB_WORKSPACE}/pytorch:/pytorch" \

View File

@ -63,13 +63,6 @@ on:
required: true
type: string
description: Hardware to run this job on. Valid values are linux.4xlarge, linux.4xlarge.nvidia.gpu, linux.arm64.2xlarge, and linux.rocm.gpu
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
secrets:
github-token:
required: true
@ -104,7 +97,6 @@ jobs:
PR_NUMBER: ${{ github.event.pull_request.number }}
PYTORCH_FINAL_PACKAGE_DIR: /artifacts
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
steps:
- name: Make the env permanent during this workflow (but not the secrets)
shell: bash
@ -132,7 +124,6 @@ jobs:
echo "PR_NUMBER=${{ env.PR_NUMBER }}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
echo "SHA1=${{ env.SHA1 }}"
echo "USE_SPLIT_BUILD=${{ env.USE_SPLIT_BUILD }}"
} >> "${GITHUB_ENV} }}"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"

View File

@ -55,13 +55,6 @@ on:
required: false
type: string
description: Desired python version
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
secrets:
github-token:
required: true
@ -100,7 +93,6 @@ jobs:
PR_NUMBER: ${{ github.event.pull_request.number }}
PYTORCH_FINAL_PACKAGE_DIR: /artifacts
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main

View File

@ -56,13 +56,6 @@ on:
required: false
type: string
default: ""
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
@ -114,4 +107,3 @@ jobs:
aws-role-to-assume: ${{ inputs.aws-role-to-assume }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
use_split_build: ${{ inputs.use_split_build }}

105
.github/workflows/_linux-build-rg.yml vendored Normal file
View File

@ -0,0 +1,105 @@
name: linux-build-rg
on:
workflow_call:
inputs:
build-environment:
required: true
type: string
description: Top-level label for what's being built/tested.
docker-image-name:
required: true
type: string
description: Name of the base docker image to build with.
build-generates-artifacts:
required: false
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
default: ""
description: |
If this is set, our linter will use this to make sure that every other
job with the same `sync-tag` is identical.
cuda-arch-list:
required: false
type: string
default: "5.2"
description: |
List of CUDA architectures CI build should target.
runner-group:
required: false
type: string
default: "arc-lf-linux.2xlarge"
description: Runner group to select group type
test-matrix:
required: false
type: string
description: |
An option JSON description of what test configs to run later on. This
is moved here from the Linux test workflow so that we can apply filter
logic using test-config labels earlier and skip unnecessary builds
s3-bucket:
description: S3 bucket to download artifact
required: false
type: string
default: "gha-artifacts"
aws-role-to-assume:
description: role to assume for downloading artifacts
required: false
type: string
default: ""
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
description: |
HF Auth token to avoid rate limits when downloading models or datasets from hub
outputs:
docker-image:
value: ${{ jobs.build.outputs.docker-image }}
description: The docker image containing the built PyTorch.
test-matrix:
value: ${{ jobs.build.outputs.test-matrix }}
description: An optional JSON description of what test configs to run later on.
jobs:
build:
# Don't run on forked repos
if: github.repository_owner == 'pytorch'
runs-on:
group: ${{ inputs.runner-group }}
timeout-minutes: 240
outputs:
docker-image: ${{ steps.linux-build.outputs.docker-image }}
test-matrix: ${{ steps.linux-build.outputs.test-matrix }}
steps:
# [pytorch repo ref]
# Use a pytorch/pytorch reference instead of a reference to the local
# checkout because when we run this action we don't *have* a local
# checkout. In other cases you should prefer a local checkout.
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
- name: Linux Build
id: linux-build
uses: ./.github/actions/linux-build
with:
build-environment: ${{ inputs.build-environment }}
docker-image-name: ${{ inputs.docker-image-name }}
build-generates-artifacts: ${{ inputs.build-generates-artifacts }}
build-with-debug: ${{ inputs.build-with-debug }}
sync-tag: ${{ inputs.sync-tag }}
cuda-arch-list: ${{ inputs.cuda-arch-list }}
test-matrix: ${{ inputs.test-matrix }}
s3-bucket: ${{ inputs.s3-bucket }}
aws-role-to-assume: ${{ inputs.aws-role-to-assume }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}

View File

@ -39,7 +39,7 @@ on:
type: string
default: "linux.2xlarge"
description: |
Label of the runner this job should run on.
List of CUDA architectures CI build should target.
test-matrix:
required: false
type: string
@ -64,14 +64,6 @@ on:
required: false
type: string
default: ""
use_split_build:
description: |
[Experimental] Build a libtorch only wheel and build pytorch such that
are built from the libtorch wheel.
required: false
type: boolean
default: false
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
@ -189,7 +181,6 @@ jobs:
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 }}
USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
run: |
# detached container should get cleaned up by teardown_ec2_linux
container_name=$(docker run \
@ -208,7 +199,6 @@ jobs:
-e PR_LABELS \
-e OUR_GITHUB_JOB_ID \
-e HUGGING_FACE_HUB_TOKEN \
-e USE_SPLIT_BUILD \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
@ -228,7 +218,7 @@ jobs:
- name: Store PyTorch Build Artifacts on S3
uses: seemethere/upload-artifact-s3@v5
if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && inputs.use_split_build != 'true'
if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped'
with:
name: ${{ inputs.build-environment }}
retention-days: 14
@ -236,16 +226,6 @@ jobs:
path: artifacts.zip
s3-bucket: ${{ inputs.s3-bucket }}
- name: Store PyTorch Build Artifacts on S3
uses: seemethere/upload-artifact-s3@v5
if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && inputs.use_split_build == 'true'
with:
name: ${{ inputs.build-environment }}-experimental-split-build
retention-days: 14
if-no-files-found: error
path: artifacts.zip
s3-bucket: ${{ inputs.s3-bucket }}
- name: Upload sccache stats
if: steps.build.outcome != 'skipped'
uses: seemethere/upload-artifact-s3@v5

85
.github/workflows/_linux-test-label.yml vendored Normal file
View File

@ -0,0 +1,85 @@
name: linux-test-rg
on:
workflow_call:
inputs:
build-environment:
required: true
type: string
description: Top-level label for what's being built/tested.
test-matrix:
required: true
type: string
description: JSON description of what test configs to run.
docker-image:
required: true
type: string
description: Docker image to run in.
sync-tag:
required: false
type: string
default: ""
description: |
If this is set, our linter will use this to make sure that every other
job with the same `sync-tag` is identical.
timeout-minutes:
required: false
type: number
default: 240
description: |
Set the maximum (in minutes) how long the workflow should take to finish
use-gha:
required: false
type: string
default: ""
description: If set to any value, upload to GHA. Otherwise upload to S3.
dashboard-tag:
required: false
type: string
default: ""
s3-bucket:
description: S3 bucket to download artifact
required: false
type: string
default: "gha-artifacts"
aws-role-to-assume:
description: role to assume for downloading artifacts
required: false
type: string
default: ""
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
description: |
HF Auth token to avoid rate limits when downloading models or datasets from hub
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
jobs:
test:
# Don't run on forked repos or empty test matrix
if: github.repository_owner == 'pytorch' && toJSON(fromJSON(inputs.test-matrix).include) != '[]'
strategy:
matrix: ${{ fromJSON(inputs.test-matrix) }}
fail-fast: false
runs-on: ${{ matrix.runner }}
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
- name: Linux Test
id: linux-test
uses: ./.github/actions/linux-test
with:
build-environment: ${{ inputs.build-environment }}
test-matrix: ${{ inputs.test-matrix }}
docker-image: ${{ inputs.docker-image }}
sync-tag: ${{ inputs.sync-tag }}
use-gha: ${{ inputs.use-gha }}
dashboard-tag: ${{ inputs.dashboard-tag }}
s3-bucket: ${{ inputs.s3-bucket }}
aws-role-to-assume: ${{ inputs.aws-role-to-assume }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

86
.github/workflows/_linux-test-rg.yml vendored Normal file
View File

@ -0,0 +1,86 @@
name: linux-test-label
on:
workflow_call:
inputs:
build-environment:
required: true
type: string
description: Top-level label for what's being built/tested.
test-matrix:
required: true
type: string
description: JSON description of what test configs to run.
docker-image:
required: true
type: string
description: Docker image to run in.
sync-tag:
required: false
type: string
default: ""
description: |
If this is set, our linter will use this to make sure that every other
job with the same `sync-tag` is identical.
timeout-minutes:
required: false
type: number
default: 240
description: |
Set the maximum (in minutes) how long the workflow should take to finish
use-gha:
required: false
type: string
default: ""
description: If set to any value, upload to GHA. Otherwise upload to S3.
dashboard-tag:
required: false
type: string
default: ""
s3-bucket:
description: S3 bucket to download artifact
required: false
type: string
default: "gha-artifacts"
aws-role-to-assume:
description: role to assume for downloading artifacts
required: false
type: string
default: ""
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
description: |
HF Auth token to avoid rate limits when downloading models or datasets from hub
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
jobs:
test:
# Don't run on forked repos or empty test matrix
if: github.repository_owner == 'pytorch' && toJSON(fromJSON(inputs.test-matrix).include) != '[]'
strategy:
matrix: ${{ fromJSON(inputs.test-matrix) }}
fail-fast: false
runs-on:
group: ${{ matrix.runner }}
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
- name: Linux Test
id: linux-test
uses: ./.github/actions/linux-test
with:
build-environment: ${{ inputs.build-environment }}
test-matrix: ${{ inputs.test-matrix }}
docker-image: ${{ inputs.docker-image }}
sync-tag: ${{ inputs.sync-tag }}
use-gha: ${{ inputs.use-gha }}
dashboard-tag: ${{ inputs.dashboard-tag }}
s3-bucket: ${{ inputs.s3-bucket }}
aws-role-to-assume: ${{ inputs.aws-role-to-assume }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View File

@ -3,272 +3,39 @@ name: Check whether the workflow owner can use ARC runners
on:
workflow_call:
inputs:
triggering_actor:
user_name:
required: true
type: string
description: The triggering_actor for the workflow. Use github.triggering_actor
issue_owner:
required: true
type: string
description: The owner of the issue. Use github.event.pull_request.user.login || github.event.issue.user.login
description: The name of the workflow owner.
curr_branch:
required: true
type: string
description: Current branch or tag.
curr_ref_type:
required: false
type: string
default: branch
description: The value of "github.ref_type", "branch" or "tag"
description: Current branch.
issue_number:
required: false
type: string
default: "5132"
description: |
Fetch's GitHub Issue from pytorch/test-infra
Example: https://github.com/pytorch/test-infra/issues/5132
outputs:
label-type:
workflow-type:
description: Type of runners to use
value: ${{ jobs.runner-determinator.outputs.label-type }}
value: ${{ jobs.runner-determinator.outputs.workflow-type }}
jobs:
runner-determinator:
runs-on: ubuntu-latest
runs-on: linux.4xlarge
outputs:
label-type: ${{ steps.set-condition.outputs.label-type }}
workflow-type: ${{ steps.set-condition.outputs.workflow-type }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
ISSUE_NUMBER: ${{ inputs.issue_number }}
TRIGGERING_ACTOR: ${{ inputs.triggering_actor }}
ISSUE_OWNER: ${{ inputs.issue_owner }}
USERNAME: ${{ inputs.user_name }}
steps:
# - name: Checkout PyTorch
# uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
# with:
# fetch-depth: 1
# submodules: true
# TODO: Remove the hardcoded step below
# Hardcoding below is temporary for testing ALI runners
# This file below should match the script found in .github/scripts/runner_determinator.py
- name: Hardcode runner-determinator script
run: |
cat <<EOF > runner_determinator.py
# flake8: noqa: G004
import logging
import os
from argparse import ArgumentParser
from logging import LogRecord
from typing import Any, Iterable
from github import Auth, Github
from github.Issue import Issue
WORKFLOW_LABEL_META = "" # use meta runners
WORKFLOW_LABEL_LF = "lf." # use runners from the linux foundation
GITHUB_OUTPUT = os.getenv("GITHUB_OUTPUT", "")
GH_OUTPUT_KEY_LABEL_TYPE = "label-type"
class ColorFormatter(logging.Formatter):
"""Color codes the log messages based on the log level"""
COLORS = {
"WARNING": "\033[33m", # Yellow
"ERROR": "\033[31m", # Red
"CRITICAL": "\033[31m", # Red
"INFO": "\033[0m", # Reset
"DEBUG": "\033[0m", # Reset
}
def format(self, record: LogRecord) -> str:
log_color = self.COLORS.get(record.levelname, "\033[0m") # Default to reset
record.msg = f"{log_color}{record.msg}\033[0m"
return super().format(record)
handler = logging.StreamHandler()
handler.setFormatter(ColorFormatter(fmt="%(levelname)-8s: %(message)s"))
log = logging.getLogger(os.path.basename(__file__))
log.addHandler(handler)
log.setLevel(logging.INFO)
def set_github_output(key: str, value: str) -> None:
"""
Defines outputs of the github action that invokes this script
"""
if not GITHUB_OUTPUT:
# See https://github.blog/changelog/2022-10-11-github-actions-deprecating-save-state-and-set-output-commands/ for deprecation notice
log.warning(
"No env var found for GITHUB_OUTPUT, you must be running this code locally. Falling back to the deprecated print method."
)
print(f"::set-output name={key}::{value}")
return
with open(GITHUB_OUTPUT, "a") as f:
log.info(f"Setting output: {key}='{value}'")
f.write(f"{key}={value}\n")
def parse_args() -> Any:
parser = ArgumentParser("Get dynamic rollout settings")
parser.add_argument("--github-token", type=str, required=True, help="GitHub token")
parser.add_argument(
"--github-issue-repo",
type=str,
required=False,
default="pytorch/test-infra",
help="GitHub repo to get the issue",
)
parser.add_argument(
"--github-repo",
type=str,
required=True,
help="GitHub repo where CI is running",
)
parser.add_argument(
"--github-issue", type=int, required=True, help="GitHub issue number"
)
parser.add_argument(
"--github-actor", type=str, required=True, help="GitHub triggering_actor"
)
parser.add_argument(
"--github-issue-owner", type=str, required=True, help="GitHub issue owner"
)
parser.add_argument(
"--github-branch", type=str, required=True, help="Current GitHub branch or tag"
)
parser.add_argument(
"--github-ref-type",
type=str,
required=True,
help="Current GitHub ref type, branch or tag",
)
return parser.parse_args()
def get_gh_client(github_token: str) -> Github:
auth = Auth.Token(github_token)
return Github(auth=auth)
def get_issue(gh: Github, repo: str, issue_num: int) -> Issue:
repo = gh.get_repo(repo)
return repo.get_issue(number=issue_num)
def get_potential_pr_author(
gh: Github, repo: str, username: str, ref_type: str, ref_name: str
) -> str:
# If the trigger was a new tag added by a bot, this is a ciflow case
# Fetch the actual username from the original PR. The PR number is
# embedded in the tag name: ciflow/<name>/<pr-number>
if username == "pytorch-bot[bot]" and ref_type == "tag":
split_tag = ref_name.split("/")
if (
len(split_tag) == 3
and split_tag[0] == "ciflow"
and split_tag[2].isnumeric()
):
pr_number = split_tag[2]
try:
repository = gh.get_repo(repo)
pull = repository.get_pull(number=int(pr_number))
except Exception as e:
raise Exception( # noqa: TRY002
f"issue with pull request {pr_number} from repo {repository}"
) from e
return pull.user.login
# In all other cases, return the original input username
return username
def is_exception_branch(branch: str) -> bool:
return branch.split("/")[0] in {"main", "nightly", "release", "landchecks"}
def get_workflow_type(issue: Issue, workflow_requestors: Iterable[str]) -> str:
try:
first_comment = issue.get_comments()[0].body.strip("\n\t ")
if first_comment[0] == "!":
log.info("LF Workflows are disabled for everyone. Using meta runners.")
return WORKFLOW_LABEL_META
elif first_comment[0] == "*":
log.info("LF Workflows are enabled for everyone. Using LF runners.")
return WORKFLOW_LABEL_LF
else:
all_opted_in_users = {
usr_raw.strip("\n\t@ ") for usr_raw in first_comment.split()
}
opted_in_requestors = {
usr for usr in workflow_requestors if usr in all_opted_in_users
}
if opted_in_requestors:
log.info(
f"LF Workflows are enabled for {', '.join(opted_in_requestors)}. Using LF runners."
)
return WORKFLOW_LABEL_LF
else:
log.info(
f"LF Workflows are disabled for {', '.join(workflow_requestors)}. Using meta runners."
)
return WORKFLOW_LABEL_META
except Exception as e:
log.error(
f"Failed to get determine workflow type. Falling back to meta runners. Exception: {e}"
)
return WORKFLOW_LABEL_META
def main() -> None:
args = parse_args()
if args.github_ref_type == "branch" and is_exception_branch(args.github_branch):
log.info(f"Exception branch: '{args.github_branch}', using meta runners")
label_type = WORKFLOW_LABEL_META
else:
try:
gh = get_gh_client(args.github_token)
# The default issue we use - https://github.com/pytorch/test-infra/issues/5132
issue = get_issue(gh, args.github_issue_repo, args.github_issue)
username = get_potential_pr_author(
gh,
args.github_repo,
args.github_actor,
args.github_ref_type,
args.github_branch,
)
label_type = get_workflow_type(
issue,
(
args.github_issue_owner,
username,
),
)
except Exception as e:
log.error(
f"Failed to get issue. Falling back to meta runners. Exception: {e}"
)
label_type = WORKFLOW_LABEL_META
set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, label_type)
if __name__ == "__main__":
main()
EOF
cat runner_determinator.py
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
fetch-depth: 1
submodules: true
- name: Install dependencies
run: python3 -m pip install urllib3==1.26.18 PyGithub==2.3.0
@ -277,14 +44,15 @@ jobs:
id: set-condition
run: |
curr_branch="${{ inputs.curr_branch }}"
curr_ref_type="${{ inputs.curr_ref_type }}"
echo "Current branch is '$curr_branch'"
python3 runner_determinator.py \
output="$(python3 .github/scripts/get_workflow_type.py \
--github-token "$GITHUB_TOKEN" \
--github-issue "$ISSUE_NUMBER" \
--github-branch "$curr_branch" \
--github-actor "$TRIGGERING_ACTOR" \
--github-issue-owner "$ISSUE_OWNER" \
--github-ref-type "$curr_ref_type" \
--github-repo "$GITHUB_REPOSITORY"
--github-user "$USERNAME")"
echo "Output: '${output}'"
WORKFLOW_TYPE=$(echo "${output}" | jq -r '.workflow_type')
echo "workflow-type=$WORKFLOW_TYPE" >> "$GITHUB_OUTPUT"

View File

@ -30,12 +30,6 @@ on:
An option JSON description of what test configs to run later on. This
is moved here from the Linux test workflow so that we can apply filter
logic using test-config labels earlier and skip unnecessary builds
runner:
required: false
type: string
default: "windows.4xlarge.nonephemeral"
description: |
Label of the runner this job should run on.
outputs:
test-matrix:
@ -49,13 +43,10 @@ jobs:
build:
# Don't run on forked repos.
if: github.repository_owner == 'pytorch'
runs-on: ${{ inputs.runner }}
runs-on: [self-hosted, windows.4xlarge.nonephemeral]
timeout-minutes: 240
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
defaults:
run:
shell: bash
steps:
# Duplicated in win-test because this MUST go before a checkout
- name: Enable git symlinks on Windows and disable fsmonitor daemon
@ -98,7 +89,6 @@ jobs:
- name: Parse ref
id: parse-ref
shell: bash
run: python3 .github/scripts/parse_ref.py
- name: Get workflow job id

View File

@ -41,9 +41,6 @@ jobs:
fail-fast: false
runs-on: ${{ matrix.runner }}
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
defaults:
run:
shell: bash
steps:
# Duplicated in win-build because this MUST go before a checkout
- name: Enable git symlinks on Windows and disable fsmonitor daemon
@ -227,7 +224,6 @@ jobs:
- name: Parse ref
id: parse-ref
shell: bash
run: python3 .github/scripts/parse_ref.py
- name: Uninstall PyTorch

View File

@ -14,7 +14,6 @@ on:
- .github/ci_commit_pins/triton.txt
- .ci/docker/ci_commit_pins/triton.txt
- .ci/docker/ci_commit_pins/triton-rocm.txt
- .ci/docker/ci_commit_pins/triton-xpu.txt
pull_request:
paths:
- .github/workflows/build-triton-wheel.yml
@ -22,7 +21,6 @@ on:
- .github/ci_commit_pins/triton.txt
- .ci/docker/ci_commit_pins/triton.txt
- .ci/docker/ci_commit_pins/triton-rocm.txt
- .ci/docker/ci_commit_pins/triton-xpu.txt
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
@ -36,7 +34,7 @@ jobs:
fail-fast: false
matrix:
py_vers: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
device: ["cuda", "rocm", "xpu"]
device: ["cuda", "rocm"]
include:
- device: "rocm"
rocm_version: "6.1"
@ -104,6 +102,11 @@ jobs:
;;
esac
BUILD_ROCM=""
if [[ "$BUILD_DEVICE" == "rocm" ]]; then
BUILD_ROCM="--build-rocm"
fi
RELEASE=""
if [[ "${IS_RELEASE_TAG}" == true ]]; then
RELEASE="--release"
@ -111,13 +114,7 @@ jobs:
docker exec -t "${container_name}" yum install -y zlib-devel zip
docker exec -t "${container_name}" "${PYTHON_EXECUTABLE}" -m pip install -U setuptools==67.4.0
# Triton xpu build use GCC11
if [[ "${BUILD_DEVICE}" == xpu ]]; then
docker exec -t "${container_name}" yum install -y devtoolset-11-gcc-c++
docker exec -t "${container_name}" bash -c "source /opt/rh/devtoolset-11/enable && ${PYTHON_EXECUTABLE} /pytorch/.github/scripts/build_triton_wheel.py --device=$BUILD_DEVICE $RELEASE"
else
docker exec -t "${container_name}" bash -c "${PYTHON_EXECUTABLE} /pytorch/.github/scripts/build_triton_wheel.py --device=$BUILD_DEVICE $RELEASE"
fi
docker exec -t "${container_name}" "${PYTHON_EXECUTABLE}" /pytorch/.github/scripts/build_triton_wheel.py $BUILD_ROCM $RELEASE
docker exec -t "${container_name}" chown -R 1000.1000 /artifacts
- uses: actions/upload-artifact@v3

View File

@ -5,11 +5,6 @@ on:
branches:
- main
- release/*
tags:
# Final Release tags look like: v1.11.0
- v[0-9]+.[0-9]+.[0-9]+
# Release candidate tags look like: v1.11.0-rc1
- v[0-9]+.[0-9]+.[0-9]+-rc[0-9]+
release:
types: [published]
pull_request:
@ -23,8 +18,6 @@ jobs:
# https://github.com/softprops/action-gh-release?tab=readme-ov-file#permissions
permissions:
contents: write
outputs:
pt_release_name: ${{ steps.release_name.outputs.pt_release_name }}
steps:
- uses: malfet/checkout@silent-checkout
with:
@ -56,44 +49,11 @@ jobs:
# Create archive
tar -czf "$PT_RELEASE_FILE" "$PT_RELEASE_NAME"
echo "Created source archive $PT_RELEASE_FILE with content: $(ls -a "$PT_RELEASE_NAME")"
- name: Upload source distribution for release
- name: Upload source distribution
if: ${{ github.event_name == 'release' }}
uses: softprops/action-gh-release@v1
with:
files: ${{env.PT_RELEASE_FILE}}
- name: Upload source distribution to GHA artifacts for release tags
if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && contains(github.ref, 'rc') }}
uses: actions/upload-artifact@v2
with:
name: ${{ env.PT_RELEASE_FILE }}
path: ${{ env.PT_RELEASE_FILE }}
- name: Set output
id: release_name
run: echo "::set-output name=pt_release_name::${{ env.PT_RELEASE_NAME }}.tar.gz"
upload_source_code_to_s3:
if: ${{ github.repository == 'pytorch/pytorch' && github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && contains(github.ref, 'rc') }}
runs-on: linux.2xlarge
environment: sourcecode-upload
name: Upload source code to S3 for release tags
permissions:
id-token: write
needs: release
steps:
- uses: actions/download-artifact@v2
with:
name: ${{ needs.release.outputs.pt_release_name }}
- name: Configure AWS credentials(PyTorch account)
uses: aws-actions/configure-aws-credentials@v3
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_pytorch_source_code_upload_role
aws-region: us-east-1
- uses: seemethere/upload-artifact-s3@v5
with:
s3-bucket: pytorch
s3-prefix: source_code/test
if-no-files-found: warn
path: ${{ needs.release.outputs.pt_release_name }}
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name }}

View File

@ -54,7 +54,6 @@ jobs:
pytorch-linux-focal-py3-clang9-android-ndk-r21e,
pytorch-linux-jammy-py3.8-gcc11,
pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks,
pytorch-linux-jammy-py3.12-halide,
pytorch-linux-jammy-xpu-2024.0-py3,
pytorch-linux-jammy-py3-clang15-asan,
pytorch-linux-focal-py3-clang10-onnx,

View File

@ -54,7 +54,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_8-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cpu-aarch64-test: # Testing
@ -162,7 +162,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_9-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cpu-aarch64-test: # Testing
@ -270,7 +270,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cpu-aarch64-test: # Testing
@ -378,7 +378,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cpu-aarch64-test: # Testing
@ -486,7 +486,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cpu-aarch64-test: # Testing

View File

@ -48,7 +48,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda11_8-test: # Testing
@ -72,48 +72,6 @@ jobs:
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda11_8-split-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu118
GPU_ARCH_VERSION: 11.8
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda11_8-split
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda11_8-split-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_8-cuda11_8-split-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu118
GPU_ARCH_VERSION: 11.8
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda11_8-split
build_environment: linux-binary-manywheel
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -130,7 +88,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-test: # Testing
@ -154,48 +112,6 @@ jobs:
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-split-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu121
GPU_ARCH_VERSION: 12.1
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_1-split
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-split-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_8-cuda12_1-split-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu121
GPU_ARCH_VERSION: 12.1
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_1-split
build_environment: linux-binary-manywheel
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -212,7 +128,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-test: # Testing
@ -235,45 +151,3 @@ jobs:
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-split-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu124
GPU_ARCH_VERSION: 12.4
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4-split
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-split-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_8-cuda12_4-split-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
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: cu124
GPU_ARCH_VERSION: 12.4
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
use_split_build: True
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4-split
build_environment: linux-binary-manywheel
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

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@ -54,7 +54,7 @@ jobs:
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_8-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cpu-s390x-test: # Testing
@ -117,7 +117,7 @@ jobs:
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_9-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cpu-s390x-test: # Testing
@ -180,7 +180,7 @@ jobs:
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_10-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cpu-s390x-test: # Testing
@ -243,7 +243,7 @@ jobs:
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_11-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cpu-s390x-test: # Testing
@ -306,7 +306,7 @@ jobs:
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_12-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cpu-s390x-test: # Testing

View File

@ -46,7 +46,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -165,7 +165,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -284,7 +284,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -403,7 +403,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -522,7 +522,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}

View File

@ -46,7 +46,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -290,7 +290,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -536,7 +536,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -782,7 +782,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1027,7 +1027,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1271,7 +1271,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1517,7 +1517,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1763,7 +1763,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2008,7 +2008,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2252,7 +2252,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2498,7 +2498,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2744,7 +2744,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2989,7 +2989,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3233,7 +3233,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3479,7 +3479,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3725,7 +3725,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3970,7 +3970,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4214,7 +4214,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4460,7 +4460,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4706,7 +4706,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash

View File

@ -28,8 +28,7 @@ jobs:
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_distributed", shard: 1, num_shards: 1, runner: "linux.g5.12xlarge.nvidia.gpu" },
{ config: "inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
@ -96,8 +95,7 @@ jobs:
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_12-gcc9-inductor-test:

View File

@ -56,29 +56,3 @@ jobs:
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-periodic-dynamo-benchmarks-build.outputs.test-matrix }}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [
{ config: "inductor_torchbench_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.gcp.a100" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-test-gcp:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp.outputs.test-matrix }}
use-gha: anything-non-empty-to-use-gha
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}

View File

@ -24,8 +24,7 @@ jobs:
docker-image-name: pytorch-linux-focal-rocm-n-py3
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.2" },
{ config: "inductor", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.2" },
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.2" },
]}
linux-focal-rocm6_1-py3_8-inductor-test:
@ -49,8 +48,7 @@ jobs:
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_distributed", shard: 1, num_shards: 1, runner: "linux.g5.12xlarge.nvidia.gpu" },
{ config: "inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
@ -83,6 +81,32 @@ jobs:
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [
{ config: "inductor_torchbench_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.gcp.a100" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-test-gcp:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build-gcp.outputs.test-matrix }}
use-gha: anything-non-empty-to-use-gha
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_12-gcc9-inductor-build:
name: cuda12.1-py3.12-gcc9-sm86
uses: ./.github/workflows/_linux-build.yml
@ -92,8 +116,7 @@ jobs:
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_12-gcc9-inductor-test:
@ -105,26 +128,6 @@ jobs:
docker-image: ${{ needs.linux-focal-cuda12_1-py3_12-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_12-gcc9-inductor-build.outputs.test-matrix }}
linux-jammy-cpu-py3_12-inductor-halide-build:
name: linux-jammy-cpu-py3.12-gcc11-inductor-halide
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-py3.12-gcc11
docker-image-name: pytorch-linux-jammy-py3.12-halide
test-matrix: |
{ include: [
{ config: "inductor-halide", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
]}
linux-jammy-cpu-py3_12-inductor-halide-test:
name: linux-jammy-cpu-py3.12-gcc11-inductor-halide
uses: ./.github/workflows/_linux-test.yml
needs: linux-jammy-cpu-py3_12-inductor-halide-build
with:
build-environment: linux-jammy-py3.12-gcc11
docker-image: ${{ needs.linux-jammy-cpu-py3_12-inductor-halide-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cpu-py3_12-inductor-halide-build.outputs.test-matrix }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-build:
# Should be synced with the one in inductor-periodic.yml but this only runs inductor_timm
name: cuda12.4-py3.10-gcc9-sm86
@ -172,21 +175,11 @@ jobs:
{ config: "cpu_inductor_timm_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench_freezing", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_huggingface_amp_freezing", shard: 1, num_shards: 1, runner: "linux.16xlarge.spr" },
{ config: "cpu_inductor_timm_amp_freezing", shard: 1, num_shards: 2, runner: "linux.16xlarge.spr" },
{ config: "cpu_inductor_timm_amp_freezing", shard: 2, num_shards: 2, runner: "linux.16xlarge.spr" },
{ config: "cpu_inductor_torchbench_amp_freezing", shard: 1, num_shards: 2, runner: "linux.16xlarge.spr" },
{ config: "cpu_inductor_torchbench_amp_freezing", shard: 2, num_shards: 2, runner: "linux.16xlarge.spr" },
{ config: "dynamic_cpu_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_timm", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_timm", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_aot_inductor_huggingface_freezing", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
{ config: "cpu_aot_inductor_timm_freezing", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_aot_inductor_timm_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_aot_inductor_torchbench_freezing", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_aot_inductor_torchbench_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "inductor_torchbench_cpu_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.24xl.spr-metal" },
]}
secrets:

View File

@ -36,24 +36,33 @@ jobs:
ref: v0.0.2
path: llm-target-determinator
- name: Setup miniconda
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
- name: Setup Conda
uses: conda-incubator/setup-miniconda@v2.1.1
with:
python-version: "3.9"
miniconda-version: "py39_4.12.0"
python-version: 3.9
- name: Install requirements
- name: Install Requirements
shell: bash -l {0}
run: |
set -euxo pipefail
${CONDA_RUN} pip install -r llm-target-determinator/requirements.txt
cd "${GITHUB_WORKSPACE}/codellama"
${CONDA_RUN} pip install -e .
conda create \
--yes \
--quiet \
--name "tdenv" \
"python=3.9"
conda activate tdenv
cd "${GITHUB_WORKSPACE}/llm-target-determinator"
pip install -r requirements.txt
cd ../codellama
pip install -e .
- name: Fetch CodeLlama Checkpoint
shell: bash -l {0}
run: |
set -euxo pipefail
cd "${GITHUB_WORKSPACE}/codellama"
conda activate tdenv
cd codellama/
mkdir "CodeLlama-7b-Python"
aws s3 cp "s3://target-determinator-assets/CodeLlama-7b-Python" "CodeLlama-7b-Python" --recursive --no-progress
@ -66,7 +75,7 @@ jobs:
shell: bash
command: |
set -euxo pipefail
${CONDA_RUN} python -m pip install awscli==1.29.40
python3 -m pip install awscli==1.29.40
cd "${GITHUB_WORKSPACE}"/llm-target-determinator/assets
aws s3 cp "s3://target-determinator-assets/indexes/latest" . --recursive
@ -79,8 +88,9 @@ jobs:
shell: bash -l {0}
run: |
set -euxo pipefail
conda activate tdenv
cd "${GITHUB_WORKSPACE}"/llm-target-determinator
${CONDA_RUN} torchrun \
torchrun \
--standalone \
--nnodes=1 \
--nproc-per-node=1 \

View File

@ -73,6 +73,7 @@ jobs:
{ config: "default", shard: 3, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "deploy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
@ -294,53 +295,3 @@ jobs:
build-environment: linux-focal-rocm6.1-py3.8
docker-image: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.test-matrix }}
linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build:
name: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
with:
use_split_build: true
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build-test:
name: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build
- target-determination
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build.outputs.test-matrix }}
linux-focal-cuda11_8-py3_9-gcc9-experimental-split-build:
name: linux-focal-cuda11.8-py3.9-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
with:
use_split_build: true
build-environment: linux-focal-cuda11.8-py3.9-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [
{ config: "multigpu", shard: 1, num_shards: 1, runner: "linux.g5.12xlarge.nvidia.gpu" },
]}
build-with-debug: false
linux-focal-cuda11_8-py3_9-gcc9-experimental-split-build-test:
name: linux-focal-cuda11.8-py3.9-gcc9-experimental-split-build-test
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda11_8-py3_9-gcc9-experimental-split-build
- target-determination
with:
build-environment: linux-focal-cuda11.8-py3.9-gcc9-experimental-split-build
docker-image: ${{ needs.linux-focal-cuda11_8-py3_9-gcc9-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda11_8-py3_9-gcc9-experimental-split-build.outputs.test-matrix }}

View File

@ -35,33 +35,22 @@ jobs:
id-token: write
contents: read
get-label-type:
name: get-label-type
uses: ./.github/workflows/_runner-determinator.yml
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
linux-jammy-py3_8-gcc11-build:
name: linux-jammy-py3.8-gcc11
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.8-gcc11
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 4, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "docs_test", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "backwards_compat", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "distributed", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "distributed", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
{ config: "docs_test", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "backwards_compat", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "distributed", shard: 1, num_shards: 2, runner: "linux.2xlarge" },
{ config: "distributed", shard: 2, num_shards: 2, runner: "linux.2xlarge" },
]}
linux-jammy-py3_8-gcc11-test:
@ -86,9 +75,7 @@ jobs:
linux-jammy-py3_8-gcc11-no-ops:
name: linux-jammy-py3.8-gcc11-no-ops
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.8-gcc11-no-ops
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
@ -99,9 +86,7 @@ jobs:
linux-jammy-py3_8-gcc11-pch:
name: linux-jammy-py3.8-gcc11-pch
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.8-gcc11-pch
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
@ -113,19 +98,17 @@ jobs:
linux-jammy-py3_10-clang15-asan-build:
name: linux-jammy-py3.10-clang15-asan
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.10-clang15-asan
docker-image-name: pytorch-linux-jammy-py3-clang15-asan
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 2, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 3, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 4, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 5, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 6, num_shards: 6, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 1, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 2, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 3, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 4, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 5, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 6, num_shards: 6, runner: "linux.4xlarge" },
]}
sync-tag: asan-build
@ -145,15 +128,13 @@ jobs:
linux-focal-py3_8-clang10-onnx-build:
name: linux-focal-py3.8-clang10-onnx
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3.8-clang10-onnx
docker-image-name: pytorch-linux-focal-py3-clang10-onnx
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 1, num_shards: 2, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 2, runner: "linux.2xlarge" },
]}
linux-focal-py3_8-clang10-onnx-test:
@ -170,22 +151,19 @@ jobs:
linux-focal-py3_8-clang10-build:
name: linux-focal-py3.8-clang10
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3.8-clang10
docker-image-name: pytorch-linux-focal-py3.8-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 4, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "linux.2xlarge" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
]}
linux-focal-py3_8-clang10-test:
name: linux-focal-py3.8-clang10
@ -201,24 +179,22 @@ jobs:
linux-focal-py3_11-clang10-build:
name: linux-focal-py3.11-clang10
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3.11-clang10
docker-image-name: pytorch-linux-focal-py3.11-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 4, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "linux.2xlarge" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
]}
linux-focal-py3_11-clang10-test:
name: linux-focal-py3.11-clang10
uses: ./.github/workflows/_linux-test.yml
@ -233,20 +209,17 @@ jobs:
linux-focal-py3_12-clang10-build:
name: linux-focal-py3.12-clang10
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3.12-clang10
docker-image-name: pytorch-linux-focal-py3.12-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 4, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "default", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
]}
linux-focal-py3_12-clang10-test:
@ -262,16 +235,14 @@ jobs:
linux-focal-cuda11_8-py3_10-gcc9-build:
name: linux-focal-cuda11.8-py3.10-gcc9
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-cuda11.8-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "distributed", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
]}
linux-focal-cuda11_8-py3_10-gcc9-test:
@ -289,18 +260,17 @@ jobs:
linux-focal-cuda12_1-py3_10-gcc9-build:
name: linux-focal-cuda12.1-py3.10-gcc9
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 1, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "deploy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_10-gcc9-test:
@ -318,9 +288,7 @@ jobs:
linux-jammy-py3-clang12-mobile-build:
name: linux-jammy-py3-clang12-mobile-build
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3-clang12-mobile-build
docker-image-name: pytorch-linux-jammy-py3-clang15-asan
build-generates-artifacts: false
@ -332,9 +300,7 @@ jobs:
linux-jammy-cuda-11_8-cudnn9-py3_8-clang12-build:
name: linux-jammy-cuda11.8-cudnn9-py3.8-clang12
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-cuda11.8-cudnn9-py3.8-clang12
docker-image-name: pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12
test-matrix: |
@ -345,9 +311,7 @@ jobs:
linux-focal-py3-clang9-mobile-custom-build-static:
name: linux-focal-py3-clang9-mobile-custom-build-static
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3-clang9-mobile-custom-build-static
docker-image-name: pytorch-linux-focal-py3-clang9-android-ndk-r21e
build-generates-artifacts: false
@ -359,14 +323,12 @@ jobs:
linux-focal-py3_8-clang9-xla-build:
name: linux-focal-py3_8-clang9-xla
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-py3.8-clang9-xla
docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/xla_base:v1.1-lite
test-matrix: |
{ include: [
{ config: "xla", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.12xlarge" },
{ config: "xla", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
]}
linux-focal-py3_8-clang9-xla-test:
@ -383,59 +345,51 @@ jobs:
if: github.event_name == 'pull_request'
name: win-vs2019-cpu-py3
uses: ./.github/workflows/_win-build.yml
needs: get-label-type
with:
build-environment: win-vs2019-cpu-py3
cuda-version: cpu
sync-tag: win-cpu-build
runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 1, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
{ config: "default", shard: 2, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
{ config: "default", shard: 3, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
]}
linux-focal-cpu-py3_10-gcc9-bazel-test:
name: linux-focal-cpu-py3.10-gcc9-bazel-test
uses: ./.github/workflows/_bazel-build-test.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.large"
build-environment: linux-focal-cuda12.1-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
cuda-version: cpu
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "default", shard: 1, num_shards: 1, runner: "linux.4xlarge" },
]}
linux-focal-cuda12_1-py3_10-gcc9-bazel-test:
name: linux-focal-cuda12.1-py3.10-gcc9-bazel-test
uses: ./.github/workflows/_bazel-build-test.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.large"
build-environment: linux-focal-cuda12.1-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
cuda-version: "12.1"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_10-gcc9-bazel-test:
name: linux-focal-cuda12.4-py3.10-gcc9-bazel-test
uses: ./.github/workflows/_bazel-build-test.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.large"
build-environment: linux-focal-cuda12.4-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
cuda-version: "12.4"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-py3-clang9-android-ndk-r21e-gradle-custom-build-single:
@ -463,9 +417,7 @@ jobs:
linux-jammy-py3_8-gcc11-mobile-lightweight-dispatch-build:
name: linux-jammy-py3.8-gcc11-mobile-lightweight-dispatch-build
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.8-gcc111-mobile-lightweight-dispatch-build
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
build-generates-artifacts: false
@ -479,9 +431,7 @@ jobs:
if: github.event_name == 'pull_request'
name: linux-focal-rocm6.1-py3.8
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-rocm6.1-py3.8
docker-image-name: pytorch-linux-focal-rocm-n-py3
sync-tag: rocm-build
@ -495,19 +445,17 @@ jobs:
linux-focal-cuda12_1-py3_10-gcc9-sm86-build:
name: linux-focal-cuda12.1-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 1, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_10-gcc9-sm86-test:
@ -524,14 +472,12 @@ jobs:
linux-jammy-py3-clang12-executorch-build:
name: linux-jammy-py3-clang12-executorch
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3-clang12-executorch
docker-image-name: pytorch-linux-jammy-py3-clang12-executorch
test-matrix: |
{ include: [
{ config: "executorch", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
{ config: "executorch", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
]}
linux-jammy-py3-clang12-executorch-test:
@ -542,59 +488,3 @@ jobs:
build-environment: linux-jammy-py3-clang12-executorch
docker-image: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.test-matrix }}
linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build:
name: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
use_split_build: true
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build-test:
name: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build
- target-determination
with:
timeout-minutes: 360
build-environment: linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-experimental-split-build.outputs.test-matrix }}
linux-focal-py3_12-clang10-experimental-split-build:
name: linux-focal-py3.12-clang10-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
with:
use_split_build: True
build-environment: linux-focal-py3.12-clang10
docker-image-name: pytorch-linux-focal-py3.12-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "default", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "linux.2xlarge" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "linux.2xlarge" },
]}
linux-focal-py3_12-clang10-experimental-split-build-test:
name: linux-focal-py3.12-clang10-experimental-split-build
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-py3_12-clang10-experimental-split-build
with:
build-environment: linux-focal-py3.12-clang10-experimental-split-build
docker-image: ${{ needs.linux-focal-py3_12-clang10-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-py3_12-clang10-experimental-split-build.outputs.test-matrix }}
timeout-minutes: 600

View File

@ -36,15 +36,6 @@ jobs:
id-token: write
contents: read
get-label-type:
name: get-label-type
uses: ./.github/workflows/_runner-determinator.yml
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: ${{ github.ref_type }}
linux-focal-cuda12_1-py3-gcc9-slow-gradcheck-build:
name: linux-focal-cuda12.1-py3-gcc9-slow-gradcheck
uses: ./.github/workflows/_linux-build.yml
@ -106,8 +97,7 @@ jobs:
docker-image-name: pytorch-linux-focal-py3.8-clang10
test-matrix: |
{ include: [
{ config: "slow", shard: 1, num_shards: 2, runner: "linux.2xlarge" },
{ config: "slow", shard: 2, num_shards: 2, runner: "linux.2xlarge" },
{ config: "slow", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
]}
linux-focal-py3_8-clang10-test:
@ -129,8 +119,7 @@ jobs:
docker-image-name: pytorch-linux-focal-rocm-n-py3
test-matrix: |
{ include: [
{ config: "slow", shard: 1, num_shards: 2, runner: "linux.rocm.gpu" },
{ config: "slow", shard: 2, num_shards: 2, runner: "linux.rocm.gpu" },
{ config: "slow", shard: 1, num_shards: 1, runner: "linux.rocm.gpu" },
]}
linux-focal-rocm6_1-py3_8-test:
@ -150,16 +139,14 @@ jobs:
linux-jammy-py3_10-clang15-asan-build:
name: linux-jammy-py3.10-clang15-asan
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-jammy-py3.10-clang15-asan
docker-image-name: pytorch-linux-jammy-py3-clang15-asan
test-matrix: |
{ include: [
{ config: "slow", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "slow", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "slow", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "slow", shard: 1, num_shards: 3, runner: "linux.4xlarge" },
{ config: "slow", shard: 2, num_shards: 3, runner: "linux.4xlarge" },
{ config: "slow", shard: 3, num_shards: 3, runner: "linux.4xlarge" },
]}
sync-tag: asan-build

View File

@ -34,15 +34,6 @@ jobs:
id-token: write
contents: read
get-label-type:
name: get-label-type
uses: ./.github/workflows/_runner-determinator.yml
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: ${{ github.ref_type }}
linux-focal-cuda12_4-py3_10-gcc9-sm86-build:
name: linux-focal-cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-build-label.yml
@ -179,17 +170,15 @@ jobs:
win-vs2019-cpu-py3-build:
name: win-vs2019-cpu-py3
uses: ./.github/workflows/_win-build.yml
needs: get-label-type
with:
build-environment: win-vs2019-cpu-py3
cuda-version: cpu
sync-tag: win-cpu-build
runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
{ config: "default", shard: 1, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
{ config: "default", shard: 2, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
{ config: "default", shard: 3, num_shards: 3, runner: "windows.4xlarge.nonephemeral" },
]}
win-vs2019-cpu-py3-test:
@ -203,21 +192,28 @@ jobs:
cuda-version: cpu
test-matrix: ${{ needs.win-vs2019-cpu-py3-build.outputs.test-matrix }}
win-vs2019-cuda12_1-py3-build:
name: win-vs2019-cuda12.1-py3
win-vs2019-cuda11_8-py3-build:
name: win-vs2019-cuda11.8-py3
uses: ./.github/workflows/_win-build.yml
needs: get-label-type
with:
build-environment: win-vs2019-cuda12.1-py3
cuda-version: "12.1"
runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
build-environment: win-vs2019-cuda11.8-py3
cuda-version: "11.8"
sync-tag: win-cuda-build
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 6, num_shards: 6, runner: "windows.g5.4xlarge.nvidia.gpu" },
{ config: "force_on_cpu", shard: 1, num_shards: 1, runner: "windows.4xlarge.nonephemeral" },
]}
linux-focal-rocm6_1-py3_8-build:
name: linux-focal-rocm6.1-py3.8
uses: ./.github/workflows/_linux-build-label.yml
needs: get-label-type
with:
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
build-environment: linux-focal-rocm6.1-py3.8
docker-image-name: pytorch-linux-focal-rocm-n-py3
sync-tag: rocm-build
@ -242,59 +238,3 @@ jobs:
docker-image: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.test-matrix }}
tests-to-include: "test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor distributed/test_c10d_common distributed/test_c10d_nccl"
linux-focal-cuda12_4-py3_10-gcc9-experimental-split-build:
name: linux-focal-cuda12.4-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
with:
use_split_build: true
build-environment: linux-focal-cuda12.4-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 1, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_10-gcc9-experimental-split-build-test:
name: linux-focal-cuda12.4-py3.10-gcc9-experimental-split-build-test
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_4-py3_10-gcc9-experimental-split-build
- target-determination
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-experimental-split-build
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-experimental-split-build.outputs.test-matrix }}
linux-focal-cuda11_8-py3_10-gcc9-experimental-split-build:
name: linux-focal-cuda11.8-py3.10-gcc9-experimental-split-build
uses: ./.github/workflows/_linux-build-label.yml
with:
use_split_build: true
build-environment: linux-focal-cuda11.8-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
]}
linux-focal-cuda11_8-py3_10-gcc9-experimental-split-build-test:
name: linux-focal-cuda11.8-py3.10-gcc9-experimental-split-build-test
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda11_8-py3_10-gcc9-experimental-split-build
- target-determination
with:
timeout-minutes: 360
build-environment: linux-focal-cuda11.8-py3.10-gcc9-experimental-split-build
docker-image: ${{ needs.linux-focal-cuda11_8-py3_10-gcc9-experimental-split-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda11_8-py3_10-gcc9-experimental-split-build.outputs.test-matrix }}

View File

@ -9,8 +9,6 @@ jobs:
name: try_merge_pr_${{ github.event.client_payload.pr_num }}
runs-on: linux.20_04.4x
environment: mergebot
permissions:
id-token: write
env:
GH_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
steps:
@ -45,7 +43,6 @@ jobs:
IGNORE_CURRENT: ${{ github.event.client_payload.ignore_current }}
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
DRCI_BOT_KEY: ${{ secrets.DRCI_BOT_KEY }}
GITHUB_RUN_ID: ${{ github.run_id }}
run: |
set -x
if [ -n "${REBASE}" ]; then
@ -87,22 +84,6 @@ jobs:
set -x
python3 .github/scripts/comment_on_pr.py "${PR_NUM}" "merge"
- name: configure aws credentials
uses: aws-actions/configure-aws-credentials@v3
continue-on-error: true
with:
role-to-assume: arn:aws:iam::308535385114:role/upload_to_ossci_raw_job_status
aws-region: us-east-1
- name: Upload merge record to s3
if: always()
continue-on-error: true
uses: seemethere/upload-artifact-s3@v5
with:
s3-bucket: ossci-raw-job-status
s3-prefix: merges/${{ github.repository }}/${{ github.event.client_payload.pr_num }}/${{ github.event.client_payload.comment_id }}/${{ github.run_id }}
path: merge_record.json
# We want newer merge commands to supercede old ones
concurrency:
group: try-merge-${{ github.event.client_payload.pr_num }}

View File

@ -25,11 +25,12 @@ jobs:
upload-test-stats:
needs: get_workflow_conclusion
if: github.repository_owner == 'pytorch'
if:
github.repository_owner == 'pytorch' &&
(github.event.workflow_run.conclusion == 'success' || github.event.workflow_run.conclusion == 'failure' ||
needs.get_workflow_conclusion.outputs.conclusion == 'success' || needs.get_workflow_conclusion.outputs.conclusion == 'failure')
runs-on: ubuntu-22.04
environment: upload-stats
permissions:
id-token: write
name: Upload test stats for ${{ github.event.workflow_run.id }}, attempt ${{ github.event.workflow_run.run_attempt }}
steps:
- name: Print workflow information
@ -40,13 +41,6 @@ jobs:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
- name: Configure aws credentials
uses: aws-actions/configure-aws-credentials@v3
continue-on-error: true
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_upload-torch-test-stats
aws-region: us-east-1
- uses: actions/setup-python@v4
with:
python-version: '3.11'
@ -58,6 +52,8 @@ jobs:
- name: Upload test artifacts
id: upload-s3
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
WORKFLOW_ARTIFACTS_URL: ${{ github.event.workflow_run.artifacts_url }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
@ -73,6 +69,8 @@ jobs:
- name: Upload test stats
env:
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
WORKFLOW_RUN_ATTEMPT: ${{ github.event.workflow_run.run_attempt }}
@ -86,6 +84,8 @@ jobs:
- name: Analyze disabled tests rerun
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
WORKFLOW_ARTIFACTS_URL: ${{ github.event.workflow_run.artifacts_url }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
@ -99,12 +99,14 @@ jobs:
if: steps.upload-s3.outcome && steps.upload-s3.outcome == 'success' && github.event.workflow_run.name == 'inductor-micro-benchmark'
env:
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
WORKFLOW_RUN_ATTEMPT: ${{ github.event.workflow_run.run_attempt }}
REPO_FULLNAME: ${{ github.event.workflow_run.repository.full_name }}
HEAD_BRANCH: ${{ github.event.workflow_run.head_branch }}
run: |
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection oss_ci_benchmark --rockset-workspace benchmarks --dynamodb-table torchci-oss-ci-benchmark --match-filename "^gpt_fast_benchmark"
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection oss_ci_benchmark --rockset-workspace benchmarks --match-filename "^gpt_fast_benchmark"
check-api-rate:
if: ${{ always() && github.repository_owner == 'pytorch' }}

View File

@ -26,8 +26,6 @@ jobs:
github.event.workflow_run.conclusion == 'failure' || needs.get-conclusion.outputs.conclusion == 'failure'
runs-on: ubuntu-22.04
environment: upload-stats
permissions:
id-token: write
name: Upload dynamo performance stats for ${{ github.event.workflow_run.id }}, attempt ${{ github.event.workflow_run.run_attempt }}
steps:
- name: Checkout PyTorch
@ -36,13 +34,6 @@ jobs:
submodules: false
fetch-depth: 1
- name: Configure aws credentials
uses: aws-actions/configure-aws-credentials@v3
continue-on-error: true
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_upload-torch-test-stats
aws-region: us-east-1
- uses: actions/setup-python@v4
with:
python-version: '3.11'
@ -54,6 +45,8 @@ jobs:
- name: Upload torch dynamo performance stats to S3
id: upload-s3
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
WORKFLOW_ARTIFACTS_URL: ${{ github.event.workflow_run.artifacts_url }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
@ -68,9 +61,11 @@ jobs:
if: steps.upload-s3.outcome && steps.upload-s3.outcome == 'success'
env:
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
WORKFLOW_RUN_ATTEMPT: ${{ github.event.workflow_run.run_attempt }}
REPO_FULLNAME: ${{ github.event.workflow_run.repository.full_name }}
HEAD_BRANCH: ${{ github.event.workflow_run.head_branch }}
run: |
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection torch_dynamo_perf_stats --rockset-workspace inductor --dynamodb-table torchci-dynamo-perf-stats --match-filename "^inductor_"
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection torch_dynamo_perf_stats --rockset-workspace inductor --match-filename "^inductor_"

1
.gitignore vendored
View File

@ -129,7 +129,6 @@ env
scripts/release_notes/*.json
sccache-stats*.json
lint.json
merge_record.json
# These files get copied over on invoking setup.py
torchgen/packaged/*

View File

@ -68,8 +68,6 @@ include_patterns = [
'aten/src/ATen/native/cudnn/*.cpp',
'c10/**/*.h',
'c10/**/*.cpp',
'distributed/c10d/*DMAConnectivity.*',
'distributed/c10d/*SymmetricMemory.*',
'torch/csrc/**/*.h',
'torch/csrc/**/*.hpp',
'torch/csrc/**/*.cpp',
@ -138,7 +136,7 @@ init_command = [
'numpy==1.24.3 ; python_version == "3.8"',
'numpy==1.26.0 ; python_version >= "3.9"',
'expecttest==0.1.6',
'mypy==1.10.0',
'mypy==1.9.0',
'sympy==1.11.1',
'types-requests==2.27.25',
'types-PyYAML==6.0.7',
@ -204,8 +202,6 @@ include_patterns = [
'torch/csrc/*.cpp',
'torch/csrc/**/*.h',
'torch/csrc/**/*.cpp',
'torch/csrc/jit/serialization/*.h',
'torch/csrc/jit/serialization/*.cpp',
]
exclude_patterns = [
# The negative filters below are to exclude files that include onnx_pb.h or
@ -220,6 +216,7 @@ exclude_patterns = [
'c10/util/complex_math.h',
'c10/util/complex_utils.h',
'c10/util/flat_hash_map.h',
'c10/util/Float8*.h',
'c10/util/logging*.h',
'c10/util/hash.h',
'c10/util/strong_type.h',
@ -227,6 +224,7 @@ exclude_patterns = [
'c10/util/win32-headers.h',
'c10/util/*inl.h',
'c10/test/**/*.h',
'aten/src/ATen/core/TensorImpl_test.cpp',
'third_party/**/*',
'torch/csrc/api/**',
'torch/csrc/autograd/generated/**',
@ -234,8 +232,10 @@ exclude_patterns = [
'torch/csrc/dynamo/eval_frame.h',
'torch/csrc/inductor/**/*',
'torch/csrc/jit/**/*',
'torch/csrc/jit/serialization/mobile_bytecode_generated.h',
'torch/csrc/jit/serialization/import_legacy.cpp',
'torch/csrc/jit/serialization/export.cpp',
'torch/csrc/lazy/**/*',
'torch/csrc/mps/**/*',
]
init_command = [
'python3',
@ -999,6 +999,7 @@ command = [
]
exclude_patterns = [
'tools/gen_vulkan_spv.py',
'torch/__init__.py', # Skip this file to format because it's part of the public API
# We don't care too much about files in this directory, don't enforce
# formatting on them
'caffe2/**/*.py',
@ -1098,12 +1099,14 @@ exclude_patterns = [
'test/test_namedtuple_return_api.py',
'test/test_native_functions.py',
'test/test_native_mha.py',
'test/test_nestedtensor.py',
'test/test_nn.py',
'test/test_out_dtype_op.py',
'test/test_overrides.py',
'test/test_prims.py',
'test/test_proxy_tensor.py',
'test/test_pruning_op.py',
'test/test_public_bindings.py',
'test/test_quantization.py',
'test/test_reductions.py',
'test/test_scatter_gather_ops.py',
@ -1129,6 +1132,8 @@ exclude_patterns = [
'test/test_type_promotion.py',
'test/test_unary_ufuncs.py',
'test/test_vulkan.py',
'test/test_xnnpack_integration.py',
'test/torch_np/numpy_test/**/*.py',
'torch/_awaits/__init__.py',
'torch/_custom_op/__init__.py',
'torch/_custom_op/autograd.py',
@ -1189,6 +1194,9 @@ exclude_patterns = [
'torch/_export/serde/upgrade.py',
'torch/_export/trace.py',
'torch/_export/verifier.py',
'torch/_higher_order_ops/__init__.py',
'torch/_higher_order_ops/out_dtype.py',
'torch/_higher_order_ops/wrap.py',
'torch/_vendor/**',
'torch/ao/__init__.py',
'torch/ao/nn/__init__.py',
@ -1385,8 +1393,172 @@ exclude_patterns = [
'torch/contrib/_tensorboard_vis.py',
"torch/cuda/_gpu_trace.py",
'torch/cuda/_memory_viz.py', # mypy: Value of type "object" is not indexable
'torch/distributed/__init__.py',
'torch/distributed/_composable_state.py',
'torch/distributed/_shard/__init__.py',
'torch/distributed/_shard/_utils.py',
'torch/distributed/_shard/api.py',
'torch/distributed/_shard/checkpoint/__init__.py',
'torch/distributed/_shard/common_op_utils.py',
'torch/distributed/_shard/metadata.py',
'torch/distributed/_shard/op_registry_utils.py',
'torch/distributed/_shard/sharded_optim/__init__.py',
'torch/distributed/_shard/sharded_optim/api.py',
'torch/distributed/_shard/sharded_tensor/__init__.py',
'torch/distributed/_shard/sharded_tensor/_ops/__init__.py',
'torch/distributed/_shard/sharded_tensor/_ops/_common.py',
'torch/distributed/_shard/sharded_tensor/_ops/binary_cmp.py',
'torch/distributed/_shard/sharded_tensor/_ops/init.py',
'torch/distributed/_shard/sharded_tensor/_ops/misc_ops.py',
'torch/distributed/_shard/sharded_tensor/_ops/tensor_ops.py',
'torch/distributed/_shard/sharded_tensor/api.py',
'torch/distributed/_shard/sharded_tensor/logger.py',
'torch/distributed/_shard/sharded_tensor/logging_handlers.py',
'torch/distributed/_shard/sharded_tensor/metadata.py',
'torch/distributed/_shard/sharded_tensor/reshard.py',
'torch/distributed/_shard/sharded_tensor/shard.py',
'torch/distributed/_shard/sharded_tensor/utils.py',
'torch/distributed/_shard/sharder.py',
'torch/distributed/_shard/sharding_plan/__init__.py',
'torch/distributed/_shard/sharding_plan/api.py',
'torch/distributed/_shard/sharding_spec/__init__.py',
'torch/distributed/_shard/sharding_spec/_internals.py',
'torch/distributed/_shard/sharding_spec/api.py',
'torch/distributed/_shard/sharding_spec/chunk_sharding_spec.py',
'torch/distributed/_shard/sharding_spec/chunk_sharding_spec_ops/__init__.py',
'torch/distributed/_shard/sharding_spec/chunk_sharding_spec_ops/_common.py',
'torch/distributed/_shard/sharding_spec/chunk_sharding_spec_ops/embedding.py',
'torch/distributed/_shard/sharding_spec/chunk_sharding_spec_ops/embedding_bag.py',
'torch/distributed/_sharded_tensor/__init__.py',
'torch/distributed/_sharding_spec/__init__.py',
'torch/distributed/_tools/__init__.py',
'torch/distributed/_tools/memory_tracker.py',
'torch/distributed/algorithms/__init__.py',
'torch/distributed/algorithms/_checkpoint/__init__.py',
'torch/distributed/algorithms/_checkpoint/checkpoint_wrapper.py',
'torch/distributed/algorithms/_comm_hooks/__init__.py',
'torch/distributed/algorithms/_comm_hooks/default_hooks.py',
'torch/distributed/algorithms/_optimizer_overlap/__init__.py',
'torch/distributed/algorithms/_optimizer_overlap/optimizer_overlap.py',
'torch/distributed/algorithms/_quantization/__init__.py',
'torch/distributed/algorithms/_quantization/quantization.py',
'torch/distributed/algorithms/ddp_comm_hooks/__init__.py',
'torch/distributed/algorithms/ddp_comm_hooks/ddp_zero_hook.py',
'torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py',
'torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py',
'torch/distributed/algorithms/ddp_comm_hooks/mixed_precision_hooks.py',
'torch/distributed/algorithms/ddp_comm_hooks/optimizer_overlap_hooks.py',
'torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py',
'torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py',
'torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py',
'torch/distributed/algorithms/join.py',
'torch/distributed/algorithms/model_averaging/__init__.py',
'torch/distributed/algorithms/model_averaging/averagers.py',
'torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py',
'torch/distributed/algorithms/model_averaging/utils.py',
'torch/distributed/argparse_util.py',
'torch/distributed/autograd/__init__.py',
'torch/distributed/benchmarks/benchmark_ddp_rpc.py',
'torch/distributed/c10d_logger.py',
'torch/distributed/collective_utils.py',
'torch/distributed/constants.py',
'torch/distributed/distributed_c10d.py',
'torch/distributed/elastic/__init__.py',
'torch/distributed/elastic/agent/__init__.py',
'torch/distributed/elastic/agent/server/__init__.py',
'torch/distributed/elastic/agent/server/api.py',
'torch/distributed/elastic/agent/server/local_elastic_agent.py',
'torch/distributed/elastic/events/__init__.py',
'torch/distributed/elastic/events/api.py',
'torch/distributed/elastic/events/handlers.py',
'torch/distributed/elastic/metrics/__init__.py',
'torch/distributed/elastic/metrics/api.py',
'torch/distributed/elastic/multiprocessing/__init__.py',
'torch/distributed/elastic/multiprocessing/api.py',
'torch/distributed/elastic/multiprocessing/errors/__init__.py',
'torch/distributed/elastic/multiprocessing/errors/error_handler.py',
'torch/distributed/elastic/multiprocessing/errors/handlers.py',
'torch/distributed/elastic/multiprocessing/redirects.py',
'torch/distributed/elastic/multiprocessing/tail_log.py',
'torch/distributed/elastic/rendezvous/__init__.py',
'torch/distributed/elastic/rendezvous/api.py',
'torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py',
'torch/distributed/elastic/rendezvous/dynamic_rendezvous.py',
'torch/distributed/elastic/rendezvous/etcd_rendezvous.py',
'torch/distributed/elastic/rendezvous/etcd_rendezvous_backend.py',
'torch/distributed/elastic/rendezvous/etcd_server.py',
'torch/distributed/elastic/rendezvous/etcd_store.py',
'torch/distributed/elastic/rendezvous/registry.py',
'torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py',
'torch/distributed/elastic/rendezvous/utils.py',
'torch/distributed/elastic/timer/__init__.py',
'torch/distributed/elastic/timer/api.py',
'torch/distributed/elastic/timer/file_based_local_timer.py',
'torch/distributed/elastic/timer/local_timer.py',
'torch/distributed/elastic/utils/__init__.py',
'torch/distributed/elastic/utils/api.py',
'torch/distributed/elastic/utils/data/__init__.py',
'torch/distributed/elastic/utils/data/cycling_iterator.py',
'torch/distributed/elastic/utils/data/elastic_distributed_sampler.py',
'torch/distributed/elastic/utils/distributed.py',
'torch/distributed/elastic/utils/log_level.py',
'torch/distributed/elastic/utils/logging.py',
'torch/distributed/elastic/utils/store.py',
'torch/distributed/examples/memory_tracker_example.py',
'torch/distributed/launch.py',
'torch/distributed/launcher/__init__.py',
'torch/distributed/launcher/api.py',
'torch/distributed/logging_handlers.py',
'torch/distributed/nn/__init__.py',
'torch/distributed/nn/api/__init__.py',
'torch/distributed/nn/api/remote_module.py',
'torch/distributed/nn/functional.py',
'torch/distributed/nn/jit/__init__.py',
'torch/distributed/nn/jit/instantiator.py',
'torch/distributed/nn/jit/templates/__init__.py',
'torch/distributed/nn/jit/templates/remote_module_template.py',
'torch/distributed/optim/__init__.py',
'torch/distributed/optim/apply_optimizer_in_backward.py',
'torch/distributed/optim/functional_adadelta.py',
'torch/distributed/optim/functional_adagrad.py',
'torch/distributed/optim/functional_adam.py',
'torch/distributed/optim/functional_adamax.py',
'torch/distributed/optim/functional_adamw.py',
'torch/distributed/optim/functional_rmsprop.py',
'torch/distributed/optim/functional_rprop.py',
'torch/distributed/optim/functional_sgd.py',
'torch/distributed/optim/named_optimizer.py',
'torch/distributed/optim/optimizer.py',
'torch/distributed/optim/post_localSGD_optimizer.py',
'torch/distributed/optim/utils.py',
'torch/distributed/optim/zero_redundancy_optimizer.py',
'torch/distributed/remote_device.py',
'torch/distributed/rendezvous.py',
'torch/distributed/rpc/__init__.py',
'torch/distributed/rpc/_testing/__init__.py',
'torch/distributed/rpc/_testing/faulty_agent_backend_registry.py',
'torch/distributed/rpc/_utils.py',
'torch/distributed/rpc/api.py',
'torch/distributed/rpc/backend_registry.py',
'torch/distributed/rpc/constants.py',
'torch/distributed/rpc/functions.py',
'torch/distributed/rpc/internal.py',
'torch/distributed/rpc/options.py',
'torch/distributed/rpc/rref_proxy.py',
'torch/distributed/rpc/server_process_global_profiler.py',
'torch/distributed/run.py',
'torch/distributed/tensor/__init__.py',
'torch/distributed/tensor/parallel/__init__.py',
'torch/distributed/tensor/parallel/_utils.py',
'torch/distributed/tensor/parallel/_view_with_dim_change.py',
'torch/distributed/tensor/parallel/api.py',
'torch/distributed/tensor/parallel/fsdp.py',
'torch/distributed/tensor/parallel/input_reshard.py',
'torch/distributed/tensor/parallel/multihead_attention_tp.py',
'torch/distributed/tensor/parallel/style.py',
'torch/fft/__init__.py',
'torch/func/__init__.py',
'torch/functional.py',
'torch/futures/__init__.py',
'torch/fx/__init__.py',
'torch/fx/_compatibility.py',
@ -1472,9 +1644,20 @@ exclude_patterns = [
'torch/fx/subgraph_rewriter.py',
'torch/fx/tensor_type.py',
'torch/fx/traceback.py',
'torch/hub.py',
'torch/library.py',
'torch/linalg/__init__.py',
'torch/monitor/__init__.py',
'torch/nested/__init__.py',
'torch/nn/__init__.py',
'torch/nn/_reduction.py',
'torch/nn/backends/__init__.py',
'torch/nn/backends/thnn.py',
'torch/nn/common_types.py',
'torch/nn/cpp.py',
'torch/nn/functional.py',
'torch/nn/grad.py',
'torch/nn/init.py',
'torch/nn/intrinsic/__init__.py',
'torch/nn/intrinsic/modules/__init__.py',
'torch/nn/intrinsic/modules/fused.py',
@ -1491,6 +1674,40 @@ exclude_patterns = [
'torch/nn/intrinsic/quantized/modules/bn_relu.py',
'torch/nn/intrinsic/quantized/modules/conv_relu.py',
'torch/nn/intrinsic/quantized/modules/linear_relu.py',
'torch/nn/modules/__init__.py',
'torch/nn/modules/_functions.py',
'torch/nn/modules/activation.py',
'torch/nn/modules/adaptive.py',
'torch/nn/modules/batchnorm.py',
'torch/nn/modules/channelshuffle.py',
'torch/nn/modules/container.py',
'torch/nn/modules/conv.py',
'torch/nn/modules/distance.py',
'torch/nn/modules/dropout.py',
'torch/nn/modules/flatten.py',
'torch/nn/modules/fold.py',
'torch/nn/modules/instancenorm.py',
'torch/nn/modules/lazy.py',
'torch/nn/modules/linear.py',
'torch/nn/modules/loss.py',
'torch/nn/modules/module.py',
'torch/nn/modules/normalization.py',
'torch/nn/modules/padding.py',
'torch/nn/modules/pixelshuffle.py',
'torch/nn/modules/pooling.py',
'torch/nn/modules/rnn.py',
'torch/nn/modules/sparse.py',
'torch/nn/modules/transformer.py',
'torch/nn/modules/upsampling.py',
'torch/nn/modules/utils.py',
'torch/nn/parallel/__init__.py',
'torch/nn/parallel/_functions.py',
'torch/nn/parallel/comm.py',
'torch/nn/parallel/data_parallel.py',
'torch/nn/parallel/parallel_apply.py',
'torch/nn/parallel/replicate.py',
'torch/nn/parallel/scatter_gather.py',
'torch/nn/parameter.py',
'torch/nn/qat/__init__.py',
'torch/nn/qat/dynamic/__init__.py',
'torch/nn/qat/dynamic/modules/__init__.py',
@ -1528,10 +1745,44 @@ exclude_patterns = [
'torch/nn/quantized/modules/normalization.py',
'torch/nn/quantized/modules/rnn.py',
'torch/nn/quantized/modules/utils.py',
'torch/nn/utils/__init__.py',
'torch/nn/utils/_deprecation_utils.py',
'torch/nn/utils/_expanded_weights/__init__.py',
'torch/nn/utils/_expanded_weights/conv_expanded_weights.py',
'torch/nn/utils/_expanded_weights/conv_utils.py',
'torch/nn/utils/_expanded_weights/embedding_expanded_weights.py',
'torch/nn/utils/_expanded_weights/expanded_weights_impl.py',
'torch/nn/utils/_expanded_weights/expanded_weights_utils.py',
'torch/nn/utils/_expanded_weights/group_norm_expanded_weights.py',
'torch/nn/utils/_expanded_weights/instance_norm_expanded_weights.py',
'torch/nn/utils/_expanded_weights/layer_norm_expanded_weights.py',
'torch/nn/utils/_expanded_weights/linear_expanded_weights.py',
'torch/nn/utils/_per_sample_grad.py',
'torch/nn/utils/clip_grad.py',
'torch/nn/utils/convert_parameters.py',
'torch/nn/utils/fusion.py',
'torch/nn/utils/init.py',
'torch/nn/utils/memory_format.py',
'torch/nn/utils/parametrizations.py',
'torch/nn/utils/parametrize.py',
'torch/nn/utils/prune.py',
'torch/nn/utils/rnn.py',
'torch/nn/utils/spectral_norm.py',
'torch/nn/utils/weight_norm.py',
'torch/overrides.py',
'torch/quasirandom.py',
'torch/random.py',
'torch/return_types.py',
'torch/serialization.py',
'torch/signal/__init__.py',
'torch/signal/windows/__init__.py',
'torch/signal/windows/windows.py',
'torch/sparse/__init__.py',
'torch/sparse/_semi_structured_conversions.py',
'torch/sparse/_triton_ops.py',
'torch/sparse/semi_structured.py',
'torch/special/__init__.py',
'torch/storage.py',
'torch/testing/_internal/__init__.py',
'torch/testing/_internal/autocast_test_lists.py',
'torch/testing/_internal/autograd_function_db.py',
@ -1539,7 +1790,9 @@ exclude_patterns = [
'torch/testing/_internal/codegen/__init__.py',
'torch/testing/_internal/codegen/random_topo_test.py',
'torch/testing/_internal/common_cuda.py',
'torch/testing/_internal/common_device_type.py',
'torch/testing/_internal/common_distributed.py',
'torch/testing/_internal/common_dtype.py',
'torch/testing/_internal/common_jit.py',
'torch/testing/_internal/common_methods_invocations.py',
'torch/testing/_internal/common_modules.py',
@ -1604,6 +1857,7 @@ exclude_patterns = [
'torch/testing/_internal/test_module/__init__.py',
'torch/testing/_internal/test_module/future_div.py',
'torch/testing/_internal/test_module/no_future_div.py',
'torch/utils/__init__.py',
'torch/utils/_contextlib.py',
'torch/utils/_cpp_extension_versioner.py',
'torch/utils/_crash_handler.py',
@ -1654,6 +1908,53 @@ exclude_patterns = [
'torch/utils/collect_env.py',
'torch/utils/cpp_backtrace.py',
'torch/utils/cpp_extension.py',
'torch/utils/data/__init__.py',
'torch/utils/data/_utils/__init__.py',
'torch/utils/data/_utils/collate.py',
'torch/utils/data/_utils/fetch.py',
'torch/utils/data/_utils/pin_memory.py',
'torch/utils/data/_utils/serialization.py',
'torch/utils/data/_utils/signal_handling.py',
'torch/utils/data/_utils/worker.py',
'torch/utils/data/backward_compatibility.py',
'torch/utils/data/dataloader.py',
'torch/utils/data/datapipes/__init__.py',
'torch/utils/data/datapipes/_decorator.py',
'torch/utils/data/datapipes/_hook_iterator.py',
'torch/utils/data/datapipes/_typing.py',
'torch/utils/data/datapipes/dataframe/__init__.py',
'torch/utils/data/datapipes/dataframe/dataframe_wrapper.py',
'torch/utils/data/datapipes/dataframe/dataframes.py',
'torch/utils/data/datapipes/dataframe/datapipes.py',
'torch/utils/data/datapipes/dataframe/structures.py',
'torch/utils/data/datapipes/datapipe.py',
'torch/utils/data/datapipes/gen_pyi.py',
'torch/utils/data/datapipes/iter/__init__.py',
'torch/utils/data/datapipes/iter/callable.py',
'torch/utils/data/datapipes/iter/combinatorics.py',
'torch/utils/data/datapipes/iter/combining.py',
'torch/utils/data/datapipes/iter/filelister.py',
'torch/utils/data/datapipes/iter/fileopener.py',
'torch/utils/data/datapipes/iter/grouping.py',
'torch/utils/data/datapipes/iter/routeddecoder.py',
'torch/utils/data/datapipes/iter/selecting.py',
'torch/utils/data/datapipes/iter/sharding.py',
'torch/utils/data/datapipes/iter/streamreader.py',
'torch/utils/data/datapipes/iter/utils.py',
'torch/utils/data/datapipes/map/__init__.py',
'torch/utils/data/datapipes/map/callable.py',
'torch/utils/data/datapipes/map/combinatorics.py',
'torch/utils/data/datapipes/map/combining.py',
'torch/utils/data/datapipes/map/grouping.py',
'torch/utils/data/datapipes/map/utils.py',
'torch/utils/data/datapipes/utils/__init__.py',
'torch/utils/data/datapipes/utils/common.py',
'torch/utils/data/datapipes/utils/decoder.py',
'torch/utils/data/datapipes/utils/snapshot.py',
'torch/utils/data/distributed.py',
'torch/utils/data/graph.py',
'torch/utils/data/graph_settings.py',
'torch/utils/data/sampler.py',
'torch/utils/dlpack.py',
'torch/utils/file_baton.py',
'torch/utils/flop_counter.py',
@ -1693,9 +1994,8 @@ init_command = [
'--dry-run={{DRYRUN}}',
'--no-black-binary',
'black==23.12.1',
'ufmt==2.7.0',
'usort==1.0.8.post1',
'isort==5.13.2',
'ufmt==2.1.0',
'usort==1.0.6',
]
is_formatter = true
@ -1779,7 +2079,7 @@ init_command = [
'python3',
'tools/linter/adapters/pip_init.py',
'--dry-run={{DRYRUN}}',
'ruff==0.5.0',
'ruff==0.4.8',
]
is_formatter = true

View File

@ -461,7 +461,15 @@ filegroup(
filegroup(
name = "caffe2_perfkernels_srcs",
srcs = [
"caffe2/perfkernels/adagrad.cc",
"caffe2/perfkernels/embedding_lookup.cc",
"caffe2/perfkernels/embedding_lookup_idx.cc",
"caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup.cc",
"caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup_idx.cc",
"caffe2/perfkernels/fused_nbit_rowwise_conversion.cc",
"caffe2/perfkernels/lstm_unit_cpu_common.cc",
"caffe2/perfkernels/math_cpu_base.cc",
"caffe2/perfkernels/typed_axpy.cc",
],
)
@ -498,6 +506,7 @@ cc_library(
hdrs = [
"caffe2/core/common.h",
"caffe2/perfkernels/common.h",
"caffe2/perfkernels/embedding_lookup.h",
"caffe2/perfkernels/embedding_lookup_idx.h",
"caffe2/utils/fixed_divisor.h",
] + glob([
@ -744,7 +753,6 @@ cc_library(
"torch/csrc/cuda/python_nccl.cpp",
"torch/csrc/cuda/nccl.cpp",
"torch/csrc/distributed/c10d/intra_node_comm.cu",
"torch/csrc/distributed/c10d/CUDASymmetricMemory.cu",
"torch/csrc/distributed/c10d/Utils.cu",
"torch/csrc/distributed/c10d/quantization/quantization_gpu.cu",
],
@ -762,7 +770,6 @@ cc_library(
":torch_headers",
"@kineto",
"@cpp-httplib",
"@nlohmann",
] + if_cuda([
"@cuda//:nvToolsExt",
"@cutlass",

View File

@ -208,6 +208,7 @@ endif()
include(CMakeDependentOption)
option(ATEN_NO_TEST "Do not build ATen test binaries" OFF)
option(BUILD_BINARY "Build C++ binaries" OFF)
option(BUILD_DOCS "Build Caffe2 documentation" OFF)
option(BUILD_CUSTOM_PROTOBUF
"Build and use Caffe2's own protobuf under third_party" ON)
option(BUILD_PYTHON "Build Python binaries" ON)
@ -749,6 +750,7 @@ if(NOT TORCH_BUILD_VERSION)
CACHE STRING "Torch build version" FORCE)
endif()
caffe2_parse_version_str(TORCH ${TORCH_BUILD_VERSION})
caffe2_parse_version_str(CAFFE2 ${TORCH_BUILD_VERSION})
set(TORCH_SOVERSION "${TORCH_VERSION_MAJOR}.${TORCH_VERSION_MINOR}")
# ---[ CMake scripts + modules
@ -1221,6 +1223,45 @@ endif()
add_subdirectory(c10)
add_subdirectory(caffe2)
# --[ Documentation
if(BUILD_DOCS)
# check if Doxygen is installed
find_package(Doxygen)
if(DOXYGEN_FOUND)
message("Generating documentation")
set(DOXYGEN_C_IN ${CMAKE_CURRENT_SOURCE_DIR}/docs/caffe2/.Doxyfile-c)
set(DOXYGEN_C_OUT ${CMAKE_CURRENT_SOURCE_DIR}/docs/caffe2/Doxyfile-c)
set(DOXYGEN_P_IN ${CMAKE_CURRENT_SOURCE_DIR}/docs/caffe2/.Doxyfile-python)
set(DOXYGEN_P_OUT ${CMAKE_CURRENT_SOURCE_DIR}/docs/caffe2/Doxyfile-python)
if(EXISTS ${CMAKE_CURRENT_BINARY_DIR}/docs)
file(REMOVE_RECURSE ${CMAKE_CURRENT_BINARY_DIR}/docs)
endif()
file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/docs)
configure_file(${DOXYGEN_C_IN} ${DOXYGEN_C_OUT} @ONLY)
configure_file(${DOXYGEN_P_IN} ${DOXYGEN_P_OUT} @ONLY)
add_custom_target(
doc_doxygen_c ALL
COMMAND ${DOXYGEN_EXECUTABLE} ${DOXYGEN_C_OUT}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
COMMENT "Generating C++ API documentation with Doxygen"
VERBATIM)
add_custom_target(
doc_doxygen_python ALL
COMMAND ${DOXYGEN_EXECUTABLE} ${DOXYGEN_P_OUT}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
COMMENT "Generating Python API documentation with Doxygen"
VERBATIM)
else()
message(
FATAL_ERROR "Doxygen needs to be installed to generate the documentation")
endif()
endif()
# ---[ CMake related files Uninistall option.
if(NOT TARGET caffe2_uninstall)
configure_file(

View File

@ -43,12 +43,12 @@ nn/qat/ @jerryzh168
/torch/csrc/distributed/rpc/tensorpipe_agent.h @jiayisuse @osalpekar @lw
# ONNX Export
/torch/_dynamo/backends/onnxrt.py @wschin @xadupre
/torch/csrc/jit/passes/onnx.h @titaiwangms @shubhambhokare1 @xadupre
/torch/csrc/jit/passes/onnx.cpp @titaiwangms @shubhambhokare1 @xadupre
/torch/csrc/jit/passes/onnx/ @titaiwangms @shubhambhokare1 @xadupre
/torch/onnx/ @titaiwangms @shubhambhokare1 @justinchuby @wschin @xadupre
/test/onnx/ @titaiwangms @shubhambhokare1 @justinchuby @wschin @xadupre
/torch/_dynamo/backends/onnxrt.py @bowenbao @thiagocrepaldi @wschin
/torch/csrc/jit/passes/onnx.h @bowenbao @thiagocrepaldi
/torch/csrc/jit/passes/onnx.cpp @bowenbao @thiagocrepaldi
/torch/csrc/jit/passes/onnx/ @bowenbao @thiagocrepaldi
/torch/onnx/ @bowenbao @thiagocrepaldi @wschin
/test/onnx/ @bowenbao @thiagocrepaldi @wschin
# CI
/.ci @pytorch/pytorch-dev-infra
@ -57,7 +57,6 @@ nn/qat/ @jerryzh168
/.ci/docker/ @jeffdaily
/.ci/docker/ci_commit_pins/triton.txt @desertfire @Chillee @eellison @shunting314 @bertmaher @jeffdaily @jataylo @jithunnair-amd @pruthvistony
/.ci/docker/ci_commit_pins/triton-rocm.txt @jeffdaily @jataylo @jithunnair-amd @pruthvistony
/.ci/docker/ci_commit_pins/triton-xpu.txt @EikanWang @gujinghui
# Github Actions
# This list is for people wanting to be notified every time there's a change
@ -108,10 +107,10 @@ aten/src/ATen/detail/MTIAHooksInterface.h @egienvalue
torch/csrc/mtia/ @egienvalue
# Profiler
torch/csrc/autograd/profiler* @aaronenyeshi @sraikund16
torch/autograd/profiler* @aaronenyeshi @sraikund16
torch/csrc/profiler/ @aaronenyeshi @sraikund16
torch/profiler/ @aaronenyeshi @sraikund16
torch/csrc/autograd/profiler* @aaronenyeshi
torch/autograd/profiler* @aaronenyeshi
torch/csrc/profiler/ @aaronenyeshi
torch/profiler/ @aaronenyeshi
# AOTDispatch tests
test/functorch/test_aotdispatch.py @ezyang @Chillee
@ -133,15 +132,6 @@ caffe2/operators/hip @jeffdaily @jithunnair-amd
caffe2/operators/rnn/hip @jeffdaily @jithunnair-amd
caffe2/utils/hip @jeffdaily @jithunnair-amd
# XPU-specific files
/aten/src/ATen/xpu/ @EikanWang @gujinghui
/c10/xpu/ @EikanWang @gujinghui
/torch/csrc/xpu/ @EikanWang @gujinghui
/torch/xpu/ @EikanWang @gujinghui
/test/xpu/ @EikanWang @gujinghui
/test/test_xpu.py @EikanWang @gujinghui
/third_party/xpu.txt @EikanWang @gujinghui
# torch.export
/torch/export/ @avikchaudhuri @gmagogsfm @tugsbayasgalan @zhxchen17
/torch/_export/ @avikchaudhuri @gmagogsfm @tugsbayasgalan @zhxchen17

View File

@ -77,11 +77,6 @@ RUN case ${TARGETPLATFORM} in \
esac && \
/opt/conda/bin/conda clean -ya
RUN /opt/conda/bin/pip install torchelastic
RUN IS_CUDA=$(python -c 'import torch ; print(torch.cuda._is_compiled())'); \
echo "Is torch compiled with cuda: ${IS_CUDA}"; \
if test "${IS_CUDA}" != "True" -a ! -z "${CUDA_VERSION}"; then \
exit 1; \
fi
FROM ${BASE_IMAGE} as official
ARG PYTORCH_VERSION

View File

@ -51,7 +51,6 @@ Following is the Release Compatibility Matrix for PyTorch releases:
| PyTorch version | Python | Stable CUDA | Experimental CUDA | Stable ROCm |
| --- | --- | --- | --- | --- |
| 2.4 | >=3.8, <=3.12 | CUDA 11.8, CUDA 12.1, CUDNN 9.1.0.70 | CUDA 12.4, CUDNN 9.1.0.70 | ROCm 6.1 |
| 2.3 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 6.0 |
| 2.2 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 5.7 |
| 2.1 | >=3.8, <=3.11 | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 5.6 |
@ -61,19 +60,15 @@ Following is the Release Compatibility Matrix for PyTorch releases:
## Release Cadence
Following is the release cadence for year 2023/2024. All dates below are tentative, for latest updates on the release scheduled please follow [dev discuss](https://dev-discuss.pytorch.org/c/release-announcements/27). Please note: Patch Releases are optional.
Following is the release cadence for year 2023/2024. All dates below are tentative, for latest updates on the release scheduled please follow [dev discuss](https://dev-discuss.pytorch.org/c/release-announcements/27).
| Minor Version | Release branch cut | Release date | First patch release date | Second patch release date|
| --- | --- | --- | --- | --- |
| 2.1 | Aug 2023 | Oct 2023 | Nov 2023 | Dec 2023 |
| 2.2 | Dec 2023 | Jan 2024 | Feb 2024 | Mar 2024 |
| 2.3 | Mar 2024 | Apr 2024 | Jun 2024 | Not planned |
| 2.4 | Jun 2024 | Jul 2024 | (Sept 2024) | Not planned |
| 2.5 | Aug 2024 | Oct 2024 | (Nov 2024) | (Dec 2024) |
| 2.6 | Dec 2024 | Jan 2025 | (Feb 2025) | (Mar 2025) |
| 2.7 | Mar 2025 | Apr 2025 | (May 2025) | (Jun 2025) |
| 2.8 | Jun 2025 | Jul 2025 | (Aug 2025) | (Sept 2025) |
| 2.9 | Aug 2025 | Oct 2025 | (Nov 2025) | (Dec 2025) |
| 2.4 | Jun 2024 | Jul 2024 | Aug 2024 | Sep 2024 |
| 2.5 | Aug 2024 | Oct 2024 | Nov 2024 | Dec 2024 |
## General Overview
@ -295,7 +290,7 @@ After the final RC is created. The following tasks should be performed :
* Create validation issue for the release, see for example [Validations for 2.1.2 release](https://github.com/pytorch/pytorch/issues/114904) and perform required validations.
* Run performance tests in [benchmark repository](https://github.com/pytorch/benchmark). Make sure there are no performance regressions.
* Run performance tests in [benchmark repository](https://github.com/pytorch/benchmark). Make sure there are no prerformance regressions.
* Prepare and stage PyPI binaries for promotion. This is done with this script:
[`pytorch/builder:release/pypi/promote_pypi_to_staging.sh`](https://github.com/pytorch/builder/blob/main/release/pypi/promote_pypi_to_staging.sh)
@ -434,12 +429,12 @@ need to support these particular versions of software.
## Operating Systems
Supported OS flavors are summarized in the table below:
| Operating System family | Architecture | Notes |
| Operating System family | Architectrue | Notes |
| --- | --- | --- |
| Linux | aarch64, x86_64 | Wheels are manylinux2014 compatible, i.e. they should be runnable on any Linux system with glibc-2.17 or above. |
| MacOS | arm64 | Builds should be compatible with MacOS 11 (Big Sur) or newer, but are actively tested against MacOS 14 (Sonoma). |
| MacOS | x86_64 | Requires MacOS Catalina or above, not supported after 2.2, see https://github.com/pytorch/pytorch/issues/114602 |
| Windows | x86_64 | Builds are compatible with Windows-10 or newer. |
| Windows | x86_64 | Buils are compatible with Windows-10 or newer. |
# Submitting Tutorials

View File

@ -6,7 +6,7 @@
- [Untrusted inputs](#untrusted-inputs)
- [Data privacy](#data-privacy)
- [Using distributed features](#using-distributed-features)
- [**CI/CD security principles**](#cicd-security-principles)
## Reporting Security Issues
Beware that none of the topics under [Using Pytorch Securely](#using-pytorch-securely) are considered vulnerabilities of Pytorch.
@ -61,27 +61,3 @@ If applicable, prepare your model against bad inputs and prompt injections. Some
PyTorch can be used for distributed computing, and as such there is a `torch.distributed` package. PyTorch Distributed features are intended for internal communication only. They are not built for use in untrusted environments or networks.
For performance reasons, none of the PyTorch Distributed primitives (including c10d, RPC, and TCPStore) include any authorization protocol and will send messages unencrypted. They accept connections from anywhere, and execute the workload sent without performing any checks. Therefore, if you run a PyTorch Distributed program on your network, anybody with access to the network can execute arbitrary code with the privileges of the user running PyTorch.
## CI/CD security principles
_Audience_: Contributors and reviewers, especially if modifying the workflow files/build system.
PyTorch CI/CD security philosophy is based on finding a balance between open and transparent CI pipelines while keeping the environment efficient and safe.
PyTorch testing requirements are complex, and a large part of the code base can only be tested on specialized powerful hardware, such as GPU, making it a lucrative target for resource misuse. To prevent this, we require workflow run approval for PRs from non-member contributors. To keep the volume of those approvals relatively low, we easily extend write permissions to the repository to regular contributors.
More widespread write access to the repo presents challenges when it comes to reviewing changes, merging code into trunk, and creating releases. [Protected branches](https://docs.github.com/en/repositories/configuring-branches-and-merges-in-your-repository/managing-protected-branches/about-protected-branches) are used to restrict the ability to merge to the trunk/release branches only to the repository administrators and merge bot. The merge bot is responsible for mechanistically merging the change and validating reviews against the path-based rules defined in [merge_rules.yml](https://github.com/pytorch/pytorch/blob/main/.github/merge_rules.yaml). Once a PR has been reviewed by person(s) mentioned in these rules, leaving a `@pytorchbot merge` comment on the PR will initiate the merge process. To protect merge bot credentials from leaking, merge actions must be executed only on ephemeral runners (see definition below) using a specialized deployment environment.
To speed up the CI system, build steps of the workflow rely on the distributed caching mechanism backed by [sccache](https://github.com/mozilla/sccache), making them susceptible to cache corruption compromises. For that reason binary artifacts generated during CI should not be executed in an environment that contains an access to any sensitive/non-public information and should not be published for use by general audience. One should not have any expectation about the lifetime of those artifacts, although in practice they likely remain accessible for about two weeks after the PR has been closed.
To speed up CI system setup, PyTorch relies heavily on Docker to pre-build and pre-install the dependencies. To prevent a potentially malicious PR from altering ones that were published in the past, ECR has been configured to use immutable tags.
To improve runner availability and more efficient resource utilization, some of the CI runners are non-ephemeral, i.e., workflow steps from completely unrelated PRs could be scheduled sequentially on the same runner, making them susceptible to reverse shell attacks. For that reason, PyTorch does not rely on the repository secrets mechanism, as these can easily be compromised in such attacks.
### Release pipelines security
To ensure safe binary releases, PyTorch release pipelines are built on the following principles:
- All binary builds/upload jobs must be run on ephemeral runners, i.e., on a machine that is allocated from the cloud to do the build and released back to the cloud after the build is finished. This protects those builds from interference from external actors, who potentially can get reverse shell access to a non-ephemeral runner and wait there for a binary build.
- All binary builds are cold-start builds, i.e., distributed caching/incremental builds are not permitted. This renders builds much slower than incremental CI builds but isolates them from potential compromises of the intermediate artifacts caching systems.
- All upload jobs are executed in a [deployment environments](https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment) that are restricted to protected branches
- Security credentials needed to upload binaries to PyPI/conda or stable indexes `download.pytorch.org/whl` are never uploaded to repo secrets storage/environment. This requires an extra manual step to publish the release but ensures that access to those would not be compromised by deliberate/accidental leaks of secrets stored in the cloud.
- No binary artifacts should be published to GitHub releases pages, as these are overwritable by anyone with write permission to the repo.

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@ -174,12 +174,6 @@ new_local_repository(
path = "third_party/cpp-httplib",
)
new_local_repository(
name = "nlohmann",
build_file = "//third_party:nlohmann.BUILD",
path = "third_party/nlohmann",
)
new_local_repository(
name = "tensorpipe",
build_file = "//third_party:tensorpipe.BUILD",

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@ -119,7 +119,7 @@ class PytorchJni : public facebook::jni::HybridClass<PytorchJni> {
}
deviceType_ = deviceJniCodeToDeviceType(device);
module_ = torch::jit::load(
std::move(modelPath->toStdString()), std::nullopt, extra_files);
std::move(modelPath->toStdString()), c10::nullopt, extra_files);
if (has_extra) {
static auto putMethod =
facebook::jni::JMap<facebook::jni::JString, facebook::jni::JString>::

View File

@ -84,9 +84,9 @@ class PytorchJni : public facebook::jni::HybridClass<PytorchJni> {
}
deviceType_ = deviceJniCodeToDeviceType(device);
module_ = torch::jit::_load_for_mobile(
std::move(modelPath->toStdString()), std::nullopt, extra_files);
std::move(modelPath->toStdString()), c10::nullopt, extra_files);
torch::jit::_load_extra_only_for_mobile(
std::move(modelPath->toStdString()), std::nullopt, extra_files);
std::move(modelPath->toStdString()), c10::nullopt, extra_files);
if (has_extra) {
static auto putMethod =
facebook::jni::JMap<facebook::jni::JString, facebook::jni::JString>::

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@ -53,6 +53,11 @@ if(NOT BUILD_LITE_INTERPRETER)
file(GLOB_RECURSE ATen_CORE_TEST_SRCS "core/*_test.cpp")
endif()
EXCLUDE(ATen_CORE_SRCS "${ATen_CORE_SRCS}" ${ATen_CORE_TEST_SRCS})
# Exclude TensorImpl_test.cpp if compiling without Caffe2
if(NOT BUILD_LITE_INTERPRETER)
file(GLOB_RECURSE ATen_CORE_EXCLUDED_TEST_SRCS "core/TensorImpl_test.cpp")
EXCLUDE(ATen_CORE_TEST_SRCS "${ATen_CORE_TEST_SRCS}" ${ATen_CORE_EXCLUDED_TEST_SRCS})
endif()
file(GLOB base_h "*.h" "detail/*.h" "cpu/*.h" "cpu/vec/vec512/*.h" "cpu/vec/vec256/*.h" "cpu/vec/vec256/vsx/*.h" "cpu/vec/vec256/zarch/*.h" "cpu/vec/*.h" "quantized/*.h" "functorch/*.h")
file(GLOB base_cpp "*.cpp" "detail/*.cpp" "cpu/*.cpp" "functorch/*.cpp")
@ -468,7 +473,6 @@ endif()
if(USE_CUDA AND NOT USE_ROCM)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/cutlass/include)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/cutlass/tools/util/include)
if($ENV{ATEN_STATIC_CUDA})
list(APPEND ATen_CUDA_DEPENDENCY_LIBS
${CUDA_LIBRARIES}

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@ -222,7 +222,7 @@ c10::intrusive_ptr<c10::TensorImpl> CPUGeneratorImpl::get_state() const {
static const size_t size = sizeof(CPUGeneratorImplState);
static_assert(std::is_standard_layout_v<CPUGeneratorImplState>, "CPUGeneratorImplState is not a PODType");
auto state_tensor = at::detail::empty_cpu({(int64_t)size}, ScalarType::Byte, std::nullopt, std::nullopt, std::nullopt, std::nullopt);
auto state_tensor = at::detail::empty_cpu({(int64_t)size}, ScalarType::Byte, c10::nullopt, c10::nullopt, c10::nullopt, c10::nullopt);
auto rng_state = state_tensor.data_ptr();
// accumulate generator data to be copied into byte tensor

View File

@ -3,7 +3,7 @@
#include <ATen/core/Generator.h>
#include <ATen/core/MT19937RNGEngine.h>
#include <c10/core/GeneratorImpl.h>
#include <optional>
#include <c10/util/Optional.h>
namespace at {

View File

@ -56,14 +56,6 @@ void Context::setDeterministicCuDNN(bool b) {
deterministic_cudnn = b;
}
bool Context::deterministicMkldnn() const {
return deterministic_mkldnn;
}
void Context::setDeterministicMkldnn(bool b) {
deterministic_mkldnn = b;
}
bool Context::deterministicAlgorithms() const {
return _deterministic_algorithms;
}
@ -153,13 +145,6 @@ void Context::setSDPUseCuDNN(bool e) {
enabled_cudnnSDP = e;
}
void Context::setSDPUseOverrideable(bool e) {
enabled_overrideable = e;
}
bool Context::userEnabledOverrideableSDP() const {
return enabled_overrideable;
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
static const char cublas_config_var_name[] = "CUBLAS_WORKSPACE_CONFIG";
@ -278,24 +263,7 @@ void Context::setLinalgPreferredBackend(at::LinalgBackend b) {
}
}
at::BlasBackend Context::blasPreferredBackend() {
#ifdef USE_ROCM
if (blas_preferred_backend == at::BlasBackend::Cublaslt) {
static const bool hipblaslt_unsupported = []() {
static const std::vector<std::string> archs = {"gfx90a", "gfx940", "gfx941", "gfx942"};
for (auto index: c10::irange(getNumGPUs())) {
if (!detail::getCUDAHooks().isGPUArch(index, archs)) {
TORCH_WARN_ONCE(
"Attempting to use hipBLASLt on an unsupported architecture! "
"Overriding blas backend to hipblas");
return true;
}
}
return false;
}();
if (hipblaslt_unsupported) blas_preferred_backend = at::BlasBackend::Cublas;
}
#endif
at::BlasBackend Context::blasPreferredBackend() const {
return blas_preferred_backend;
}

View File

@ -59,14 +59,12 @@ class TORCH_API Context {
}
}
const AcceleratorHooksInterface& getAcceleratorHooksInterface(
std::optional<c10::DeviceType> opt_device_type = std::nullopt) {
std::optional<c10::DeviceType> opt_device_type = c10::nullopt) {
c10::DeviceType device_type = opt_device_type.has_value()
? opt_device_type.value()
: at::getAccelerator(true).value();
if (device_type == at::kCUDA) {
return at::detail::getCUDAHooks();
} else if (device_type == at::kXPU) {
return at::detail::getXPUHooks();
} else if (device_type == at::kMPS) {
return at::detail::getMPSHooks();
} else if (device_type == at::kPrivateUse1) {
@ -190,8 +188,6 @@ class TORCH_API Context {
void setBenchmarkLimitCuDNN(int);
bool deterministicCuDNN() const;
void setDeterministicCuDNN(bool);
bool deterministicMkldnn() const;
void setDeterministicMkldnn(bool);
bool userEnabledNNPACK() const;
void setUserEnabledNNPACK(bool e);
@ -218,13 +214,10 @@ class TORCH_API Context {
void setSDPUseCuDNN(bool);
bool userEnabledCuDNNSDP() const;
void setSDPUseOverrideable(bool);
bool userEnabledOverrideableSDP() const;
at::LinalgBackend linalgPreferredBackend() const;
void setLinalgPreferredBackend(at::LinalgBackend);
at::BlasBackend blasPreferredBackend();
at::BlasBackend blasPreferredBackend() const;
void setBlasPreferredBackend(at::BlasBackend);
// Note [Enabling Deterministic Operations]
@ -365,7 +358,6 @@ class TORCH_API Context {
c10::once_flag thp_init;
bool enabled_cudnn = true;
bool deterministic_cudnn = false;
bool deterministic_mkldnn = false;
bool _deterministic_algorithms = false;
bool _deterministic_algorithms_warn_only = false;
bool _deterministic_fill_uninitialized_memory = true;
@ -373,7 +365,6 @@ class TORCH_API Context {
bool enabled_mem_efficientSDP = true;
bool enabled_mathSDP = true;
bool enabled_cudnnSDP = true;
bool enabled_overrideable = true;
#ifdef USE_ROCM
bool benchmark_cudnn = true;
#else
@ -407,7 +398,7 @@ class TORCH_API Context {
bool release_original_weights = false;
#endif
bool display_vmap_fallback_warnings_ = false;
std::optional<at::QEngine> quantized_engine = std::nullopt;
std::optional<at::QEngine> quantized_engine = c10::nullopt;
bool enable_sparse_tensor_invariant_checks = false;
bool allow_fp16_reduction_cpu = false;

View File

@ -115,9 +115,6 @@ static DLDevice getDLDevice(const Tensor& tensor, c10::DeviceIndex device_id) {
ctx.device_id =
at::detail::getXPUHooks().getGlobalIdxFromDevice(tensor.device());
break;
case DeviceType::MAIA:
ctx.device_type = DLDeviceType::kDLMAIA;
break;
default:
TORCH_CHECK(false, "Cannot pack tensors on " + tensor.device().str());
}
@ -144,11 +141,9 @@ static Device getATenDevice(const DLDevice& ctx, void* data) {
#endif
case DLDeviceType::kDLOneAPI:
return at::detail::getXPUHooks().getDeviceFromPtr(data);
case DLDeviceType::kDLMAIA:
return at::Device(DeviceType::MAIA, ctx.device_id);
default:
TORCH_CHECK(
false, "Unsupported device_type: ", std::to_string(ctx.device_type));
false, "Unsupported device_type: " + c10::to_string(ctx.device_type));
}
}
@ -172,7 +167,7 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kUInt bits ", std::to_string(dtype.bits));
false, "Unsupported kUInt bits " + c10::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLInt:
@ -191,7 +186,7 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kInt bits ", std::to_string(dtype.bits));
false, "Unsupported kInt bits " + c10::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat:
@ -207,7 +202,7 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kFloat bits ", std::to_string(dtype.bits));
false, "Unsupported kFloat bits " + c10::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLBfloat:
@ -217,7 +212,7 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kFloat bits ", std::to_string(dtype.bits));
false, "Unsupported kFloat bits " + c10::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLComplex:
@ -233,7 +228,7 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kFloat bits ", std::to_string(dtype.bits));
false, "Unsupported kFloat bits " + c10::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLBool:
@ -243,11 +238,11 @@ ScalarType toScalarType(const DLDataType& dtype) {
break;
default:
TORCH_CHECK(
false, "Unsupported kDLBool bits ", std::to_string(dtype.bits));
false, "Unsupported kDLBool bits " + c10::to_string(dtype.bits));
}
break;
default:
TORCH_CHECK(false, "Unsupported code ", std::to_string(dtype.code));
TORCH_CHECK(false, "Unsupported code " + c10::to_string(dtype.code));
}
return stype;
}
@ -303,7 +298,9 @@ Tensor fromDLPack(DLManagedTensor* src) {
return fromDLPack(src, std::move(deleter));
}
Tensor fromDLPack(DLManagedTensor* src, std::function<void(void*)> deleter) {
Tensor fromDLPack(
DLManagedTensor* src,
std::function<void(void*)> deleter) {
Device device = getATenDevice(src->dl_tensor.device, src->dl_tensor.data);
ScalarType stype = toScalarType(src->dl_tensor.dtype);
if (!src->dl_tensor.strides) {

View File

@ -1,37 +1,39 @@
#include <ATen/Context.h>
#include <ATen/DeviceAccelerator.h>
#include <ATen/Context.h>
namespace at {
C10_API std::optional<DeviceType> getAccelerator(bool checked) {
#define DETECT_AND_ASSIGN_ACCELERATOR(device_name) \
if (at::has##device_name()) { \
device_type = k##device_name; \
TORCH_CHECK( \
!is_accelerator_detected, \
"Cannot have ", \
device_type.value(), \
" with other accelerators."); \
is_accelerator_detected = true; \
}
#define CHECK_NO_CUDA \
TORCH_CHECK(!at::hasCUDA(), "Cannot have both CUDA and PrivateUse1");
if (is_privateuse1_backend_registered()) {
// We explicitly allow PrivateUse1 and another device at the same time as we
// use this for testing. Whenever a PrivateUse1 device is registered, use it
// first.
return kPrivateUse1;
}
std::optional<DeviceType> device_type = std::nullopt;
bool is_accelerator_detected = false;
DETECT_AND_ASSIGN_ACCELERATOR(CUDA)
DETECT_AND_ASSIGN_ACCELERATOR(MTIA)
DETECT_AND_ASSIGN_ACCELERATOR(XPU)
if (checked) {
TORCH_CHECK(
device_type, "Cannot access accelerator device when none is available.")
}
return device_type;
#define CHECK_NO_PU1 \
TORCH_CHECK(!is_privateuse1_backend_registered(), "Cannot have both CUDA and PrivateUse1");
#undef DETECT_AND_ASSIGN_ACCELERATOR
#define CHECK_NO_MTIA \
TORCH_CHECK(!at::hasMTIA(), "Cannot have MTIA with other devices");
if (is_privateuse1_backend_registered()) {
// We explicitly allow PrivateUse1 and another device at the same time
// as we use this for testing.
// Whenever a PrivateUse1 device is registered, use it first.
return kPrivateUse1;
} else if (at::hasCUDA()) {
CHECK_NO_PU1
CHECK_NO_MTIA
return kCUDA;
} else if (at::hasMTIA()) {
CHECK_NO_CUDA
CHECK_NO_PU1
return kMTIA;
} else {
TORCH_CHECK(!checked, "Cannot access accelerator device when none is available.")
return std::nullopt;
}
#undef CHECK_NO_CUDA
#undef CHECK_NO_PU1
}
} // namespace at

View File

@ -13,9 +13,9 @@
// - It provides a set of common APIs as defined by AcceleratorHooksInterface
//
// As of today, accelerator devices are (in no particular order):
// CUDA, MTIA, XPU, PrivateUse1
// CUDA, MTIA, PrivateUse1
// We want to add once all the proper APIs are supported and tested:
// HIP, MPS
// HIP, MPS, XPU
namespace at {

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