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https://github.com/pytorch/pytorch.git
synced 2025-10-23 06:34:55 +08:00
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1 Commits
chuanqi129
...
module-sta
| Author | SHA1 | Date | |
|---|---|---|---|
| f1f9683409 |
@ -13,6 +13,49 @@ def list_dir(path: str) -> list[str]:
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return check_output(["ls", "-1", path]).decode().split("\n")
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def build_ArmComputeLibrary() -> None:
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"""
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Using ArmComputeLibrary for aarch64 PyTorch
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"""
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print("Building Arm Compute Library")
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acl_build_flags = [
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"debug=0",
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"neon=1",
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"opencl=0",
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"os=linux",
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"openmp=1",
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"cppthreads=0",
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"arch=armv8a",
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"multi_isa=1",
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"fixed_format_kernels=1",
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"build=native",
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]
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acl_install_dir = "/acl"
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acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
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if os.path.isdir(acl_install_dir):
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shutil.rmtree(acl_install_dir)
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if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
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check_call(
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[
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"git",
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"clone",
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"https://github.com/ARM-software/ComputeLibrary.git",
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"-b",
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"v25.02",
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"--depth",
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"1",
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"--shallow-submodules",
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]
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)
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check_call(
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["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
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cwd=acl_checkout_dir,
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)
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for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
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shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
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def replace_tag(filename) -> None:
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with open(filename) as f:
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lines = f.readlines()
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@ -313,13 +356,19 @@ if __name__ == "__main__":
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build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1 "
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if enable_mkldnn:
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build_ArmComputeLibrary()
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print("build pytorch with mkldnn+acl backend")
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build_vars += "USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
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build_vars += "ACL_ROOT_DIR=/acl "
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build_vars += (
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"USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
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"ACL_ROOT_DIR=/acl "
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"LD_LIBRARY_PATH=/pytorch/build/lib:/acl/build:$LD_LIBRARY_PATH "
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"ACL_INCLUDE_DIR=/acl/build "
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"ACL_LIBRARY=/acl/build "
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)
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if enable_cuda:
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build_vars += "BLAS=NVPL "
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else:
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build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/opt/OpenBLAS "
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build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/OpenBLAS "
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else:
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print("build pytorch without mkldnn backend")
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@ -299,6 +299,40 @@ def install_condaforge_python(host: RemoteHost, python_version="3.8") -> None:
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)
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def build_OpenBLAS(host: RemoteHost, git_clone_flags: str = "") -> None:
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print("Building OpenBLAS")
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host.run_cmd(
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f"git clone https://github.com/xianyi/OpenBLAS -b v0.3.28 {git_clone_flags}"
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)
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make_flags = "NUM_THREADS=64 USE_OPENMP=1 NO_SHARED=1 DYNAMIC_ARCH=1 TARGET=ARMV8"
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host.run_cmd(
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f"pushd OpenBLAS && make {make_flags} -j8 && sudo make {make_flags} install && popd && rm -rf OpenBLAS"
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)
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def build_ArmComputeLibrary(host: RemoteHost, git_clone_flags: str = "") -> None:
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print("Building Arm Compute Library")
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acl_build_flags = " ".join(
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[
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"debug=0",
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"neon=1",
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"opencl=0",
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"os=linux",
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"openmp=1",
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"cppthreads=0",
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"arch=armv8a",
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"multi_isa=1",
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"fixed_format_kernels=1",
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"build=native",
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]
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)
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host.run_cmd(
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f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v25.02 {git_clone_flags}"
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)
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host.run_cmd(f"cd ComputeLibrary && scons Werror=1 -j8 {acl_build_flags}")
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def embed_libgomp(host: RemoteHost, use_conda, wheel_name) -> None:
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host.run_cmd("pip3 install auditwheel")
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host.run_cmd(
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@ -666,6 +700,7 @@ def start_build(
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configure_system(
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host, compiler=compiler, use_conda=use_conda, python_version=python_version
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)
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build_OpenBLAS(host, git_clone_flags)
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if host.using_docker():
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print("Move libgfortant.a into a standard location")
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@ -688,8 +723,6 @@ def start_build(
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f"git clone --recurse-submodules -b {branch} https://github.com/pytorch/pytorch {git_clone_flags}"
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)
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host.run_cmd("pytorch/.ci/docker/common/install_openblas.sh")
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print("Building PyTorch wheel")
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build_opts = ""
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if pytorch_build_number is not None:
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@ -710,18 +743,16 @@ def start_build(
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if host.using_docker():
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build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
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if enable_mkldnn:
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host.run_cmd("pytorch/.ci/docker/common/install_acl.sh")
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build_ArmComputeLibrary(host, git_clone_flags)
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print("build pytorch with mkldnn+acl backend")
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build_vars += " USE_MKLDNN=ON USE_MKLDNN_ACL=ON"
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build_vars += " BLAS=OpenBLAS"
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build_vars += " OpenBLAS_HOME=/opt/OpenBLAS"
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build_vars += " ACL_ROOT_DIR=/acl"
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host.run_cmd(
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f"cd $HOME/pytorch && {build_vars} python3 -m build --wheel --no-isolation{build_opts}"
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f"cd $HOME/pytorch && export ACL_ROOT_DIR=$HOME/ComputeLibrary && "
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f"{build_vars} python3 -m build --wheel --no-isolation{build_opts}"
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)
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print("Repair the wheel")
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pytorch_wheel_name = host.list_dir("pytorch/dist")[0]
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ld_library_path = "/acl/build:$HOME/pytorch/build/lib"
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ld_library_path = "$HOME/acl/build:$HOME/pytorch/build/lib"
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host.run_cmd(
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f"export LD_LIBRARY_PATH={ld_library_path} && auditwheel repair $HOME/pytorch/dist/{pytorch_wheel_name}"
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)
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@ -877,7 +908,7 @@ def terminate_instances(instance_type: str) -> None:
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def parse_arguments():
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from argparse import ArgumentParser
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parser = ArgumentParser("Build and test AARCH64 wheels using EC2")
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parser = ArgumentParser("Builid and test AARCH64 wheels using EC2")
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parser.add_argument("--key-name", type=str)
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parser.add_argument("--debug", action="store_true")
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parser.add_argument("--build-only", action="store_true")
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@ -37,9 +37,9 @@ case ${DOCKER_TAG_PREFIX} in
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rocm*)
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BASE_TARGET=rocm
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PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
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# add gfx950, gfx115x conditionally starting in ROCm 7.0
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# add gfx950 conditionally starting in ROCm 7.0
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if [[ "$ROCM_VERSION" == *"7.0"* ]]; then
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PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
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PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
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fi
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EXTRA_BUILD_ARGS="${EXTRA_BUILD_ARGS} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
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;;
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@ -344,7 +344,7 @@ docker build \
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--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
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--build-arg "KATEX=${KATEX:-}" \
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--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
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--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a;gfx942;gfx1100}" \
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--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a;gfx942}" \
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--build-arg "IMAGE_NAME=${IMAGE_NAME}" \
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--build-arg "UCX_COMMIT=${UCX_COMMIT}" \
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--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
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@ -1 +1 @@
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||||
deb42f2a8e48f5032b4a98ee781a15fa87a157cf
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e0dda9059d082537cee36be6c5e4fe3b18c880c0
|
||||
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||||
@ -1 +1 @@
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v2.27.5-1
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v2.28.3-1
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||||
@ -1 +1 @@
|
||||
v2.27.7-1
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v2.28.3-1
|
||||
|
||||
@ -1 +1 @@
|
||||
7416ffcb92cdbe98d9f97e4e6f95247e46dfc9fd
|
||||
bbb06c0334a6772b92d24bde54956e675c8c6604
|
||||
|
||||
27
.ci/docker/common/install_acl.sh
Executable file → Normal file
27
.ci/docker/common/install_acl.sh
Executable file → Normal file
@ -1,27 +1,16 @@
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#!/bin/bash
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# Script used only in CD pipeline
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set -euo pipefail
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set -eux
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ACL_VERSION=${ACL_VERSION:-"v25.02"}
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ACL_INSTALL_DIR="/acl"
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readonly version=v25.02
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readonly src_host=https://github.com/ARM-software
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readonly src_repo=ComputeLibrary
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# Clone ACL
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git clone https://github.com/ARM-software/ComputeLibrary.git -b "${ACL_VERSION}" --depth 1 --shallow-submodules
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[[ ! -d ${src_repo} ]] && git clone ${src_host}/${src_repo}.git
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cd ${src_repo}
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git checkout $version
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ACL_CHECKOUT_DIR="ComputeLibrary"
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# Build with scons
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pushd $ACL_CHECKOUT_DIR
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scons -j8 Werror=0 debug=0 neon=1 opencl=0 embed_kernels=0 \
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os=linux arch=armv8a build=native multi_isa=1 \
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fixed_format_kernels=1 openmp=1 cppthreads=0
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popd
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|
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# Install ACL
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sudo mkdir -p ${ACL_INSTALL_DIR}
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for d in arm_compute include utils support src build
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do
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sudo cp -r ${ACL_CHECKOUT_DIR}/${d} ${ACL_INSTALL_DIR}/${d}
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done
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||||
|
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rm -rf $ACL_CHECKOUT_DIR
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@ -19,8 +19,8 @@ pip_install \
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transformers==4.36.2
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|
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pip_install coloredlogs packaging
|
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pip_install onnxruntime==1.23.0
|
||||
pip_install onnxscript==0.5.3
|
||||
pip_install onnxruntime==1.22.1
|
||||
pip_install onnxscript==0.4.0
|
||||
|
||||
# Cache the transformers model to be used later by ONNX tests. We need to run the transformers
|
||||
# package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/
|
||||
|
||||
12
.ci/docker/common/install_openblas.sh
Executable file → Normal file
12
.ci/docker/common/install_openblas.sh
Executable file → Normal file
@ -3,10 +3,8 @@
|
||||
|
||||
set -ex
|
||||
|
||||
OPENBLAS_VERSION=${OPENBLAS_VERSION:-"v0.3.30"}
|
||||
|
||||
# Clone OpenBLAS
|
||||
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION}" --depth 1 --shallow-submodules
|
||||
cd /
|
||||
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.30}" --depth 1 --shallow-submodules
|
||||
|
||||
OPENBLAS_CHECKOUT_DIR="OpenBLAS"
|
||||
OPENBLAS_BUILD_FLAGS="
|
||||
@ -19,7 +17,5 @@ CFLAGS=-O3
|
||||
BUILD_BFLOAT16=1
|
||||
"
|
||||
|
||||
make -j8 ${OPENBLAS_BUILD_FLAGS} -C $OPENBLAS_CHECKOUT_DIR
|
||||
sudo make install -C $OPENBLAS_CHECKOUT_DIR
|
||||
|
||||
rm -rf $OPENBLAS_CHECKOUT_DIR
|
||||
make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
|
||||
make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}
|
||||
|
||||
@ -1,9 +0,0 @@
|
||||
#!/bin/bash
|
||||
set -xe
|
||||
# Script used in Linux x86 and aarch64 CD pipeline
|
||||
|
||||
# Workaround for exposing statically linked libstdc++ CXX11 ABI symbols.
|
||||
# see: https://github.com/pytorch/pytorch/issues/133437
|
||||
LIBNONSHARED=$(gcc -print-file-name=libstdc++_nonshared.a)
|
||||
nm -g $LIBNONSHARED | grep " T " | grep recursive_directory_iterator | cut -c 20- > weaken-symbols.txt
|
||||
objcopy --weaken-symbols weaken-symbols.txt $LIBNONSHARED $LIBNONSHARED
|
||||
@ -46,9 +46,9 @@ case ${DOCKER_TAG_PREFIX} in
|
||||
BASE_TARGET=rocm
|
||||
GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete
|
||||
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
|
||||
# add gfx950, gfx115x conditionally starting in ROCm 7.0
|
||||
# add gfx950 conditionally starting in ROCm 7.0
|
||||
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
|
||||
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
|
||||
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
|
||||
fi
|
||||
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
|
||||
;;
|
||||
|
||||
@ -130,8 +130,7 @@ ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/op
|
||||
RUN for cpython_version in "cp312-cp312" "cp313-cp313" "cp313-cp313t"; do \
|
||||
/opt/python/${cpython_version}/bin/python -m pip install setuptools wheel; \
|
||||
done;
|
||||
ADD ./common/patch_libstdc.sh patch_libstdc.sh
|
||||
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
|
||||
|
||||
|
||||
# cmake-3.18.4 from pip; force in case cmake3 already exists
|
||||
RUN yum install -y python3-pip && \
|
||||
|
||||
@ -62,13 +62,6 @@ ARG OPENBLAS_VERSION
|
||||
ADD ./common/install_openblas.sh install_openblas.sh
|
||||
RUN bash ./install_openblas.sh && rm install_openblas.sh
|
||||
|
||||
# Install Arm Compute Library
|
||||
FROM base as arm_compute
|
||||
# use python3.9 to install scons
|
||||
RUN python3.9 -m pip install scons==4.7.0
|
||||
RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
|
||||
COPY ./common/install_acl.sh install_acl.sh
|
||||
RUN bash ./install_acl.sh && rm install_acl.sh
|
||||
FROM base as final
|
||||
|
||||
# remove unnecessary python versions
|
||||
@ -77,7 +70,4 @@ RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
|
||||
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
|
||||
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
|
||||
COPY --from=openblas /opt/OpenBLAS/ /opt/OpenBLAS/
|
||||
COPY --from=arm_compute /acl /acl
|
||||
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:/acl/build/:$LD_LIBRARY_PATH
|
||||
ADD ./common/patch_libstdc.sh patch_libstdc.sh
|
||||
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
|
||||
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH
|
||||
|
||||
@ -86,15 +86,6 @@ FROM base as nvpl
|
||||
ADD ./common/install_nvpl.sh install_nvpl.sh
|
||||
RUN bash ./install_nvpl.sh && rm install_nvpl.sh
|
||||
|
||||
# Install Arm Compute Library
|
||||
FROM base as arm_compute
|
||||
# use python3.9 to install scons
|
||||
RUN python3.9 -m pip install scons==4.7.0
|
||||
RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
|
||||
COPY ./common/install_acl.sh install_acl.sh
|
||||
RUN bash ./install_acl.sh && rm install_acl.sh
|
||||
FROM base as final
|
||||
|
||||
FROM final as cuda_final
|
||||
ARG BASE_CUDA_VERSION
|
||||
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
|
||||
@ -102,9 +93,5 @@ COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BAS
|
||||
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
|
||||
COPY --from=nvpl /opt/nvpl/lib/ /usr/local/lib/
|
||||
COPY --from=nvpl /opt/nvpl/include/ /usr/local/include/
|
||||
COPY --from=arm_compute /acl /acl
|
||||
RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
|
||||
ENV PATH=/usr/local/cuda/bin:$PATH
|
||||
ENV LD_LIBRARY_PATH=/acl/build/:$LD_LIBRARY_PATH
|
||||
ADD ./common/patch_libstdc.sh patch_libstdc.sh
|
||||
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
|
||||
|
||||
@ -115,9 +115,6 @@ RUN env GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True pip3 install grpcio
|
||||
# cmake-3.28.0 from pip for onnxruntime
|
||||
RUN python3 -mpip install cmake==3.28.0
|
||||
|
||||
ADD ./common/patch_libstdc.sh patch_libstdc.sh
|
||||
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
|
||||
|
||||
# build onnxruntime 1.21.0 from sources.
|
||||
# it is not possible to build it from sources using pip,
|
||||
# so just build it from upstream repository.
|
||||
|
||||
@ -28,7 +28,6 @@ fi
|
||||
MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
|
||||
DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
|
||||
OPENBLAS_VERSION=${OPENBLAS_VERSION:-}
|
||||
ACL_VERSION=${ACL_VERSION:-}
|
||||
|
||||
case ${image} in
|
||||
manylinux2_28-builder:cpu)
|
||||
@ -42,6 +41,7 @@ case ${image} in
|
||||
GPU_IMAGE=arm64v8/almalinux:8
|
||||
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
|
||||
MANY_LINUX_VERSION="2_28_aarch64"
|
||||
OPENBLAS_VERSION="v0.3.30"
|
||||
;;
|
||||
manylinuxs390x-builder:cpu-s390x)
|
||||
TARGET=final
|
||||
@ -84,9 +84,9 @@ case ${image} in
|
||||
DEVTOOLSET_VERSION="11"
|
||||
GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
|
||||
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
|
||||
# add gfx950, gfx115x conditionally starting in ROCm 7.0
|
||||
# add gfx950 conditionally starting in ROCm 7.0
|
||||
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
|
||||
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
|
||||
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
|
||||
fi
|
||||
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
|
||||
;;
|
||||
@ -119,8 +119,7 @@ tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
|
||||
DOCKER_BUILDKIT=1 docker build \
|
||||
${DOCKER_GPU_BUILD_ARG} \
|
||||
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
|
||||
--build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION:-}" \
|
||||
--build-arg "ACL_VERSION=${ACL_VERSION:-}" \
|
||||
--build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION}" \
|
||||
--target "${TARGET}" \
|
||||
-t "${tmp_tag}" \
|
||||
$@ \
|
||||
|
||||
@ -52,10 +52,10 @@ flatbuffers==24.12.23
|
||||
#Pinned versions: 24.12.23
|
||||
#test that import:
|
||||
|
||||
hypothesis==6.56.4
|
||||
hypothesis==5.35.1
|
||||
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
|
||||
#Description: advanced library for generating parametrized tests
|
||||
#Pinned versions: 6.56.4
|
||||
#Pinned versions: 5.35.1
|
||||
#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
|
||||
|
||||
junitparser==2.1.1
|
||||
@ -98,7 +98,7 @@ librosa==0.10.2 ; python_version == "3.12" and platform_machine != "s390x"
|
||||
#Pinned versions:
|
||||
#test that import:
|
||||
|
||||
mypy==1.16.0 ; platform_system == "Linux"
|
||||
mypy==1.16.0 ; platform_system != "Windows"
|
||||
# Pin MyPy version because new errors are likely to appear with each release
|
||||
# Skip on Windows as lots of type annotations are POSIX specific
|
||||
#Description: linter
|
||||
@ -120,8 +120,9 @@ ninja==1.11.1.4
|
||||
numba==0.55.2 ; python_version == "3.10" and platform_machine != "s390x"
|
||||
numba==0.60.0 ; python_version == "3.12" and platform_machine != "s390x"
|
||||
#Description: Just-In-Time Compiler for Numerical Functions
|
||||
#Pinned versions: 0.55.2, 0.60.0
|
||||
#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
|
||||
#test that import: test_numba_integration.py
|
||||
#For numba issue see https://github.com/pytorch/pytorch/issues/51511
|
||||
#Need release > 0.61.2 for s390x due to https://github.com/numba/numba/pull/10073
|
||||
|
||||
#numpy
|
||||
@ -168,7 +169,7 @@ optree==0.13.0
|
||||
|
||||
pillow==11.0.0
|
||||
#Description: Python Imaging Library fork
|
||||
#Pinned versions: 11.0.0
|
||||
#Pinned versions: 10.3.0
|
||||
#test that import:
|
||||
|
||||
protobuf==5.29.5
|
||||
@ -216,7 +217,7 @@ pytest-subtests==0.13.1
|
||||
#Pinned versions:
|
||||
#test that import:
|
||||
|
||||
xdoctest==1.3.0
|
||||
xdoctest==1.1.0
|
||||
#Description: runs doctests in pytest
|
||||
#Pinned versions: 1.1.0
|
||||
#test that import:
|
||||
@ -241,9 +242,10 @@ pygments==2.15.0
|
||||
#Pinned versions: 14.1.0
|
||||
#test that import:
|
||||
|
||||
scikit-image==0.22.0
|
||||
scikit-image==0.19.3 ; python_version < "3.10"
|
||||
scikit-image==0.22.0 ; python_version >= "3.10"
|
||||
#Description: image processing routines
|
||||
#Pinned versions: 0.22.0
|
||||
#Pinned versions:
|
||||
#test that import: test_nn.py
|
||||
|
||||
#scikit-learn
|
||||
@ -266,7 +268,7 @@ scipy==1.14.1 ; python_version >= "3.12"
|
||||
#test that import:
|
||||
|
||||
# needed by torchgen utils
|
||||
typing-extensions==4.12.2
|
||||
typing-extensions>=4.10.0
|
||||
#Description: type hints for python
|
||||
#Pinned versions:
|
||||
#test that import:
|
||||
@ -339,7 +341,7 @@ onnx==1.18.0
|
||||
#Pinned versions:
|
||||
#test that import:
|
||||
|
||||
onnxscript==0.5.3
|
||||
onnxscript==0.4.0
|
||||
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
|
||||
#Pinned versions:
|
||||
#test that import:
|
||||
@ -359,10 +361,9 @@ pwlf==2.2.1
|
||||
#test that import: test_sac_estimator.py
|
||||
|
||||
# To build PyTorch itself
|
||||
pyyaml==6.0.2
|
||||
pyyaml
|
||||
pyzstd
|
||||
setuptools==78.1.1
|
||||
packaging==23.1
|
||||
setuptools>=70.1.0
|
||||
six
|
||||
|
||||
scons==4.5.2 ; platform_machine == "aarch64"
|
||||
@ -383,10 +384,7 @@ cmake==3.31.6
|
||||
tlparse==0.4.0
|
||||
#Description: required for log parsing
|
||||
|
||||
filelock==3.18.0
|
||||
#Description: required for inductor testing
|
||||
|
||||
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x" and platform_system != "Darwin"
|
||||
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"
|
||||
#Description: required for testing CUDAGraph::raw_cuda_graph(). See https://nvidia.github.io/cuda-python/cuda-bindings/latest/support.html for how this version was chosen. Note "Any fix in the latest bindings would be backported to the prior major version" means that only the newest version of cuda-bindings will get fixes. Depending on the latest version of 12.x is okay because all 12.y versions will be supported via "CUDA minor version compatibility". Pytorch builds against 13.z versions of cuda toolkit work with 12.x versions of cuda-bindings as well because newer drivers work with old toolkits.
|
||||
#test that import: test_cuda.py
|
||||
|
||||
|
||||
@ -5,7 +5,7 @@ DESIRED_ROCM ?= 7.0
|
||||
DESIRED_ROCM_SHORT = $(subst .,,$(DESIRED_ROCM))
|
||||
PACKAGE_NAME = magma-rocm
|
||||
# inherit this from underlying docker image, do not pass this env var to docker
|
||||
#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1150;gfx1151;gfx1200;gfx1201
|
||||
#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201
|
||||
|
||||
DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
|
||||
-v $(shell git rev-parse --show-toplevel)/.ci:/builder \
|
||||
@ -18,6 +18,7 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
|
||||
.PHONY: all
|
||||
all: magma-rocm70
|
||||
all: magma-rocm64
|
||||
all: magma-rocm63
|
||||
|
||||
.PHONY:
|
||||
clean:
|
||||
@ -33,3 +34,8 @@ magma-rocm70:
|
||||
magma-rocm64: DESIRED_ROCM := 6.4
|
||||
magma-rocm64:
|
||||
$(DOCKER_RUN)
|
||||
|
||||
.PHONY: magma-rocm63
|
||||
magma-rocm63: DESIRED_ROCM := 6.3
|
||||
magma-rocm63:
|
||||
$(DOCKER_RUN)
|
||||
|
||||
@ -89,7 +89,7 @@ fi
|
||||
if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
|
||||
export USE_MKLDNN=1
|
||||
export USE_MKLDNN_ACL=1
|
||||
export ACL_ROOT_DIR=/acl
|
||||
export ACL_ROOT_DIR=/ComputeLibrary
|
||||
fi
|
||||
|
||||
if [[ "$BUILD_ENVIRONMENT" == *riscv64* ]]; then
|
||||
|
||||
@ -256,7 +256,7 @@ test_torchbench_smoketest() {
|
||||
local device=mps
|
||||
local dtypes=(undefined float16 bfloat16 notset)
|
||||
local dtype=${dtypes[$1]}
|
||||
local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
|
||||
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
|
||||
|
||||
for backend in eager inductor; do
|
||||
|
||||
@ -319,7 +319,7 @@ test_aoti_torchbench_smoketest() {
|
||||
local device=mps
|
||||
local dtypes=(undefined float16 bfloat16 notset)
|
||||
local dtype=${dtypes[$1]}
|
||||
local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
|
||||
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
|
||||
|
||||
echo "Launching torchbench inference performance run for AOT Inductor and dtype ${dtype}"
|
||||
local dtype_arg="--${dtype}"
|
||||
|
||||
@ -32,9 +32,6 @@ LIBTORCH_NAMESPACE_LIST = (
|
||||
"torch::",
|
||||
)
|
||||
|
||||
# Patterns for detecting statically linked libstdc++ symbols
|
||||
STATICALLY_LINKED_CXX11_ABI = [re.compile(r".*recursive_directory_iterator.*")]
|
||||
|
||||
|
||||
def _apply_libtorch_symbols(symbols):
|
||||
return [
|
||||
@ -56,17 +53,12 @@ def get_symbols(lib: str) -> list[tuple[str, str, str]]:
|
||||
return [x.split(" ", 2) for x in lines.decode("latin1").split("\n")[:-1]]
|
||||
|
||||
|
||||
def grep_symbols(
|
||||
lib: str, patterns: list[Any], symbol_type: str | None = None
|
||||
) -> list[str]:
|
||||
def grep_symbols(lib: str, patterns: list[Any]) -> list[str]:
|
||||
def _grep_symbols(
|
||||
symbols: list[tuple[str, str, str]], patterns: list[Any]
|
||||
) -> list[str]:
|
||||
rc = []
|
||||
for _s_addr, _s_type, s_name in symbols:
|
||||
# Filter by symbol type if specified
|
||||
if symbol_type and _s_type != symbol_type:
|
||||
continue
|
||||
for pattern in patterns:
|
||||
if pattern.match(s_name):
|
||||
rc.append(s_name)
|
||||
@ -88,18 +80,6 @@ def grep_symbols(
|
||||
return functools.reduce(list.__add__, (x.result() for x in tasks), [])
|
||||
|
||||
|
||||
def check_lib_statically_linked_libstdc_cxx_abi_symbols(lib: str) -> None:
|
||||
cxx11_statically_linked_symbols = grep_symbols(
|
||||
lib, STATICALLY_LINKED_CXX11_ABI, symbol_type="T"
|
||||
)
|
||||
num_statically_linked_symbols = len(cxx11_statically_linked_symbols)
|
||||
print(f"num_statically_linked_symbols (T): {num_statically_linked_symbols}")
|
||||
if num_statically_linked_symbols > 0:
|
||||
raise RuntimeError(
|
||||
f"Found statically linked libstdc++ symbols (recursive_directory_iterator): {cxx11_statically_linked_symbols[:100]}"
|
||||
)
|
||||
|
||||
|
||||
def check_lib_symbols_for_abi_correctness(lib: str) -> None:
|
||||
print(f"lib: {lib}")
|
||||
cxx11_symbols = grep_symbols(lib, LIBTORCH_CXX11_PATTERNS)
|
||||
@ -127,7 +107,6 @@ def main() -> None:
|
||||
|
||||
libtorch_cpu_path = str(install_root / "lib" / "libtorch_cpu.so")
|
||||
check_lib_symbols_for_abi_correctness(libtorch_cpu_path)
|
||||
check_lib_statically_linked_libstdc_cxx_abi_symbols(libtorch_cpu_path)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@ -34,14 +34,12 @@ fi
|
||||
|
||||
|
||||
# Patch numba to avoid CUDA-13 crash, see https://github.com/pytorch/pytorch/issues/162878
|
||||
if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
|
||||
NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
|
||||
if [ -n "$NUMBA_CUDA_DIR" ]; then
|
||||
NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
|
||||
pushd "$NUMBA_CUDA_DIR"
|
||||
patch -p4 <"$NUMBA_PATCH"
|
||||
popd
|
||||
fi
|
||||
NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
|
||||
if [ -n "$NUMBA_CUDA_DIR" ]; then
|
||||
NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
|
||||
pushd "$NUMBA_CUDA_DIR"
|
||||
patch -p4 <"$NUMBA_PATCH"
|
||||
popd
|
||||
fi
|
||||
|
||||
echo "Environment variables:"
|
||||
@ -838,7 +836,7 @@ test_dynamo_benchmark() {
|
||||
elif [[ "${suite}" == "timm_models" ]]; then
|
||||
export TORCHBENCH_ONLY_MODELS="inception_v3"
|
||||
elif [[ "${suite}" == "torchbench" ]]; then
|
||||
export TORCHBENCH_ONLY_MODELS="BERT_pytorch"
|
||||
export TORCHBENCH_ONLY_MODELS="hf_Bert"
|
||||
fi
|
||||
fi
|
||||
test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
|
||||
@ -869,13 +867,13 @@ test_inductor_torchbench_smoketest_perf() {
|
||||
mkdir -p "$TEST_REPORTS_DIR"
|
||||
|
||||
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
|
||||
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only BERT_pytorch \
|
||||
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
|
||||
--output "$TEST_REPORTS_DIR/inductor_training_smoketest.csv"
|
||||
# The threshold value needs to be actively maintained to make this check useful
|
||||
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_training_smoketest.csv" -t 1.4
|
||||
|
||||
# Check memory compression ratio for a few models
|
||||
for test in BERT_pytorch yolov3; do
|
||||
for test in hf_Albert timm_vision_transformer; do
|
||||
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --amp --training \
|
||||
--disable-cudagraphs --batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" \
|
||||
--only $test --output "$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv"
|
||||
@ -886,7 +884,7 @@ test_inductor_torchbench_smoketest_perf() {
|
||||
done
|
||||
|
||||
# Perform some "warm-start" runs for a few huggingface models.
|
||||
for test in AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
|
||||
for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
|
||||
python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
|
||||
--only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
|
||||
python benchmarks/dynamo/check_accuracy.py \
|
||||
|
||||
@ -1,32 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
set -ex -o pipefail
|
||||
|
||||
# Suppress ANSI color escape sequences
|
||||
export TERM=vt100
|
||||
|
||||
# shellcheck source=./common.sh
|
||||
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
|
||||
# shellcheck source=./common-build.sh
|
||||
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
|
||||
|
||||
echo "Environment variables"
|
||||
env
|
||||
|
||||
echo "Testing FA3 stable wheel still works with currently built torch"
|
||||
|
||||
echo "Installing ABI Stable FA3 wheel"
|
||||
# The wheel was built on https://github.com/Dao-AILab/flash-attention/commit/b3846b059bf6b143d1cd56879933be30a9f78c81
|
||||
# on torch nightly torch==2.9.0.dev20250830+cu129
|
||||
$MAYBE_SUDO pip -q install https://s3.amazonaws.com/ossci-linux/wheels/flash_attn_3-3.0.0b1-cp39-abi3-linux_x86_64.whl
|
||||
|
||||
pushd flash-attention/hopper
|
||||
export PYTHONPATH=$PWD
|
||||
pytest -v -s \
|
||||
"test_flash_attn.py::test_flash_attn_output[1-1-192-False-False-False-0.0-False-False-mha-dtype0]" \
|
||||
"test_flash_attn.py::test_flash_attn_varlen_output[511-1-64-True-False-False-0.0-False-False-gqa-dtype2]" \
|
||||
"test_flash_attn.py::test_flash_attn_kvcache[1-128-128-False-False-True-None-0.0-False-False-True-False-True-False-gqa-dtype0]" \
|
||||
"test_flash_attn.py::test_flash_attn_race_condition[97-97-192-True-dtype0]" \
|
||||
"test_flash_attn.py::test_flash_attn_combine[2-3-64-dtype1]" \
|
||||
"test_flash_attn.py::test_flash3_bw_compatibility"
|
||||
popd
|
||||
@ -38,12 +38,10 @@ if errorlevel 1 goto fail
|
||||
if not errorlevel 0 goto fail
|
||||
|
||||
:: Update CMake
|
||||
:: TODO: Investigate why this helps MKL detection, even when CMake from choco is not used
|
||||
call choco upgrade -y cmake --no-progress --installargs 'ADD_CMAKE_TO_PATH=System' --apply-install-arguments-to-dependencies --version=3.27.9
|
||||
if errorlevel 1 goto fail
|
||||
if not errorlevel 0 goto fail
|
||||
|
||||
:: TODO: Move to .ci/docker/requirements-ci.txt
|
||||
call pip install mkl==2024.2.0 mkl-static==2024.2.0 mkl-include==2024.2.0
|
||||
if errorlevel 1 goto fail
|
||||
if not errorlevel 0 goto fail
|
||||
|
||||
@ -37,8 +37,27 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
|
||||
export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
|
||||
fi
|
||||
|
||||
# TODO: Move this to .ci/docker/requirements-ci.txt
|
||||
python -m pip install "psutil==5.9.1" nvidia-ml-py "pytest-shard==0.1.2"
|
||||
# TODO: Move both of them to Windows AMI
|
||||
python -m pip install tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
|
||||
|
||||
# Copied from https://github.com/pytorch/test-infra/blob/be01a40157c36cd5a48391fdf44a7bc3ebd4c7e3/aws/ami/windows/scripts/Installers/Install-Pip-Dependencies.ps1#L16 with some adjustments
|
||||
# pytest-rerunfailures==10.3 as 10.2 fails with INTERNALERROR> pluggy._manager.PluginValidationError: unknown hook 'pytest_configure_node'
|
||||
# scipy from 1.6.3 to 1.10
|
||||
# expecttest from 0.1.3 to 0.3.0
|
||||
# xdoctest from 1.0.2 to 1.3.0
|
||||
python -m pip install "future==0.18.2" "hypothesis==5.35.1" "expecttest==0.3.0" "librosa>=0.6.2" "scipy==1.10.1" "psutil==5.9.1" "pynvml==11.4.1" "pillow==9.2.0" "unittest-xml-reporting<=3.2.0,>=2.0.0" "pytest==7.1.3" "pytest-xdist==2.5.0" "pytest-flakefinder==1.1.0" "pytest-rerunfailures==10.3" "pytest-shard==0.1.2" "sympy==1.11.1" "xdoctest==1.3.0" "pygments==2.12.0" "opt-einsum>=3.3" "networkx==2.8.8" "mpmath==1.2.1" "pytest-cpp==2.3.0" "boto3==1.35.42"
|
||||
|
||||
# Install Z3 optional dependency for Windows builds.
|
||||
python -m pip install z3-solver==4.15.1.0
|
||||
|
||||
# Install tlparse for test\dynamo\test_structured_trace.py UTs.
|
||||
python -m pip install tlparse==0.4.0
|
||||
|
||||
# Install parameterized
|
||||
python -m pip install parameterized==0.8.1
|
||||
|
||||
# Install pulp for testing ilps under torch\distributed\_tools
|
||||
python -m pip install pulp==2.9.0
|
||||
|
||||
run_tests() {
|
||||
# Run nvidia-smi if available
|
||||
|
||||
@ -37,10 +37,10 @@ IF "%CUDA_PATH_V128%"=="" (
|
||||
)
|
||||
|
||||
IF "%BUILD_VISION%" == "" (
|
||||
set TORCH_CUDA_ARCH_LIST=7.0;7.5;8.0;8.6;9.0;10.0;12.0
|
||||
set TORCH_CUDA_ARCH_LIST=6.1;7.0;7.5;8.0;8.6;9.0;10.0;12.0
|
||||
set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
|
||||
) ELSE (
|
||||
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
|
||||
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
|
||||
)
|
||||
|
||||
set "CUDA_PATH=%CUDA_PATH_V128%"
|
||||
|
||||
@ -71,7 +71,14 @@ export PYTORCH_BUILD_NUMBER=1
|
||||
|
||||
# Set triton version as part of PYTORCH_EXTRA_INSTALL_REQUIREMENTS
|
||||
TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
|
||||
TRITON_CONSTRAINT="platform_system == 'Linux'"
|
||||
|
||||
# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
|
||||
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
|
||||
|
||||
# CUDA 12.9/13.0 builds have triton for Linux and Linux aarch64 binaries.
|
||||
if [[ "$DESIRED_CUDA" == "cu129" ]] || [[ "$DESIRED_CUDA" == "cu130" ]]; then
|
||||
TRITON_CONSTRAINT="platform_system == 'Linux'"
|
||||
fi
|
||||
|
||||
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" && ! "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
|
||||
TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
|
||||
|
||||
@ -59,14 +59,13 @@ performance-*,
|
||||
-performance-enum-size,
|
||||
readability-container-size-empty,
|
||||
readability-delete-null-pointer,
|
||||
readability-duplicate-include,
|
||||
readability-duplicate-include
|
||||
readability-misplaced-array-index,
|
||||
readability-redundant*,
|
||||
readability-redundant*
|
||||
readability-simplify-subscript-expr,
|
||||
readability-string-compare,
|
||||
-readability-redundant-access-specifiers,
|
||||
-readability-redundant-control-flow,
|
||||
-readability-redundant-inline-specifier,
|
||||
'
|
||||
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
|
||||
WarningsAsErrors: '*'
|
||||
|
||||
35
.github/actions/setup-linux/action.yml
vendored
35
.github/actions/setup-linux/action.yml
vendored
@ -28,10 +28,6 @@ runs:
|
||||
echo "instance-type: $(get_ec2_metadata instance-type)"
|
||||
echo "system info $(uname -a)"
|
||||
|
||||
- name: Print GPU info (if present)
|
||||
shell: bash
|
||||
run: if [ -f /usr/bin/nvidia-smi ]; then nvidia-smi; fi
|
||||
|
||||
- name: Check if in a container runner
|
||||
shell: bash
|
||||
id: check_container_runner
|
||||
@ -86,6 +82,37 @@ runs:
|
||||
# Prune all of the docker images
|
||||
docker system prune -af
|
||||
|
||||
- name: Manually resolve download.pytorch.org
|
||||
shell: bash
|
||||
continue-on-error: true
|
||||
run: |
|
||||
set +e
|
||||
set -x
|
||||
|
||||
PT_DOMAIN=download.pytorch.org
|
||||
# TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400,
|
||||
# cleaning this up once the issue is fixed. There are more than one resolved IP here, the last
|
||||
# one is returned at random
|
||||
RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1)
|
||||
|
||||
if [ -z "${RESOLVED_IP}" ]; then
|
||||
echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..."
|
||||
RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1)
|
||||
|
||||
if [ -z "${RESOLVED_IP}" ]; then
|
||||
echo "Couldn't resolve ${PT_DOMAIN}, exiting..."
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
if grep -r "${PT_DOMAIN}" /etc/hosts; then
|
||||
# Clean up any old records first
|
||||
sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts
|
||||
fi
|
||||
|
||||
echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts
|
||||
cat /etc/hosts
|
||||
|
||||
- name: Check that the docker daemon is running
|
||||
shell: bash
|
||||
continue-on-error: true
|
||||
|
||||
3
.github/actions/teardown-win/action.yml
vendored
3
.github/actions/teardown-win/action.yml
vendored
@ -23,6 +23,9 @@ runs:
|
||||
run: |
|
||||
.github\scripts\kill_active_ssh_sessions.ps1
|
||||
|
||||
- name: Clean up leftover processes on non-ephemeral Windows runner
|
||||
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
|
||||
|
||||
# Cleaning up Windows workspace sometimes fails flakily with device or resource busy
|
||||
# error, meaning one or more processes haven't stopped completely yet. So trying to
|
||||
# retry this step several time similar to how checkout-pytorch GHA does
|
||||
|
||||
2
.github/ci_commit_pins/vllm.txt
vendored
2
.github/ci_commit_pins/vllm.txt
vendored
@ -1 +1 @@
|
||||
0ad9951c416d33c5da4f7a504fb162cbe62386f5
|
||||
78a47f87ce259a48f0391fa9ae15add05ea7432b
|
||||
|
||||
2
.github/ci_commit_pins/xla.txt
vendored
2
.github/ci_commit_pins/xla.txt
vendored
@ -1 +1 @@
|
||||
2a9138a26ee257fef05310ad3fecf7c55fe80d73
|
||||
0fc62aa26a30ed7ca419d285f285cb5ba02c4394
|
||||
|
||||
16
.github/ci_configs/vllm/Dockerfile.tmp_vllm
vendored
16
.github/ci_configs/vllm/Dockerfile.tmp_vllm
vendored
@ -202,7 +202,7 @@ ARG max_jobs=16
|
||||
ENV MAX_JOBS=${max_jobs}
|
||||
ARG nvcc_threads=4
|
||||
ENV NVCC_THREADS=$nvcc_threads
|
||||
ARG torch_cuda_arch_list='8.0 8.6 8.9 9.0'
|
||||
ARG torch_cuda_arch_list='8.0;8.6;8.9;9.0'
|
||||
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
|
||||
|
||||
ARG USE_SCCACHE
|
||||
@ -297,28 +297,16 @@ RUN echo "[INFO] Listing current directory before torch install step:" && \
|
||||
echo "[INFO] Showing torch_build_versions.txt content:" && \
|
||||
cat torch_build_versions.txt
|
||||
|
||||
# Install build and runtime dependencies, this is needed for flashinfer install
|
||||
COPY requirements/build.txt requirements/build.txt
|
||||
COPY use_existing_torch.py use_existing_torch.py
|
||||
RUN python3 use_existing_torch.py
|
||||
RUN cat requirements/build.txt
|
||||
|
||||
# Install uv for faster pip installs if not existed
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
if ! python3 -m uv --version > /dev/null 2>&1; then \
|
||||
python3 -m pip install uv==0.8.4; \
|
||||
fi
|
||||
|
||||
ENV UV_HTTP_TIMEOUT=500
|
||||
ENV UV_INDEX_STRATEGY="unsafe-best-match"
|
||||
# Use copy mode to avoid hardlink failures with Docker cache mounts
|
||||
ENV UV_LINK_MODE=copy
|
||||
|
||||
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
uv pip install --system -r requirements/build.txt
|
||||
|
||||
|
||||
# Default mount file as placeholder, this just avoid the mount error
|
||||
ARG TORCH_WHEELS_PATH="./requirements"
|
||||
# Install torch, torchaudio and torchvision
|
||||
@ -344,11 +332,13 @@ RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
# Install xformers wheel from previous stage
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
uv pip install --system /wheels/xformers/*.whl --verbose
|
||||
|
||||
# Build flashinfer from source.
|
||||
ARG torch_cuda_arch_list='8.0;8.9;9.0a;10.0a;12.0'
|
||||
# install package for build flashinfer
|
||||
# see issue: https://github.com/flashinfer-ai/flashinfer/issues/738
|
||||
|
||||
RUN pip install build==1.3.0
|
||||
RUN pip freeze | grep -E 'setuptools|packaging|build'
|
||||
|
||||
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
|
||||
|
||||
@ -1,14 +1,9 @@
|
||||
import glob
|
||||
import os
|
||||
|
||||
|
||||
requires_files = glob.glob("requirements/*.txt")
|
||||
requires_files += ["pyproject.toml"]
|
||||
|
||||
for file in requires_files:
|
||||
if not os.path.exists(file):
|
||||
print(f"!!! skipping missing {file}")
|
||||
continue
|
||||
print(f">>> cleaning {file}")
|
||||
with open(file) as f:
|
||||
lines = f.readlines()
|
||||
|
||||
37
.github/requirements/pip-requirements-macOS.txt
vendored
Normal file
37
.github/requirements/pip-requirements-macOS.txt
vendored
Normal file
@ -0,0 +1,37 @@
|
||||
boto3==1.35.42
|
||||
build==1.2.2.post1
|
||||
cmake==3.27.*
|
||||
expecttest==0.3.0
|
||||
fbscribelogger==0.1.7
|
||||
filelock==3.18.0
|
||||
hypothesis==6.56.4
|
||||
librosa>=0.6.2
|
||||
mpmath==1.3.0
|
||||
networkx==2.8.7
|
||||
ninja==1.10.2.4
|
||||
numba==0.59.0
|
||||
numpy==1.26.4
|
||||
opt-einsum>=3.3
|
||||
optree==0.13.0
|
||||
packaging==23.1
|
||||
parameterized==0.8.1
|
||||
pillow==10.3.0
|
||||
protobuf==5.29.5
|
||||
psutil==5.9.8
|
||||
pygments==2.15.0
|
||||
pytest-cpp==2.3.0
|
||||
pytest-flakefinder==1.1.0
|
||||
pytest-rerunfailures==10.3
|
||||
pytest-subtests==0.13.1
|
||||
pytest-xdist==3.3.1
|
||||
pytest==7.3.2
|
||||
pyyaml==6.0.2
|
||||
scipy==1.12.0
|
||||
setuptools==78.1.1
|
||||
sympy==1.13.3
|
||||
tlparse==0.4.0
|
||||
tensorboard==2.13.0
|
||||
typing-extensions==4.12.2
|
||||
unittest-xml-reporting<=3.2.0,>=2.0.0
|
||||
xdoctest==1.1.0
|
||||
z3-solver==4.15.1.0
|
||||
BIN
.github/scripts/drci_mocks.json.gz
vendored
BIN
.github/scripts/drci_mocks.json.gz
vendored
Binary file not shown.
6
.github/scripts/filter_test_configs.py
vendored
6
.github/scripts/filter_test_configs.py
vendored
@ -502,7 +502,6 @@ def perform_misc_tasks(
|
||||
job_name: str,
|
||||
pr_body: str,
|
||||
branch: Optional[str] = None,
|
||||
tag: Optional[str] = None,
|
||||
) -> None:
|
||||
"""
|
||||
In addition to apply the filter logic, the script also does the following
|
||||
@ -510,9 +509,7 @@ def perform_misc_tasks(
|
||||
"""
|
||||
set_output(
|
||||
"keep-going",
|
||||
branch == MAIN_BRANCH
|
||||
or bool(tag and re.match(r"^trunk/[a-f0-9]{40}$", tag))
|
||||
or check_for_setting(labels, pr_body, "keep-going"),
|
||||
branch == MAIN_BRANCH or check_for_setting(labels, pr_body, "keep-going"),
|
||||
)
|
||||
set_output(
|
||||
"ci-verbose-test-logs",
|
||||
@ -637,7 +634,6 @@ def main() -> None:
|
||||
job_name=args.job_name,
|
||||
pr_body=pr_body if pr_body else "",
|
||||
branch=args.branch,
|
||||
tag=tag,
|
||||
)
|
||||
|
||||
# Set the filtered test matrix as the output
|
||||
|
||||
@ -53,7 +53,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
|
||||
"nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | "
|
||||
"nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | "
|
||||
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | "
|
||||
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
|
||||
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | "
|
||||
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | "
|
||||
@ -70,7 +70,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
|
||||
"nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | "
|
||||
"nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | "
|
||||
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | "
|
||||
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
|
||||
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | "
|
||||
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | "
|
||||
@ -87,7 +87,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
|
||||
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | "
|
||||
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | "
|
||||
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | "
|
||||
"nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | "
|
||||
"nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | "
|
||||
"nvidia-nvtx==13.0.39; platform_system == 'Linux' | "
|
||||
"nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | "
|
||||
|
||||
1
.github/scripts/github_utils.py
vendored
1
.github/scripts/github_utils.py
vendored
@ -18,7 +18,6 @@ class GitHubComment:
|
||||
body_text: str
|
||||
created_at: str
|
||||
author_login: str
|
||||
author_url: Optional[str]
|
||||
author_association: str
|
||||
editor_login: Optional[str]
|
||||
database_id: int
|
||||
|
||||
BIN
.github/scripts/gql_mocks.json.gz
vendored
BIN
.github/scripts/gql_mocks.json.gz
vendored
Binary file not shown.
2
.github/scripts/test_check_labels.py
vendored
2
.github/scripts/test_check_labels.py
vendored
@ -38,7 +38,6 @@ def mock_get_comments() -> list[GitHubComment]:
|
||||
body_text="mock_body_text",
|
||||
created_at="",
|
||||
author_login="",
|
||||
author_url=None,
|
||||
author_association="",
|
||||
editor_login=None,
|
||||
database_id=1,
|
||||
@ -49,7 +48,6 @@ def mock_get_comments() -> list[GitHubComment]:
|
||||
body_text=" #" + LABEL_ERR_MSG_TITLE.replace("`", ""),
|
||||
created_at="",
|
||||
author_login=BOT_AUTHORS[1],
|
||||
author_url=None,
|
||||
author_association="",
|
||||
editor_login=None,
|
||||
database_id=2,
|
||||
|
||||
18
.github/scripts/test_trymerge.py
vendored
18
.github/scripts/test_trymerge.py
vendored
@ -32,7 +32,6 @@ from trymerge import (
|
||||
main as trymerge_main,
|
||||
MandatoryChecksMissingError,
|
||||
MergeRule,
|
||||
PostCommentError,
|
||||
RE_GHSTACK_DESC,
|
||||
read_merge_rules,
|
||||
remove_job_name_suffix,
|
||||
@ -589,23 +588,6 @@ class TestTryMerge(TestCase):
|
||||
self.assertEqual(mock_merge_base, pr.get_merge_base())
|
||||
mocked_gh_fetch_merge_base.assert_called_once()
|
||||
|
||||
def test_app_can_revert(self, *args: Any) -> None:
|
||||
pr = GitHubPR("pytorch", "pytorch", 164660)
|
||||
repo = DummyGitRepo()
|
||||
app_comment_id, impostor_comment_id = 3375785595, 3377647892
|
||||
# Check that app can revert
|
||||
self.assertIsNotNone(validate_revert(repo, pr, comment_id=app_comment_id))
|
||||
# But impostor can not
|
||||
self.assertRaises(
|
||||
PostCommentError,
|
||||
lambda: validate_revert(repo, pr, comment_id=impostor_comment_id),
|
||||
)
|
||||
# Despite it's name being the name of the bot
|
||||
self.assertEqual(
|
||||
pr.get_comment_by_id(impostor_comment_id).author_login,
|
||||
"pytorch-auto-revert",
|
||||
)
|
||||
|
||||
|
||||
@mock.patch("trymerge.gh_graphql", side_effect=mocked_gh_graphql)
|
||||
@mock.patch("trymerge.gh_fetch_merge_base", return_value="")
|
||||
|
||||
7
.github/scripts/trymerge.py
vendored
7
.github/scripts/trymerge.py
vendored
@ -234,7 +234,6 @@ query ($owner: String!, $name: String!, $number: Int!) {
|
||||
createdAt
|
||||
author {
|
||||
login
|
||||
url
|
||||
}
|
||||
authorAssociation
|
||||
editor {
|
||||
@ -1094,7 +1093,6 @@ class GitHubPR:
|
||||
body_text=node["bodyText"],
|
||||
created_at=node["createdAt"] if "createdAt" in node else "",
|
||||
author_login=node["author"]["login"],
|
||||
author_url=node["author"].get("url", None),
|
||||
author_association=node["authorAssociation"],
|
||||
editor_login=editor["login"] if editor else None,
|
||||
database_id=node["databaseId"],
|
||||
@ -2031,11 +2029,6 @@ def validate_revert(
|
||||
# For some reason, one can not be a member of private repo, only CONTRIBUTOR
|
||||
if pr.is_base_repo_private():
|
||||
allowed_reverters.append("CONTRIBUTOR")
|
||||
# Special case the pytorch-auto-revert app, whose does not have association
|
||||
# But should be able to issue revert command
|
||||
if comment.author_url == "https://github.com/apps/pytorch-auto-revert":
|
||||
allowed_reverters.append("NONE")
|
||||
|
||||
if author_association not in allowed_reverters:
|
||||
raise PostCommentError(
|
||||
f"Will not revert as @{author_login} is not one of "
|
||||
|
||||
9
.github/workflows/_get-changed-files.yml
vendored
9
.github/workflows/_get-changed-files.yml
vendored
@ -40,15 +40,6 @@ jobs:
|
||||
# Use gh CLI to get changed files in the PR with explicit repo
|
||||
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
|
||||
|
||||
# See https://github.com/pytorch/pytorch/pull/134215#issuecomment-2332128790
|
||||
PYI_FILES_TO_ADD=""
|
||||
for file in ${CHANGED_FILES}; do
|
||||
if [[ "${file}" == *".pyi.in" ]]; then
|
||||
PYI_FILES_TO_ADD="${PYI_FILES_TO_ADD} ${file//.in/}"
|
||||
fi
|
||||
done
|
||||
CHANGED_FILES="${CHANGED_FILES}${PYI_FILES_TO_ADD}"
|
||||
|
||||
if [ -z "$CHANGED_FILES" ]; then
|
||||
echo "No changed files found, setting to '*'"
|
||||
CHANGED_FILES="*"
|
||||
|
||||
255
.github/workflows/_linux-test-stable-fa3.yml
vendored
255
.github/workflows/_linux-test-stable-fa3.yml
vendored
@ -1,255 +0,0 @@
|
||||
# The point of this workflow is to test that a FA3 wheel that was built based off the
|
||||
# stable ABI as of torch nightly 20250830 can still run on the newer torch.
|
||||
#
|
||||
# This workflow is very similar to the _linux-test.yml workflow, with the following
|
||||
# differences:
|
||||
# 1. It is simpler (there is no test matrix)
|
||||
# 2. It pulls flash-attention as a secondary repository in order to access the tests.
|
||||
# Note that it does not BUILD anything from flash-attention, as we have a prebuilt
|
||||
# wheel. We pull flash-attention only to run a few tests.
|
||||
# 3. It runs only FA3 tests. No PyTorch tests are run.
|
||||
name: linux-test-stable-fa3
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
build-environment:
|
||||
required: true
|
||||
type: string
|
||||
description: Top-level label for what's being built/tested.
|
||||
docker-image:
|
||||
required: true
|
||||
type: string
|
||||
description: Docker image to run in.
|
||||
timeout-minutes:
|
||||
required: false
|
||||
type: number
|
||||
default: 30
|
||||
description: |
|
||||
Set the maximum (in minutes) how long the workflow should take to finish
|
||||
s3-bucket:
|
||||
description: S3 bucket to download artifact
|
||||
required: false
|
||||
type: string
|
||||
default: "gha-artifacts"
|
||||
secrets:
|
||||
HUGGING_FACE_HUB_TOKEN:
|
||||
required: false
|
||||
description: |
|
||||
HF Auth token to avoid rate limits when downloading models or datasets from hub
|
||||
VLLM_TEST_HUGGING_FACE_TOKEN:
|
||||
required: false
|
||||
description: |
|
||||
HF Auth token to test vllm
|
||||
SCRIBE_GRAPHQL_ACCESS_TOKEN:
|
||||
required: false
|
||||
description: |
|
||||
FB app token to write to scribe endpoint
|
||||
|
||||
env:
|
||||
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
|
||||
|
||||
jobs:
|
||||
test:
|
||||
# Don't run on forked repos
|
||||
if: github.repository_owner == 'pytorch'
|
||||
runs-on: linux.aws.h100
|
||||
timeout-minutes: ${{ inputs.timeout-minutes || 30 }}
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
steps:
|
||||
- name: Checkout PyTorch
|
||||
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
|
||||
with:
|
||||
no-sudo: true
|
||||
|
||||
- name: Checkout flash-attention as a secondary repository
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
repository: Dao-AILab/flash-attention
|
||||
path: flash-attention
|
||||
|
||||
- name: Setup Linux
|
||||
uses: ./.github/actions/setup-linux
|
||||
|
||||
- name: Calculate docker image
|
||||
id: calculate-docker-image
|
||||
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
|
||||
with:
|
||||
docker-image-name: ${{ inputs.docker-image }}
|
||||
|
||||
- name: Use following to pull public copy of the image
|
||||
id: print-ghcr-mirror
|
||||
env:
|
||||
ECR_DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
|
||||
shell: bash
|
||||
run: |
|
||||
tag=${ECR_DOCKER_IMAGE##*:}
|
||||
echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
|
||||
|
||||
- name: Pull docker image
|
||||
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
|
||||
with:
|
||||
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
|
||||
|
||||
- name: Check if in a container runner
|
||||
shell: bash
|
||||
id: check_container_runner
|
||||
run: echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
|
||||
|
||||
- name: Setup GPU_FLAG for docker run
|
||||
id: setup-gpu-flag
|
||||
run: echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}"
|
||||
|
||||
- name: Setup SCCACHE_SERVER_PORT environment for docker run when on container
|
||||
id: setup-sscache-port-flag
|
||||
run: echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}"
|
||||
if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'true' }}
|
||||
|
||||
- name: Get workflow job id
|
||||
id: get-job-id
|
||||
uses: ./.github/actions/get-workflow-job-id
|
||||
if: always()
|
||||
with:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Download build artifacts
|
||||
uses: ./.github/actions/download-build-artifacts
|
||||
with:
|
||||
name: ${{ inputs.build-environment }}
|
||||
s3-bucket: ${{ inputs.s3-bucket }}
|
||||
|
||||
- name: Parse ref
|
||||
id: parse-ref
|
||||
run: .github/scripts/parse_ref.py
|
||||
|
||||
- name: Set Test step time
|
||||
id: test-timeout
|
||||
shell: bash
|
||||
env:
|
||||
JOB_TIMEOUT: ${{ inputs.timeout-minutes }}
|
||||
run: |
|
||||
echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
|
||||
|
||||
- name: Preserve github env variables for use in docker
|
||||
shell: bash
|
||||
run: |
|
||||
env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
|
||||
env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
|
||||
|
||||
- name: Test
|
||||
id: test
|
||||
timeout-minutes: ${{ fromJson(steps.test-timeout.outputs.timeout) }}
|
||||
env:
|
||||
BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
|
||||
PR_NUMBER: ${{ github.event.pull_request.number }}
|
||||
GITHUB_REPOSITORY: ${{ github.repository }}
|
||||
GITHUB_WORKFLOW: ${{ github.workflow }}
|
||||
GITHUB_JOB: ${{ github.job }}
|
||||
GITHUB_RUN_ID: ${{ github.run_id }}
|
||||
GITHUB_RUN_NUMBER: ${{ github.run_number }}
|
||||
GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
|
||||
JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
|
||||
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
|
||||
BRANCH: ${{ steps.parse-ref.outputs.branch }}
|
||||
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
|
||||
BASE_SHA: ${{ github.event.pull_request.base.sha || github.sha }}
|
||||
SHM_SIZE: '2g'
|
||||
DOCKER_IMAGE: ${{ inputs.docker-image }}
|
||||
VLLM_TEST_HUGGING_FACE_TOKEN: ${{ secrets.VLLM_TEST_HUGGING_FACE_TOKEN }}
|
||||
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
|
||||
SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.SCRIBE_GRAPHQL_ACCESS_TOKEN }}
|
||||
ARTIFACTS_FILE_SUFFIX: ${{ github.job }}-${{ steps.get-job-id.outputs.job-id }}
|
||||
run: |
|
||||
set -x
|
||||
|
||||
TEST_COMMAND=.ci/pytorch/test_fa3_abi_stable.sh
|
||||
|
||||
# Leaving 1GB for the runner and other things
|
||||
TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo)
|
||||
# https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap
|
||||
# comes from https://github.com/pytorch/test-infra/pull/6058
|
||||
TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3))
|
||||
|
||||
|
||||
SHM_OPTS="--shm-size=${SHM_SIZE}"
|
||||
JENKINS_USER="--user jenkins"
|
||||
DOCKER_SHELL_CMD=
|
||||
|
||||
# detached container should get cleaned up by teardown_ec2_linux
|
||||
# TODO: Stop building test binaries as part of the build phase
|
||||
# Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice
|
||||
# shellcheck disable=SC2086,SC2090
|
||||
container_name=$(docker run \
|
||||
${GPU_FLAG:-} \
|
||||
${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \
|
||||
-e BUILD_ENVIRONMENT \
|
||||
-e PR_NUMBER \
|
||||
-e GITHUB_ACTIONS \
|
||||
-e GITHUB_REPOSITORY \
|
||||
-e GITHUB_WORKFLOW \
|
||||
-e GITHUB_JOB \
|
||||
-e GITHUB_RUN_ID \
|
||||
-e GITHUB_RUN_NUMBER \
|
||||
-e GITHUB_RUN_ATTEMPT \
|
||||
-e JOB_ID \
|
||||
-e JOB_NAME \
|
||||
-e BASE_SHA \
|
||||
-e BRANCH \
|
||||
-e SHA1 \
|
||||
-e MAX_JOBS="$(nproc --ignore=2)" \
|
||||
-e HUGGING_FACE_HUB_TOKEN \
|
||||
-e VLLM_TEST_HUGGING_FACE_TOKEN \
|
||||
-e SCRIBE_GRAPHQL_ACCESS_TOKEN \
|
||||
-e ARTIFACTS_FILE_SUFFIX \
|
||||
--memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
|
||||
--memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
|
||||
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
|
||||
--security-opt seccomp=unconfined \
|
||||
--cap-add=SYS_PTRACE \
|
||||
--ipc=host \
|
||||
${SHM_OPTS} \
|
||||
--tty \
|
||||
--detach \
|
||||
--name="${container_name}" \
|
||||
${JENKINS_USER} \
|
||||
-v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
|
||||
-w /var/lib/jenkins/workspace \
|
||||
"${DOCKER_IMAGE}" \
|
||||
${DOCKER_SHELL_CMD}
|
||||
)
|
||||
|
||||
echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
|
||||
|
||||
docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"
|
||||
|
||||
- name: Collect backtraces from coredumps (if any)
|
||||
if: always()
|
||||
run: |
|
||||
# shellcheck disable=SC2156
|
||||
find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
|
||||
|
||||
- name: Store Core dumps on S3
|
||||
uses: seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a # v5.1.0
|
||||
if: failure()
|
||||
with:
|
||||
name: coredumps-fa3-stable-abi-smoke-tests
|
||||
retention-days: 14
|
||||
if-no-files-found: ignore
|
||||
path: ./**/core.[1-9]*
|
||||
|
||||
- name: Upload utilization stats
|
||||
if: ${{ always() && steps.test.conclusion && steps.test.conclusion != 'skipped' }}
|
||||
continue-on-error: true
|
||||
uses: ./.github/actions/upload-utilization-stats
|
||||
with:
|
||||
job_id: ${{ steps.get-job-id.outputs.job-id }}
|
||||
job_name: ${{ steps.get-job-id.outputs.job-name }}
|
||||
workflow_name: ${{ github.workflow }}
|
||||
workflow_run_id: ${{github.run_id}}
|
||||
workflow_attempt: ${{github.run_attempt}}
|
||||
|
||||
- name: Teardown Linux
|
||||
uses: pytorch/test-infra/.github/actions/teardown-linux@main
|
||||
if: always() && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false'
|
||||
2
.github/workflows/_mac-build.yml
vendored
2
.github/workflows/_mac-build.yml
vendored
@ -85,7 +85,7 @@ jobs:
|
||||
uses: pytorch/test-infra/.github/actions/setup-python@main
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
pip-requirements-file: .ci/docker/requirements-ci.txt
|
||||
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
|
||||
|
||||
- name: Install sccache (only for non-forked PRs, and pushes to trunk)
|
||||
uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
|
||||
|
||||
2
.github/workflows/_mac-test.yml
vendored
2
.github/workflows/_mac-test.yml
vendored
@ -122,7 +122,7 @@ jobs:
|
||||
uses: pytorch/test-infra/.github/actions/setup-python@main
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
pip-requirements-file: .ci/docker/requirements-ci.txt
|
||||
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
|
||||
|
||||
- name: Start monitoring script
|
||||
id: monitor-script
|
||||
|
||||
3
.github/workflows/_win-build.yml
vendored
3
.github/workflows/_win-build.yml
vendored
@ -84,6 +84,9 @@ jobs:
|
||||
# in https://github.com/actions/checkout/issues/1018
|
||||
git config --global core.fsmonitor false
|
||||
|
||||
- name: Clean up leftover processes on non-ephemeral Windows runner
|
||||
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
|
||||
|
||||
- name: Setup SSH (Click me for login details)
|
||||
uses: pytorch/test-infra/.github/actions/setup-ssh@main
|
||||
with:
|
||||
|
||||
24
.github/workflows/_win-test.yml
vendored
24
.github/workflows/_win-test.yml
vendored
@ -77,6 +77,9 @@ jobs:
|
||||
# in https://github.com/actions/checkout/issues/1018
|
||||
git config --global core.fsmonitor false
|
||||
|
||||
- name: Clean up leftover processes on non-ephemeral Windows runner
|
||||
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
|
||||
|
||||
- name: Setup SSH (Click me for login details)
|
||||
uses: pytorch/test-infra/.github/actions/setup-ssh@main
|
||||
with:
|
||||
@ -103,6 +106,18 @@ jobs:
|
||||
with:
|
||||
cuda-version: ${{ inputs.cuda-version }}
|
||||
|
||||
# TODO: Move to a requirements.txt file for windows
|
||||
- name: Install pip dependencies
|
||||
uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
|
||||
with:
|
||||
shell: bash
|
||||
timeout_minutes: 5
|
||||
max_attempts: 5
|
||||
retry_wait_seconds: 30
|
||||
command: |
|
||||
set -eu
|
||||
python3 -m pip install 'xdoctest>=1.1.0'
|
||||
|
||||
- name: Get workflow job id
|
||||
id: get-job-id
|
||||
uses: ./.github/actions/get-workflow-job-id
|
||||
@ -257,6 +272,15 @@ jobs:
|
||||
shell: bash
|
||||
run: python3 .github/scripts/parse_ref.py
|
||||
|
||||
- name: Uninstall PyTorch
|
||||
if: always()
|
||||
continue-on-error: true
|
||||
shell: bash
|
||||
run: |
|
||||
# This step removes PyTorch installed by the test to give a clean slate
|
||||
# to the next job
|
||||
python3 -mpip uninstall -y torch
|
||||
|
||||
- name: Teardown Windows
|
||||
uses: ./.github/actions/teardown-win
|
||||
if: always()
|
||||
|
||||
2
.github/workflows/_xpu-test.yml
vendored
2
.github/workflows/_xpu-test.yml
vendored
@ -275,7 +275,7 @@ jobs:
|
||||
- name: Change permissions
|
||||
if: ${{ always() && steps.test.conclusion }}
|
||||
run: |
|
||||
docker exec -t "${{ env.CONTAINER_NAME }}" sh -c "sudo chown -R jenkins:jenkins test"
|
||||
docker exec -t "${{ env.CONTAINER_NAME }}" sh -c "sudo chown -R 1000:1000 test"
|
||||
|
||||
- name: Print remaining test logs
|
||||
shell: bash
|
||||
|
||||
42
.github/workflows/generated-linux-aarch64-binary-manywheel-nightly.yml
generated
vendored
42
.github/workflows/generated-linux-aarch64-binary-manywheel-nightly.yml
generated
vendored
@ -132,7 +132,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_10-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -178,7 +178,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_10-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -224,7 +224,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_10-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -335,7 +335,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_11-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -381,7 +381,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_11-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -427,7 +427,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_11-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -538,7 +538,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_12-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -584,7 +584,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_12-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -630,7 +630,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_12-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -741,7 +741,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -787,7 +787,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -833,7 +833,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -944,7 +944,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13t-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -990,7 +990,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13t-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1036,7 +1036,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_13t-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1147,7 +1147,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1193,7 +1193,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1239,7 +1239,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1350,7 +1350,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14t-cuda-aarch64-12_6
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1396,7 +1396,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14t-cuda-aarch64-12_8
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
@ -1442,7 +1442,7 @@ jobs:
|
||||
ALPINE_IMAGE: "arm64v8/alpine"
|
||||
build_name: manywheel-py3_14t-cuda-aarch64-13_0
|
||||
build_environment: linux-aarch64-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
timeout-minutes: 420
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
42
.github/workflows/generated-linux-binary-manywheel-nightly.yml
generated
vendored
42
.github/workflows/generated-linux-binary-manywheel-nightly.yml
generated
vendored
@ -127,7 +127,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_10-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_10-cuda12_6-test: # Testing
|
||||
@ -193,7 +193,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_10-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_10-cuda12_8-test: # Testing
|
||||
@ -259,7 +259,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_10-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_10-cuda13_0-test: # Testing
|
||||
@ -721,7 +721,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_11-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_11-cuda12_6-test: # Testing
|
||||
@ -787,7 +787,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_11-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_11-cuda12_8-test: # Testing
|
||||
@ -853,7 +853,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_11-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_11-cuda13_0-test: # Testing
|
||||
@ -1315,7 +1315,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_12-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_12-cuda12_6-test: # Testing
|
||||
@ -1381,7 +1381,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_12-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_12-cuda12_8-test: # Testing
|
||||
@ -1447,7 +1447,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_12-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_12-cuda13_0-test: # Testing
|
||||
@ -1909,7 +1909,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13-cuda12_6-test: # Testing
|
||||
@ -1975,7 +1975,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13-cuda12_8-test: # Testing
|
||||
@ -2041,7 +2041,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13-cuda13_0-test: # Testing
|
||||
@ -2503,7 +2503,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13t-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13t-cuda12_6-test: # Testing
|
||||
@ -2569,7 +2569,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13t-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13t-cuda12_8-test: # Testing
|
||||
@ -2635,7 +2635,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_13t-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_13t-cuda13_0-test: # Testing
|
||||
@ -3097,7 +3097,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14-cuda12_6-test: # Testing
|
||||
@ -3163,7 +3163,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14-cuda12_8-test: # Testing
|
||||
@ -3229,7 +3229,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14-cuda13_0-test: # Testing
|
||||
@ -3691,7 +3691,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14t-cuda12_6
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14t-cuda12_6-test: # Testing
|
||||
@ -3757,7 +3757,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14t-cuda12_8
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14t-cuda12_8-test: # Testing
|
||||
@ -3823,7 +3823,7 @@ jobs:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build_name: manywheel-py3_14t-cuda13_0
|
||||
build_environment: linux-binary-manywheel
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
|
||||
secrets:
|
||||
github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
manywheel-py3_14t-cuda13_0-test: # Testing
|
||||
|
||||
@ -2,7 +2,7 @@ name: inductor-perf-nightly-h100
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: 15 0 * * 1-6
|
||||
- cron: 15 0,12 * * 1-6
|
||||
- cron: 0 7 * * 0
|
||||
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
|
||||
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
|
||||
|
||||
@ -63,7 +63,6 @@ jobs:
|
||||
# Same as the build job
|
||||
python-version: 3.12.7
|
||||
test-matrix: ${{ needs.macos-perf-py3-arm64-build.outputs.test-matrix }}
|
||||
timeout-minutes: 300
|
||||
disable-monitor: false
|
||||
monitor-log-interval: 15
|
||||
monitor-data-collect-interval: 4
|
||||
|
||||
10
.github/workflows/inductor-periodic.yml
vendored
10
.github/workflows/inductor-periodic.yml
vendored
@ -106,16 +106,6 @@ jobs:
|
||||
{ config: "dynamic_aot_eager_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_aot_eager_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_aot_eager_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_inductor_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_inductor_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "dynamic_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "aot_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "aot_inductor_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "aot_inductor_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "aot_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "aot_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
|
||||
54
.github/workflows/operator_microbenchmark.yml
vendored
54
.github/workflows/operator_microbenchmark.yml
vendored
@ -18,7 +18,6 @@ permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
# H100 A100 runners
|
||||
opmicrobenchmark-build:
|
||||
if: github.repository_owner == 'pytorch'
|
||||
name: opmicrobenchmark-build
|
||||
@ -45,56 +44,3 @@ jobs:
|
||||
docker-image: ${{ needs.opmicrobenchmark-build.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.opmicrobenchmark-build.outputs.test-matrix }}
|
||||
secrets: inherit
|
||||
|
||||
# B200 runner
|
||||
opmicrobenchmark-build-b200:
|
||||
if: github.repository_owner == 'pytorch'
|
||||
name: opmicrobenchmark-build-b200
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
with:
|
||||
runner: linux.12xlarge.memory
|
||||
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm100
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
|
||||
cuda-arch-list: '10.0'
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "operator_microbenchmark_test", shard: 1, num_shards: 1, runner: "linux.dgx.b200" },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
opmicrobenchmark-test-b200:
|
||||
name: opmicrobenchmark-test-b200
|
||||
uses: ./.github/workflows/_linux-test.yml
|
||||
needs: opmicrobenchmark-build-b200
|
||||
with:
|
||||
timeout-minutes: 500
|
||||
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm100
|
||||
docker-image: ${{ needs.opmicrobenchmark-build-b200.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.opmicrobenchmark-build-b200.outputs.test-matrix }}
|
||||
aws-role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
|
||||
secrets: inherit
|
||||
|
||||
# ROCM MI300 runner
|
||||
opmicrobenchmark-build-rocm:
|
||||
if: github.repository_owner == 'pytorch'
|
||||
name: opmicrobenchmark-build-rocm
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
with:
|
||||
build-environment: linux-jammy-rocm-py3_10
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3-benchmarks
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "operator_microbenchmark_test", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
opmicrobenchmark-test-rocm:
|
||||
name: opmicrobenchmark-test-rocm
|
||||
uses: ./.github/workflows/_rocm-test.yml
|
||||
needs: opmicrobenchmark-build-rocm
|
||||
with:
|
||||
timeout-minutes: 500
|
||||
build-environment: linux-jammy-rocm-py3_10
|
||||
docker-image: ${{ needs.opmicrobenchmark-build-rocm.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.opmicrobenchmark-build-rocm.outputs.test-matrix }}
|
||||
secrets: inherit
|
||||
|
||||
6
.github/workflows/periodic.yml
vendored
6
.github/workflows/periodic.yml
vendored
@ -213,9 +213,9 @@ jobs:
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
|
||||
3
.github/workflows/pull.yml
vendored
3
.github/workflows/pull.yml
vendored
@ -127,8 +127,9 @@ jobs:
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
needs: get-label-type
|
||||
with:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
# More memory is needed to build with asan
|
||||
runner: linux.2xlarge.memory
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build-environment: linux-jammy-py3.10-clang18-asan
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-py3-clang18-asan
|
||||
test-matrix: |
|
||||
|
||||
26
.github/workflows/rocm.yml
vendored
26
.github/workflows/rocm.yml
vendored
@ -59,29 +59,3 @@ jobs:
|
||||
docker-image: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.test-matrix }}
|
||||
secrets: inherit
|
||||
|
||||
linux-jammy-rocm-py3_10-gfx1100-test:
|
||||
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }}
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
name: linux-jammy-rocm-py3_10-gfx1100
|
||||
uses: ./.github/workflows/_rocm-test.yml
|
||||
needs:
|
||||
- linux-jammy-rocm-py3_10-build
|
||||
- target-determination
|
||||
with:
|
||||
build-environment: linux-jammy-rocm-py3.10
|
||||
docker-image: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.docker-image }}
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "default", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx1100" },
|
||||
{ config: "default", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx1100" },
|
||||
]}
|
||||
tests-to-include: >
|
||||
test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs
|
||||
test_autograd inductor/test_torchinductor inductor/test_kernel_benchmark
|
||||
inductor/test_pad_mm inductor/test_benchmark_fusion inductor/test_aot_inductor
|
||||
inductor/test_torchinductor inductor/test_decompose_mem_bound_mm
|
||||
inductor/test_flex_attention inductor/test_max_autotune
|
||||
secrets: inherit
|
||||
|
||||
2
.github/workflows/slow.yml
vendored
2
.github/workflows/slow.yml
vendored
@ -140,6 +140,8 @@ jobs:
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
needs: get-label-type
|
||||
with:
|
||||
# More memory is needed to build with asan
|
||||
runner: linux.2xlarge.memory
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build-environment: linux-jammy-py3.10-clang18-asan
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-py3-clang18-asan
|
||||
|
||||
12
.github/workflows/test-h100.yml
vendored
12
.github/workflows/test-h100.yml
vendored
@ -61,15 +61,3 @@ jobs:
|
||||
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm90-build.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm90-build.outputs.test-matrix }}
|
||||
secrets: inherit
|
||||
|
||||
linux-jammy-cuda12_8-py3_10-gcc11-sm90-FA3-ABI-stable-test:
|
||||
name: linux-jammy-cuda12_8-py3_10-gcc11-sm90-FA3-ABI-stable-test
|
||||
uses: ./.github/workflows/_linux-test-stable-fa3.yml
|
||||
needs:
|
||||
- linux-jammy-cuda12_8-py3_10-gcc11-sm90-build
|
||||
with:
|
||||
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm90
|
||||
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm90-build.outputs.docker-image }}
|
||||
timeout-minutes: 30
|
||||
s3-bucket: gha-artifacts
|
||||
secrets: inherit
|
||||
|
||||
42
.github/workflows/trunk.yml
vendored
42
.github/workflows/trunk.yml
vendored
@ -160,10 +160,9 @@ jobs:
|
||||
runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "default", shard: 1, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
|
||||
{ config: "default", shard: 2, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
|
||||
{ config: "default", shard: 3, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
|
||||
{ config: "default", shard: 4, num_shards: 4, runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
|
||||
{ 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: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral" },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
@ -190,6 +189,41 @@ jobs:
|
||||
runner: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
|
||||
secrets: inherit
|
||||
|
||||
linux-jammy-rocm-py3_10-build:
|
||||
if: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/trunk') }}
|
||||
name: linux-jammy-rocm-py3.10
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
needs: get-label-type
|
||||
with:
|
||||
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
|
||||
build-environment: linux-jammy-rocm-py3.10
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3
|
||||
sync-tag: rocm-build
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
{ config: "default", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "default", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
|
||||
{ config: "distributed", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.4" },
|
||||
]}
|
||||
secrets: inherit
|
||||
|
||||
linux-jammy-rocm-py3_10-test:
|
||||
if: ${{ startsWith(github.event.ref, 'refs/tags/ciflow/trunk') }}
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
name: linux-jammy-rocm-py3.10
|
||||
uses: ./.github/workflows/_rocm-test.yml
|
||||
needs:
|
||||
- linux-jammy-rocm-py3_10-build
|
||||
- target-determination
|
||||
with:
|
||||
build-environment: linux-jammy-rocm-py3.10
|
||||
docker-image: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.docker-image }}
|
||||
test-matrix: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.test-matrix }}
|
||||
tests-to-include: "test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor distributed/test_c10d_common distributed/test_c10d_nccl"
|
||||
secrets: inherit
|
||||
|
||||
inductor-build:
|
||||
name: inductor-build
|
||||
uses: ./.github/workflows/_linux-build.yml
|
||||
|
||||
5
.github/workflows/update-viablestrict.yml
vendored
5
.github/workflows/update-viablestrict.yml
vendored
@ -23,7 +23,7 @@ jobs:
|
||||
with:
|
||||
repository: pytorch/pytorch
|
||||
stable-branch: viable/strict
|
||||
requires: '[\"pull\", \"trunk\", \"lint\", \"linux-aarch64\"]'
|
||||
requires: '[\"pull\", \"trunk\", \"lint\", \"^linux-binary-manywheel$\", \"^linux-binary-libtorch-release$\", \"linux-aarch64\"]'
|
||||
secret-bot-token: ${{ secrets.MERGEBOT_TOKEN }}
|
||||
clickhouse-url: ${{ secrets.CLICKHOUSE_URL }}
|
||||
clickhouse-username: ${{ secrets.CLICKHOUSE_VIABLESTRICT_USERNAME }}
|
||||
@ -48,7 +48,4 @@ jobs:
|
||||
echo "{\"sha\": \"${LATEST_SHA}\", \"repository\":\"pytorch/pytorch\", \"timestamp\": ${TIME}}" > "/tmp/${LATEST_SHA}.json"
|
||||
pip install awscli==1.29.40
|
||||
aws s3 cp "/tmp/${LATEST_SHA}.json" "s3://ossci-raw-job-status/stable_pushes/pytorch/pytorch/${LATEST_SHA}.json"
|
||||
# Push new viable/strict tag
|
||||
cd pytorch/pytorch
|
||||
git push origin "${LATEST_SHA}:refs/tags/viable/strict/${TIME}"
|
||||
fi
|
||||
|
||||
2
.github/workflows/vllm.yml
vendored
2
.github/workflows/vllm.yml
vendored
@ -42,7 +42,7 @@ jobs:
|
||||
build-external-packages: "vllm"
|
||||
build-environment: linux-jammy-cuda12.8-py3.12-gcc11
|
||||
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc11-vllm
|
||||
cuda-arch-list: '8.0 8.9 9.0'
|
||||
cuda-arch-list: '8.0;8.9;9.0'
|
||||
runner: linux.24xlarge.memory
|
||||
test-matrix: |
|
||||
{ include: [
|
||||
|
||||
2
.gitignore
vendored
2
.gitignore
vendored
@ -88,7 +88,7 @@ torch_compile_debug/
|
||||
# Listed manually because some files in this directory are not generated
|
||||
torch/testing/_internal/generated/annotated_fn_args.py
|
||||
torch/testing/_internal/data/*.pt
|
||||
torch/headeronly/version.h
|
||||
torch/csrc/api/include/torch/version.h
|
||||
torch/csrc/cudnn/cuDNN.cpp
|
||||
torch/csrc/generated
|
||||
torch/csrc/generic/TensorMethods.cpp
|
||||
|
||||
@ -18,7 +18,6 @@ exclude_patterns = [
|
||||
'torch/_inductor/autoheuristic/artifacts/**',
|
||||
'scripts/**',
|
||||
'test/generated_type_hints_smoketest.py',
|
||||
'test/test_torchfuzz_repros.py',
|
||||
# CPython tests
|
||||
'test/dynamo/cpython/**',
|
||||
# Tests from the NumPy test suite
|
||||
@ -28,7 +27,6 @@ exclude_patterns = [
|
||||
'torch/lib/**',
|
||||
'venv/**',
|
||||
'**/*.pyi',
|
||||
"tools/experimental/torchfuzz/**",
|
||||
'tools/test/test_selective_build.py',
|
||||
]
|
||||
command = [
|
||||
@ -198,7 +196,7 @@ exclude_patterns = [
|
||||
'tools/test/gen_operators_yaml_test.py',
|
||||
'tools/test/gen_oplist_test.py',
|
||||
'tools/test/test_selective_build.py',
|
||||
'tools/experimental/torchfuzz/**',
|
||||
'tools/experimental/dynamic_shapes/torchfuzz/**',
|
||||
]
|
||||
command = [
|
||||
'python3',
|
||||
@ -1262,7 +1260,6 @@ exclude_patterns = [
|
||||
'test/test_masked.py',
|
||||
'test/test_maskedtensor.py',
|
||||
'test/test_matmul_cuda.py',
|
||||
'test/test_scaled_matmul_cuda.py',
|
||||
'test/test_meta.py',
|
||||
'test/test_metal.py',
|
||||
'test/test_mkl_verbose.py',
|
||||
@ -1573,7 +1570,6 @@ exclude_patterns = [
|
||||
'torch/_inductor/fx_passes/serialized_patterns/**',
|
||||
'torch/_inductor/autoheuristic/artifacts/**',
|
||||
'test/dynamo/cpython/**',
|
||||
'test/test_torchfuzz_repros.py',
|
||||
'scripts/**',
|
||||
'third_party/**',
|
||||
'fb/**',
|
||||
|
||||
@ -13,9 +13,6 @@ load(":build_variables.bzl", "jit_core_sources", "lazy_tensor_ts_sources", "libt
|
||||
load(":ufunc_defs.bzl", "aten_ufunc_generated_cpu_kernel_sources", "aten_ufunc_generated_cpu_sources", "aten_ufunc_generated_cuda_sources")
|
||||
load("//:tools/bazel.bzl", "rules")
|
||||
|
||||
# Export files for use by torch/headeronly (where version.h generation now lives)
|
||||
exports_files(["version.txt"])
|
||||
|
||||
define_targets(rules = rules)
|
||||
|
||||
COMMON_COPTS = [
|
||||
@ -693,9 +690,7 @@ cc_library(
|
||||
"torch/csrc/*/generated/*.h",
|
||||
"torch/csrc/jit/serialization/mobile_bytecode_generated.h",
|
||||
] + torch_cuda_headers,
|
||||
) + GENERATED_AUTOGRAD_CPP + [
|
||||
"//torch/headeronly:version_h",
|
||||
],
|
||||
) + GENERATED_AUTOGRAD_CPP + [":version_h"],
|
||||
includes = [
|
||||
"third_party/kineto/libkineto/include",
|
||||
"torch/csrc",
|
||||
|
||||
18
CODEOWNERS
18
CODEOWNERS
@ -181,15 +181,15 @@ caffe2/utils/hip @jeffdaily @jithunnair-amd
|
||||
/torch/csrc/jit/python/init.cpp @mikaylagawarecki
|
||||
|
||||
# CUDA and CUDA math libraries
|
||||
aten/src/ATen/cuda/ @eqy @syed-ahmed @Aidyn-A
|
||||
aten/src/ATen/cudnn/ @eqy @syed-ahmed @Aidyn-A
|
||||
aten/src/ATen/native/cuda/ @eqy @syed-ahmed @Aidyn-A
|
||||
aten/src/ATen/native/cudnn/ @eqy @syed-ahmed @Aidyn-A
|
||||
c10/cuda @eqy @syed-ahmed @Aidyn-A
|
||||
torch/cuda/ @eqy @syed-ahmed @Aidyn-A
|
||||
torch/csrc/cuda/ @eqy @syed-ahmed @Aidyn-A
|
||||
torch/backends/cuda/ @eqy @syed-ahmed @Aidyn-A
|
||||
torch/backends/cudnn/ @eqy @syed-ahmed @Aidyn-A
|
||||
aten/src/ATen/cuda/ @eqy @syed-ahmed
|
||||
aten/src/ATen/cudnn/ @eqy @syed-ahmed
|
||||
aten/src/ATen/native/cuda/ @eqy @syed-ahmed
|
||||
aten/src/ATen/native/cudnn/ @eqy @syed-ahmed
|
||||
c10/cuda @eqy @syed-ahmed
|
||||
torch/cuda/ @eqy @syed-ahmed
|
||||
torch/csrc/cuda/ @eqy @syed-ahmed
|
||||
torch/backends/cuda/ @eqy @syed-ahmed
|
||||
torch/backends/cudnn/ @eqy @syed-ahmed
|
||||
|
||||
# PyTree utilities
|
||||
/torch/utils/_pytree.py @XuehaiPan
|
||||
|
||||
@ -81,7 +81,7 @@ git remote add upstream git@github.com:pytorch/pytorch.git
|
||||
make setup-env
|
||||
# Or run `make setup-env-cuda` for pre-built CUDA binaries
|
||||
# Or run `make setup-env-rocm` for pre-built ROCm binaries
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
|
||||
```
|
||||
|
||||
### Tips and Debugging
|
||||
@ -182,36 +182,28 @@ You can use this script to check out a new nightly branch with the following:
|
||||
|
||||
```bash
|
||||
./tools/nightly.py checkout -b my-nightly-branch
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
|
||||
```
|
||||
|
||||
To install the nightly binaries built with CUDA, you can pass in the flag `--cuda`:
|
||||
|
||||
```bash
|
||||
./tools/nightly.py checkout -b my-nightly-branch --cuda
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
|
||||
```
|
||||
|
||||
To install the nightly binaries built with ROCm, you can pass in the flag `--rocm`:
|
||||
|
||||
```bash
|
||||
./tools/nightly.py checkout -b my-nightly-branch --rocm
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
|
||||
```
|
||||
|
||||
You can also use this tool to pull the nightly commits into the current branch:
|
||||
|
||||
```bash
|
||||
./tools/nightly.py pull
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
```
|
||||
|
||||
To create the virtual environment with a specific Python interpreter, you can
|
||||
pass in the `--python` argument:
|
||||
|
||||
```bash
|
||||
./tools/nightly.py --python /path/to/python3.12
|
||||
source venv/bin/activate # or `. .\venv\Scripts\activate` on Windows
|
||||
./tools/nightly.py pull -p my-env
|
||||
source my-env/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
|
||||
```
|
||||
|
||||
Pulling will recreate a fresh virtual environment and reinstall the development
|
||||
|
||||
@ -50,10 +50,11 @@ RUN git submodule update --init --recursive
|
||||
FROM conda as conda-installs
|
||||
ARG PYTHON_VERSION=3.11
|
||||
ARG CUDA_PATH=cu121
|
||||
ARG CUDA_CHANNEL=nvidia
|
||||
ARG INSTALL_CHANNEL=whl/nightly
|
||||
# Automatically set by buildx
|
||||
# pinning version of conda here see: https://github.com/pytorch/pytorch/issues/164574
|
||||
RUN /opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda=25.7.0
|
||||
RUN /opt/conda/bin/conda update -y -n base -c defaults conda
|
||||
RUN /opt/conda/bin/conda install -y python=${PYTHON_VERSION}
|
||||
|
||||
ARG TARGETPLATFORM
|
||||
|
||||
|
||||
17
RELEASE.md
17
RELEASE.md
@ -3,7 +3,6 @@
|
||||
<!-- toc -->
|
||||
|
||||
- [Release Compatibility Matrix](#release-compatibility-matrix)
|
||||
- [PyTorch CUDA Support Matrix](#pytorch-cuda-support-matrix)
|
||||
- [Release Cadence](#release-cadence)
|
||||
- [General Overview](#general-overview)
|
||||
- [Frequently Asked Questions](#frequently-asked-questions)
|
||||
@ -64,22 +63,6 @@ Following is the Release Compatibility Matrix for PyTorch releases:
|
||||
| 1.13 | >=3.7, <=3.10 | C++14 | CUDA 11.6, CUDNN 8.3.2.44 | CUDA 11.7, CUDNN 8.5.0.96 | ROCm 5.2 |
|
||||
| 1.12 | >=3.7, <=3.10 | C++14 | CUDA 11.3, CUDNN 8.3.2.44 | CUDA 11.6, CUDNN 8.3.2.44 | ROCm 5.0 |
|
||||
|
||||
### PyTorch CUDA Support Matrix
|
||||
|
||||
For Release 2.9 PyTorch Supports following CUDA Architectures:
|
||||
|
||||
| CUDA | architectures supported for Linux x86 and Windows builds | notes |
|
||||
| --- | --- | --- |
|
||||
| 12.6.3 | Maxwell(5.0), Pascal(6.0), Volta(7.0), Turing(7.5), Ampere(8.0, 8.6), Hopper(9.0) | |
|
||||
| 12.8.1 | Volta(7.0), Turing(7.5), Ampere(8.0, 8.6), Hopper(9.0), Blackwell(10.0, 12.0) | |
|
||||
| 13.0.0 | Turing(7.5), Ampere(8.0, 8.6), Hopper(9.0), Blackwell(10.0, 12.0+PTX) | +PTX available on linux builds only |
|
||||
|
||||
| CUDA | architectures supported for Linux aarch64 builds |
|
||||
| --- | --- |
|
||||
| 12.6.3 | Ampere(8.0), Hopper(9.0) |
|
||||
| 12.8.1 | Ampere(8.0), Hopper(9.0), Blackwell(10.0, 12.0) |
|
||||
| 13.0.0 | Ampere(8.0), Hopper(9.0), Blackwell(10.0, 11.0, 12.0+PTX) |
|
||||
|
||||
## Release Cadence
|
||||
|
||||
Following is the release cadence. All future dates below are tentative. For latest updates on the release schedule, please follow [dev discuss](https://dev-discuss.pytorch.org/c/release-announcements/27). Please note: Patch Releases are optional.
|
||||
|
||||
@ -605,11 +605,6 @@ if(UNIX)
|
||||
if(HAVE_MALLOC_USABLE_SIZE)
|
||||
add_definitions(-DHAVE_MALLOC_USABLE_SIZE=1)
|
||||
endif(HAVE_MALLOC_USABLE_SIZE)
|
||||
set(CMAKE_EXTRA_INCLUDE_FILES "fcntl.h")
|
||||
CHECK_FUNCTION_EXISTS(posix_fallocate HAVE_POSIX_FALLOCATE)
|
||||
if(HAVE_POSIX_FALLOCATE)
|
||||
add_definitions(-DHAVE_POSIX_FALLOCATE=1)
|
||||
endif(HAVE_POSIX_FALLOCATE)
|
||||
endif(UNIX)
|
||||
|
||||
ADD_DEFINITIONS(-DUSE_EXTERNAL_MZCRC)
|
||||
|
||||
@ -144,7 +144,8 @@ inline std::string _all_equal_numel_error(at::ArrayRef<Tensor> tensors) {
|
||||
inline bool _apply_preamble(ArrayRef<Tensor> tensors) {
|
||||
checkDeviceType("CPU_tensor_apply", tensors, kCPU);
|
||||
checkLayout("CPU_tensor_apply", tensors, kStrided);
|
||||
TORCH_CHECK(_all_equal_numel(tensors), _all_equal_numel_error(tensors));
|
||||
if (!_all_equal_numel(tensors))
|
||||
TORCH_CHECK(false, _all_equal_numel_error(tensors));
|
||||
// An empty tensor has no elements
|
||||
for (auto& t : tensors)
|
||||
if (t.numel() == 0)
|
||||
|
||||
@ -40,6 +40,41 @@ namespace {
|
||||
->conv
|
||||
->rnn
|
||||
*/
|
||||
const std::map<std::string, std::vector<std::string>> _fp32_precisions = {
|
||||
{"generic", {{"ieee", "tf32", "bf16", "none"}}},
|
||||
{"mkldnn", {{"ieee", "tf32", "bf16", "none"}}},
|
||||
{"cuda", {{"ieee", "tf32", "none"}}}};
|
||||
|
||||
// Check whether the backend and op are legal
|
||||
void check_fp32_prec_backend_and_op(
|
||||
const std::string& backend,
|
||||
const std::string& op) {
|
||||
static std::vector<std::string> backends = {"generic", "mkldnn", "cuda"};
|
||||
static std::vector<std::string> operators = {"conv", "matmul", "rnn", "all"};
|
||||
TORCH_CHECK(
|
||||
std::find(backends.begin(), backends.end(), backend) != backends.end(),
|
||||
"Invalid backend: ",
|
||||
backend);
|
||||
TORCH_CHECK(
|
||||
std::find(operators.begin(), operators.end(), op) != operators.end(),
|
||||
"Invalid operator: ",
|
||||
op);
|
||||
if (backend == "generic") {
|
||||
TORCH_CHECK(op == "all", "Invalid operation for generic backend: ", op);
|
||||
}
|
||||
}
|
||||
|
||||
// Return whether the precision is supported by backends
|
||||
bool validate_fp32_prec(
|
||||
const std::string& backend,
|
||||
const std::string& precision) {
|
||||
auto iterp = _fp32_precisions.find(backend);
|
||||
TORCH_CHECK(iterp != _fp32_precisions.end());
|
||||
auto precisions = iterp->second;
|
||||
bool valid = std::find(precisions.begin(), precisions.end(), precision) !=
|
||||
precisions.end();
|
||||
return valid;
|
||||
}
|
||||
|
||||
C10_ALWAYS_INLINE void warn_deprecated_fp32_precision_api(){
|
||||
TORCH_WARN_ONCE(
|
||||
@ -51,54 +86,6 @@ namespace {
|
||||
}
|
||||
} // namespace
|
||||
|
||||
Float32Backend str2backend(const std::string& name) {
|
||||
if (name == "generic")
|
||||
return Float32Backend::GENERIC;
|
||||
else if (name == "cuda")
|
||||
return Float32Backend::CUDA;
|
||||
else if (name == "mkldnn")
|
||||
return Float32Backend::MKLDNN;
|
||||
TORCH_CHECK(false, "Unknown backend: ", name);
|
||||
}
|
||||
|
||||
Float32Op str2op(const std::string& name) {
|
||||
if (name == "all")
|
||||
return Float32Op::ALL;
|
||||
else if (name == "conv")
|
||||
return Float32Op::CONV;
|
||||
else if (name == "rnn")
|
||||
return Float32Op::RNN;
|
||||
else if (name == "matmul")
|
||||
return Float32Op::MATMUL;
|
||||
TORCH_CHECK(false, "Unknown op: ", name);
|
||||
}
|
||||
|
||||
Float32Precision str2precision(const std::string& name) {
|
||||
if (name == "none")
|
||||
return Float32Precision::NONE;
|
||||
else if (name == "ieee")
|
||||
return Float32Precision::IEEE;
|
||||
else if (name == "tf32")
|
||||
return Float32Precision::TF32;
|
||||
else if (name == "bf16")
|
||||
return Float32Precision::BF16;
|
||||
TORCH_CHECK(false, "Unknown precision: ", name);
|
||||
}
|
||||
|
||||
std::string precision2str(Float32Precision prec) {
|
||||
switch (prec) {
|
||||
case Float32Precision::NONE:
|
||||
return "none";
|
||||
case Float32Precision::IEEE:
|
||||
return "ieee";
|
||||
case Float32Precision::TF32:
|
||||
return "tf32";
|
||||
case Float32Precision::BF16:
|
||||
return "bf16";
|
||||
}
|
||||
TORCH_CHECK(false, "Invalid enum Float32Precision(", static_cast<int>(prec), ")");
|
||||
}
|
||||
|
||||
Context::Context() = default;
|
||||
|
||||
// TODO: This could be bad juju if someone calls globalContext() in the
|
||||
@ -192,10 +179,10 @@ void Context::setUserEnabledNNPACK(bool e) {
|
||||
enabled_nnpack = e;
|
||||
}
|
||||
|
||||
bool Context::allowTF32CuDNN(std::optional<Float32Op> op) const {
|
||||
if (!op.has_value()) {
|
||||
bool allow_tf32_rnn = float32Precision(Float32Backend::CUDA, Float32Op::RNN) == Float32Precision::TF32;
|
||||
bool allow_tf32_conv = float32Precision(Float32Backend::CUDA, Float32Op::CONV) == Float32Precision::TF32;
|
||||
bool Context::allowTF32CuDNN(const std::string& op) const {
|
||||
if (op.empty()){
|
||||
bool allow_tf32_rnn = float32Precision("cuda", "rnn") == "tf32";
|
||||
bool allow_tf32_conv = float32Precision("cuda", "conv") == "tf32";
|
||||
TORCH_CHECK(
|
||||
allow_tf32_rnn == allow_tf32_conv && allow_tf32_rnn == allow_tf32_cudnn,
|
||||
"PyTorch is checking whether allow_tf32 is enabled for cuDNN without a specific operator name,",
|
||||
@ -204,15 +191,15 @@ bool Context::allowTF32CuDNN(std::optional<Float32Op> op) const {
|
||||
"We suggest only using the new API to set the TF32 flag(s). See also: ",
|
||||
"https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices");
|
||||
} else {
|
||||
return float32Precision(Float32Backend::CUDA, op.value()) == Float32Precision::TF32;
|
||||
return float32Precision("cuda", op) == "tf32";
|
||||
}
|
||||
warn_deprecated_fp32_precision_api();
|
||||
return allow_tf32_cudnn;
|
||||
}
|
||||
|
||||
void Context::setAllowTF32CuDNN(bool b) {
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::RNN, b ? Float32Precision::TF32 : Float32Precision::NONE);
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::CONV, b ? Float32Precision::TF32 : Float32Precision::NONE);
|
||||
setFloat32Precision("cuda", "rnn", b ? "tf32" : "none");
|
||||
setFloat32Precision("cuda", "conv", b ? "tf32" : "none");
|
||||
allow_tf32_cudnn = b;
|
||||
warn_deprecated_fp32_precision_api();
|
||||
}
|
||||
@ -292,6 +279,42 @@ bool Context::userEnabledOverrideableSDP() const {
|
||||
return enabled_overrideable;
|
||||
}
|
||||
|
||||
static constexpr const auto cublas_config_var_name = "CUBLAS_WORKSPACE_CONFIG";
|
||||
static constexpr const std::array<const char*, 2> cublas_deterministic_configs = {":4096:8", ":16:8"};
|
||||
|
||||
bool Context::checkCuBLASConfigDeterministic() {
|
||||
// If using CUDA 10.2 or greater, need to make sure CuBLAS workspace config
|
||||
// is set to deterministic setting
|
||||
if (hasCUDART()) {
|
||||
const auto workspace_config = c10::utils::get_env(cublas_config_var_name);
|
||||
return (workspace_config == cublas_deterministic_configs[0] || workspace_config == cublas_deterministic_configs[1]);
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
void Context::alertCuBLASConfigNotDeterministic() const {
|
||||
static const bool cublas_config_deterministic = checkCuBLASConfigDeterministic();
|
||||
if (C10_LIKELY(!deterministicAlgorithms() || cublas_config_deterministic)) {
|
||||
return;
|
||||
}
|
||||
|
||||
auto msg = c10::str(
|
||||
"Deterministic behavior was enabled with either `torch.use_deterministic_algorithms(True)` or ",
|
||||
"`at::Context::setDeterministicAlgorithms(true)`, but this operation is not deterministic because ",
|
||||
"it uses CuBLAS and you have CUDA >= 10.2. To enable deterministic behavior in this ",
|
||||
"case, you must set an environment variable before running your PyTorch application: ",
|
||||
cublas_config_var_name, "=", cublas_deterministic_configs[0], " or ",
|
||||
cublas_config_var_name, "=", cublas_deterministic_configs[1], ". For more information, go to ",
|
||||
"https://docs.nvidia.com/cuda/cublas/index.html#results-reproducibility"
|
||||
);
|
||||
|
||||
if (deterministicAlgorithmsWarnOnly()) {
|
||||
TORCH_WARN(msg);
|
||||
} else {
|
||||
TORCH_CHECK(false, msg);
|
||||
}
|
||||
}
|
||||
|
||||
bool Context::benchmarkCuDNN() const {
|
||||
return benchmark_cudnn;
|
||||
}
|
||||
@ -318,7 +341,7 @@ void Context::setImmediateMiopen(bool b) {
|
||||
|
||||
bool Context::allowTF32CuBLAS() const {
|
||||
bool legacy_allow_tf32 = float32_matmul_precision != at::Float32MatmulPrecision::HIGHEST;
|
||||
bool allow_tf32_new = float32Precision(Float32Backend::CUDA, Float32Op::MATMUL) == Float32Precision::TF32;
|
||||
bool allow_tf32_new = float32Precision("cuda", "matmul") == "tf32";
|
||||
TORCH_CHECK(
|
||||
legacy_allow_tf32 == allow_tf32_new,
|
||||
"PyTorch is checking whether allow_tf32_new is enabled for cuBlas matmul,",
|
||||
@ -331,17 +354,17 @@ bool Context::allowTF32CuBLAS() const {
|
||||
|
||||
void Context::setAllowTF32CuBLAS(bool b) {
|
||||
float32_matmul_precision = b ? at::Float32MatmulPrecision::HIGH : at::Float32MatmulPrecision::HIGHEST;
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::MATMUL, b ? Float32Precision::TF32 : Float32Precision::IEEE);
|
||||
setFloat32Precision("cuda", "matmul", b ? "tf32" : "ieee");
|
||||
}
|
||||
|
||||
Float32MatmulPrecision Context::float32MatmulPrecision() const {
|
||||
bool invalid = float32Precision(Float32Backend::CUDA, Float32Op::MATMUL) == Float32Precision::TF32 &&
|
||||
bool invalid = float32Precision("cuda", "matmul") == "tf32" &&
|
||||
float32_matmul_precision == at::Float32MatmulPrecision::HIGHEST;
|
||||
invalid = invalid ||
|
||||
(float32Precision(Float32Backend::MKLDNN, Float32Op::MATMUL) == Float32Precision::BF16 &&
|
||||
(float32Precision("mkldnn", "matmul") == "bf16" &&
|
||||
float32_matmul_precision != at::Float32MatmulPrecision::MEDIUM);
|
||||
invalid = invalid ||
|
||||
(float32Precision(Float32Backend::MKLDNN, Float32Op::MATMUL) == Float32Precision::TF32 &&
|
||||
(float32Precision("mkldnn", "matmul") == "tf32" &&
|
||||
float32_matmul_precision != at::Float32MatmulPrecision::HIGH);
|
||||
TORCH_CHECK(
|
||||
!invalid,
|
||||
@ -353,26 +376,15 @@ Float32MatmulPrecision Context::float32MatmulPrecision() const {
|
||||
return float32_matmul_precision;
|
||||
}
|
||||
|
||||
Float32Precision Context::float32Precision(Float32Backend backend, Float32Op op) const {
|
||||
std::pair<Float32Backend, Float32Op> key{backend, op};
|
||||
auto it = fp32_precision.find(key);
|
||||
TORCH_CHECK(it != fp32_precision.end(), "Invalid (backend, op) pair: (", backend, ", ", op, ")");
|
||||
|
||||
Float32Precision precision = it->second;
|
||||
if (precision == Float32Precision::NONE) {
|
||||
key.second = Float32Op::ALL;
|
||||
precision = fp32_precision.find(key)->second;
|
||||
}
|
||||
if (precision == Float32Precision::NONE) {
|
||||
key.first = Float32Backend::GENERIC;
|
||||
precision = fp32_precision.find(key)->second;
|
||||
}
|
||||
|
||||
// "cuda" does not support "bf16"
|
||||
if (backend == Float32Backend::CUDA && precision == Float32Precision::BF16) {
|
||||
return Float32Precision::NONE;
|
||||
}
|
||||
return precision;
|
||||
std::string Context::float32Precision(const std::string& backend, const std::string& op) const {
|
||||
check_fp32_prec_backend_and_op(backend, op);
|
||||
auto precision = fp32_precision.find(backend)->second.find(op)->second;
|
||||
if (precision == "none")
|
||||
precision = fp32_precision.find(backend)->second.find("all")->second;
|
||||
if (precision == "none")
|
||||
precision = fp32_precision.find("generic")->second.find("all")->second;
|
||||
bool valid_prec = validate_fp32_prec(backend, precision);
|
||||
return valid_prec ? precision : "none";
|
||||
}
|
||||
|
||||
void Context::setFloat32MatmulPrecision(const std::string &s) {
|
||||
@ -381,18 +393,18 @@ void Context::setFloat32MatmulPrecision(const std::string &s) {
|
||||
// TODO: consider if CuDNN field needs to also be set for potential future CuDNN ops like multi-headed attention
|
||||
if (s_ == "highest") {
|
||||
float32_matmul_precision = at::Float32MatmulPrecision::HIGHEST;
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::MATMUL, Float32Precision::IEEE);
|
||||
setFloat32Precision(Float32Backend::MKLDNN, Float32Op::MATMUL, Float32Precision::IEEE);
|
||||
setFloat32Precision("cuda", "matmul", "ieee");
|
||||
setFloat32Precision("mkldnn", "matmul", "ieee");
|
||||
return true;
|
||||
} else if (s_ == "high") {
|
||||
float32_matmul_precision = at::Float32MatmulPrecision::HIGH;
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::MATMUL, Float32Precision::TF32);
|
||||
setFloat32Precision(Float32Backend::MKLDNN, Float32Op::MATMUL, Float32Precision::TF32);
|
||||
setFloat32Precision("cuda", "matmul", "tf32");
|
||||
setFloat32Precision("mkldnn", "matmul", "tf32");
|
||||
return true;
|
||||
} else if (s_ == "medium") {
|
||||
float32_matmul_precision = at::Float32MatmulPrecision::MEDIUM;
|
||||
setFloat32Precision(Float32Backend::CUDA, Float32Op::MATMUL, Float32Precision::TF32);
|
||||
setFloat32Precision(Float32Backend::MKLDNN, Float32Op::MATMUL, Float32Precision::BF16);
|
||||
setFloat32Precision("cuda", "matmul", "tf32");
|
||||
setFloat32Precision("mkldnn", "matmul", "bf16");
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
@ -406,16 +418,25 @@ void Context::setFloat32MatmulPrecision(const std::string &s) {
|
||||
"setFloat32MatmulPrecision call has no effect.");
|
||||
}
|
||||
|
||||
void Context::setFloat32Precision(Float32Backend backend, Float32Op op, Float32Precision p) {
|
||||
auto it = fp32_precision.find(std::make_pair(backend, op));
|
||||
TORCH_CHECK(
|
||||
it != fp32_precision.end(),
|
||||
"Invalid (backend, op) pair: (", backend, ", ", op, ")");
|
||||
TORCH_CHECK(
|
||||
!(backend == Float32Backend::CUDA && p == Float32Precision::BF16),
|
||||
"backend 'cuda' does not support precision 'bf16'");
|
||||
|
||||
it->second = p;
|
||||
void Context::setFloat32Precision(const std::string& backend, const std::string& op, const std::string& p) {
|
||||
check_fp32_prec_backend_and_op(backend, op);
|
||||
if (validate_fp32_prec(backend, p)) {
|
||||
fp32_precision[backend][op] = p;
|
||||
} else {
|
||||
std::string msg;
|
||||
auto iterp = _fp32_precisions.find(backend);
|
||||
TORCH_CHECK(iterp != _fp32_precisions.end());
|
||||
for (const auto& p : iterp->second) {
|
||||
msg += p;
|
||||
msg += " ";
|
||||
}
|
||||
TORCH_WARN(
|
||||
"you have set wrong precision for backend:",
|
||||
backend,
|
||||
" setFloat32Precision call has no effect.",
|
||||
"Please choose precision from: ",
|
||||
msg);
|
||||
}
|
||||
}
|
||||
|
||||
at::LinalgBackend Context::linalgPreferredBackend() const {
|
||||
@ -483,8 +504,8 @@ at::BlasBackend Context::blasPreferredBackend() {
|
||||
#if ROCM_VERSION >= 60300
|
||||
"gfx1100", "gfx1101", "gfx1200", "gfx1201", "gfx908",
|
||||
#endif
|
||||
#if ROCM_VERSION >= 70000
|
||||
"gfx950", "gfx1150", "gfx1151"
|
||||
#if ROCM_VERSION >= 60500
|
||||
"gfx950"
|
||||
#endif
|
||||
};
|
||||
for (auto index: c10::irange(detail::getCUDAHooks().deviceCount())) {
|
||||
@ -587,33 +608,20 @@ void Context::setROCmFAPreferredBackend(at::ROCmFABackend b) {
|
||||
rocm_fa_preferred_backend = b;
|
||||
}
|
||||
|
||||
CuBLASReductionOption Context::allowFP16ReductionCuBLAS() const {
|
||||
bool Context::allowFP16ReductionCuBLAS() const {
|
||||
return allow_fp16_reduction_cublas;
|
||||
}
|
||||
|
||||
CuBLASReductionOption inline get_reduction_option(bool allow_reduced_precision, bool allow_splitk) {
|
||||
TORCH_CHECK(
|
||||
!(allow_reduced_precision && !allow_splitk),
|
||||
"allow_splitk=False is not supported when reduced precision reductions are enabled");
|
||||
if (allow_reduced_precision) {
|
||||
return CuBLASReductionOption::AllowReducedPrecisionWithSplitK;
|
||||
} else if (allow_splitk) {
|
||||
return CuBLASReductionOption::DisallowReducedPrecisionAllowSplitK;
|
||||
} else {
|
||||
return CuBLASReductionOption::DisallowReducedPrecisionDisallowSplitK;
|
||||
}
|
||||
void Context::setAllowFP16ReductionCuBLAS(bool b) {
|
||||
allow_fp16_reduction_cublas = b;
|
||||
}
|
||||
|
||||
void Context::setAllowFP16ReductionCuBLAS(bool allow_reduced_precision, bool allow_splitk) {
|
||||
allow_fp16_reduction_cublas = get_reduction_option(allow_reduced_precision, allow_splitk);
|
||||
}
|
||||
|
||||
CuBLASReductionOption Context::allowBF16ReductionCuBLAS() const {
|
||||
bool Context::allowBF16ReductionCuBLAS() const {
|
||||
return allow_bf16_reduction_cublas;
|
||||
}
|
||||
|
||||
void Context::setAllowBF16ReductionCuBLAS(bool allow_reduced_precision, bool allow_splitk) {
|
||||
allow_bf16_reduction_cublas = get_reduction_option(allow_reduced_precision, allow_splitk);
|
||||
void Context::setAllowBF16ReductionCuBLAS(bool b) {
|
||||
allow_bf16_reduction_cublas = b;
|
||||
}
|
||||
|
||||
bool Context::allowFP16AccumulationCuBLAS() const {
|
||||
|
||||
@ -25,13 +25,11 @@
|
||||
#include <c10/util/CallOnce.h>
|
||||
#include <c10/util/Exception.h>
|
||||
#include <c10/util/env.h>
|
||||
#include <c10/util/hash.h>
|
||||
#include <c10/util/irange.h>
|
||||
|
||||
#include <cstdint>
|
||||
#include <map>
|
||||
#include <mutex>
|
||||
#include <unordered_map>
|
||||
|
||||
namespace at {
|
||||
|
||||
@ -39,20 +37,6 @@ class Tensor;
|
||||
|
||||
enum class TORCH_API Float32MatmulPrecision { HIGHEST, HIGH, MEDIUM };
|
||||
|
||||
enum class CuBLASReductionOption : uint8_t {
|
||||
AllowReducedPrecisionWithSplitK = 0,
|
||||
DisallowReducedPrecisionAllowSplitK = 1,
|
||||
DisallowReducedPrecisionDisallowSplitK = 2,
|
||||
};
|
||||
enum class TORCH_API Float32Backend { GENERIC, CUDA, MKLDNN };
|
||||
enum class TORCH_API Float32Op { ALL, CONV, RNN, MATMUL };
|
||||
enum class TORCH_API Float32Precision { NONE, IEEE, TF32, BF16 };
|
||||
|
||||
TORCH_API Float32Backend str2backend(const std::string& name);
|
||||
TORCH_API Float32Op str2op(const std::string& name);
|
||||
TORCH_API Float32Precision str2precision(const std::string& name);
|
||||
TORCH_API std::string precision2str(Float32Precision prec);
|
||||
|
||||
class TORCH_API Context {
|
||||
public:
|
||||
Context();
|
||||
@ -326,7 +310,13 @@ class TORCH_API Context {
|
||||
//
|
||||
// * Throw an error when `Context::deterministicAlgorithms()` is true. Most
|
||||
// of the time, this should be accomplished by calling
|
||||
// `at::globalContext().alertNotDeterminstic().
|
||||
// `at::globalContext().alertNotDeterminstic()`. However, if the
|
||||
// nondeterministic behavior is caused by the CuBLAS workspace
|
||||
// configuration in CUDA >= 10.2,
|
||||
// `at::globalContext().alertCuBLASConfigNotDeterministic()` should be
|
||||
// called instead (in this case, a comment explaining why the operation is
|
||||
// nondeterministic is not necessary). See below for details on these
|
||||
// methods.
|
||||
//
|
||||
// * Have an entry in the list of nondeterministic PyTorch operations in the
|
||||
// docstring of `use_deterministic_algorithms()` in torch/__init__.py
|
||||
@ -350,27 +340,31 @@ class TORCH_API Context {
|
||||
// Throws an error if `Context::deterministicAlgorithms()` is true
|
||||
static void alertNotDeterministic(std::string_view const& caller);
|
||||
|
||||
// Throws an error if `Context::deterministicAlgorithms()` is true, CUDA
|
||||
// >= 10.2, and CUBLAS_WORKSPACE_CONFIG is not set to either ":16:8" or
|
||||
// ":4096:8". For more details:
|
||||
// https://docs.nvidia.com/cuda/cublas/index.html#results-reproducibility
|
||||
void alertCuBLASConfigNotDeterministic() const;
|
||||
|
||||
void setFloat32MatmulPrecision(const std::string& s);
|
||||
void setFloat32Precision(
|
||||
Float32Backend backend,
|
||||
Float32Op op,
|
||||
Float32Precision p);
|
||||
bool allowTF32CuDNN(std::optional<Float32Op> op = std::nullopt) const;
|
||||
const std::string& backend,
|
||||
const std::string& op,
|
||||
const std::string& s);
|
||||
bool allowTF32CuDNN(const std::string& op = std::string()) const;
|
||||
void setAllowTF32CuDNN(bool);
|
||||
bool allowTF32OneDNN() const;
|
||||
void setAllowTF32OneDNN(bool);
|
||||
bool allowTF32CuBLAS() const;
|
||||
void setAllowTF32CuBLAS(bool);
|
||||
Float32MatmulPrecision float32MatmulPrecision() const;
|
||||
Float32Precision float32Precision(Float32Backend backend, Float32Op op) const;
|
||||
CuBLASReductionOption allowFP16ReductionCuBLAS() const;
|
||||
void setAllowFP16ReductionCuBLAS(
|
||||
bool allow_reduced_precision,
|
||||
bool allow_splitk = true);
|
||||
CuBLASReductionOption allowBF16ReductionCuBLAS() const;
|
||||
void setAllowBF16ReductionCuBLAS(
|
||||
bool allow_reduced_precision,
|
||||
bool allow_splitk = true);
|
||||
std::string float32Precision(
|
||||
const std::string& backend,
|
||||
const std::string& op) const;
|
||||
bool allowFP16ReductionCuBLAS() const;
|
||||
void setAllowFP16ReductionCuBLAS(bool);
|
||||
bool allowBF16ReductionCuBLAS() const;
|
||||
void setAllowBF16ReductionCuBLAS(bool);
|
||||
bool allowFP16AccumulationCuBLAS() const;
|
||||
void setAllowFP16AccumulationCuBLAS(bool);
|
||||
|
||||
@ -435,6 +429,7 @@ class TORCH_API Context {
|
||||
}
|
||||
|
||||
private:
|
||||
static bool checkCuBLASConfigDeterministic();
|
||||
std::array<c10::once_flag, at::COMPILE_TIME_MAX_DEVICE_TYPES> init_;
|
||||
bool enabled_cudnn = true;
|
||||
bool deterministic_cudnn = false;
|
||||
@ -462,10 +457,8 @@ class TORCH_API Context {
|
||||
: at::Float32MatmulPrecision::HIGHEST;
|
||||
int benchmark_limit_cudnn = 10;
|
||||
bool allow_tf32_cudnn = true;
|
||||
CuBLASReductionOption allow_fp16_reduction_cublas =
|
||||
CuBLASReductionOption::AllowReducedPrecisionWithSplitK;
|
||||
CuBLASReductionOption allow_bf16_reduction_cublas =
|
||||
CuBLASReductionOption::AllowReducedPrecisionWithSplitK;
|
||||
bool allow_fp16_reduction_cublas = true;
|
||||
bool allow_bf16_reduction_cublas = true;
|
||||
bool allow_fp16_accumulation_cublas = false;
|
||||
std::optional<int32_t> sm_carveout = std::nullopt;
|
||||
bool enabled_mkldnn = true;
|
||||
@ -495,20 +488,21 @@ class TORCH_API Context {
|
||||
bool enable_sparse_tensor_invariant_checks = false;
|
||||
bool allow_fp16_reduction_cpu = false;
|
||||
|
||||
using Key = std::pair<Float32Backend, Float32Op>;
|
||||
std::unordered_map<Key, Float32Precision, c10::hash<Key>> fp32_precision = {
|
||||
{{Float32Backend::GENERIC, Float32Op::ALL}, Float32Precision::NONE},
|
||||
{{Float32Backend::MKLDNN, Float32Op::ALL}, Float32Precision::NONE},
|
||||
{{Float32Backend::MKLDNN, Float32Op::CONV}, Float32Precision::NONE},
|
||||
{{Float32Backend::MKLDNN, Float32Op::RNN}, Float32Precision::NONE},
|
||||
{{Float32Backend::MKLDNN, Float32Op::MATMUL}, Float32Precision::NONE},
|
||||
{{Float32Backend::CUDA, Float32Op::ALL}, Float32Precision::NONE},
|
||||
{{Float32Backend::CUDA, Float32Op::CONV}, Float32Precision::TF32},
|
||||
{{Float32Backend::CUDA, Float32Op::RNN}, Float32Precision::TF32},
|
||||
{{Float32Backend::CUDA, Float32Op::MATMUL},
|
||||
float32_matmul_precision == at::Float32MatmulPrecision::HIGHEST
|
||||
? Float32Precision::NONE
|
||||
: Float32Precision::TF32},
|
||||
std::map<std::string, std::map<std::string, std::string>> fp32_precision = {
|
||||
{"generic", {{"all", "none"}}},
|
||||
{"mkldnn",
|
||||
{{"matmul", "none"},
|
||||
{"conv", "none"},
|
||||
{"rnn", "none"},
|
||||
{"all", "none"}}},
|
||||
{"cuda",
|
||||
{{"matmul",
|
||||
float32_matmul_precision == at::Float32MatmulPrecision::HIGHEST
|
||||
? "none"
|
||||
: "tf32"},
|
||||
{"conv", "tf32"},
|
||||
{"rnn", "tf32"},
|
||||
{"all", "none"}}},
|
||||
};
|
||||
|
||||
Allocator* prev_allocator_ptr_{nullptr};
|
||||
@ -690,4 +684,5 @@ struct TORCH_API ROCmBackwardPassGuard {
|
||||
~ROCmBackwardPassGuard();
|
||||
static bool is_backward_pass();
|
||||
};
|
||||
|
||||
} // namespace at
|
||||
|
||||
@ -292,28 +292,6 @@ MapAllocator::MapAllocator(WithFd, std::string_view filename, int fd, int flags,
|
||||
if (ftruncate(fd, static_cast<off_t>(size)) == -1) {
|
||||
TORCH_CHECK(false, "unable to resize file <", filename_, "> to the right size: ", c10::utils::str_error(errno), " (", errno, ")");
|
||||
}
|
||||
|
||||
#ifdef HAVE_POSIX_FALLOCATE
|
||||
if (flags_ & ALLOCATOR_MAPPED_SHAREDMEM) {
|
||||
for (;;) {
|
||||
if (posix_fallocate(fd, 0, static_cast<off_t>(size)) == 0) {
|
||||
break;
|
||||
}
|
||||
|
||||
if (errno == EINTR) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (errno == EINVAL || errno == EOPNOTSUPP) {
|
||||
// the underlying filesystem does not support the operation
|
||||
break;
|
||||
}
|
||||
|
||||
TORCH_CHECK(false, "unable to allocate shared memory(shm) for file <", filename_, ">: ", c10::utils::str_error(errno), " (", errno, ")");
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
if (fstat(fd, &file_stat) == -1 || file_stat.st_size < static_cast<int64_t>(size)) {
|
||||
#ifndef STRIP_ERROR_MESSAGES
|
||||
int last_err = errno;
|
||||
|
||||
@ -179,7 +179,7 @@ void propagate_names_except(const Tensor& result, const Tensor& src, IntArrayRef
|
||||
return;
|
||||
}
|
||||
const auto src_names = src.names();
|
||||
const auto result_dim = result.dim();
|
||||
const auto result_dim = static_cast<int64_t>(result.dim());
|
||||
const auto src_dim = static_cast<int64_t>(src_names.size());
|
||||
const auto excluded_dim = static_cast<int64_t>(excluded_idxs.size());
|
||||
TORCH_INTERNAL_ASSERT(src_dim - excluded_dim == result_dim);
|
||||
|
||||
@ -229,14 +229,14 @@ struct TORCH_API SparseTensorImpl : public TensorImpl {
|
||||
}
|
||||
|
||||
void resize_(int64_t sparse_dim, int64_t dense_dim, ArrayRef<int64_t> size) {
|
||||
_resize_(sparse_dim, dense_dim, size);
|
||||
return _resize_(sparse_dim, dense_dim, size);
|
||||
}
|
||||
|
||||
void resize_(
|
||||
int64_t sparse_dim,
|
||||
int64_t dense_dim,
|
||||
ArrayRef<c10::SymInt> size) {
|
||||
_resize_(sparse_dim, dense_dim, size);
|
||||
return _resize_(sparse_dim, dense_dim, size);
|
||||
}
|
||||
|
||||
// NOTE: this function will resize the sparse tensor and also set `indices`
|
||||
|
||||
@ -59,7 +59,7 @@ static inline void set_item(const Tensor& self, ArrayRef<TensorIndex> indices, c
|
||||
}
|
||||
}
|
||||
|
||||
set_item(self, indices, value);
|
||||
return set_item(self, indices, value);
|
||||
}
|
||||
|
||||
} // namespace indexing
|
||||
|
||||
@ -214,7 +214,7 @@ inline Tensor applySlice(
|
||||
"step must be greater than zero");
|
||||
|
||||
// See NOTE [nested tensor size for indexing]
|
||||
if (self_sizes.has_value() && !self_sizes.value().empty()) {
|
||||
if (self_sizes.has_value() && self_sizes.value().size() > 0) {
|
||||
// Skip this optimization if we are tracing, as the trace may be polymorphic
|
||||
// over the shape of the `self` tensor, and we still want to record
|
||||
// the slice.
|
||||
|
||||
@ -765,8 +765,7 @@ void TensorIteratorBase::for_each(loop2d_t loop, int64_t grain_size) {
|
||||
if (numel == 0) {
|
||||
return;
|
||||
} else if (numel < grain_size || at::get_num_threads() == 1) {
|
||||
serial_for_each(loop, {0, numel});
|
||||
return;
|
||||
return serial_for_each(loop, {0, numel});
|
||||
} else {
|
||||
at::parallel_for(0, numel, grain_size, [&](int64_t begin, int64_t end) {
|
||||
serial_for_each(loop, {begin, end});
|
||||
|
||||
@ -273,11 +273,11 @@ void checkLayout(CheckedFrom c, at::ArrayRef<Tensor> tensors, at::Layout layout)
|
||||
}
|
||||
|
||||
void * maybe_data_ptr(const Tensor& tensor) {
|
||||
return tensor.defined() ? tensor.data_ptr() : nullptr;
|
||||
return tensor.defined() ? (void *)tensor.data_ptr() : nullptr;
|
||||
}
|
||||
|
||||
void * maybe_data_ptr(const TensorArg& tensor) {
|
||||
return tensor->defined() ? tensor->data_ptr() : nullptr;
|
||||
return tensor->defined() ? (void *)tensor->data_ptr() : nullptr;
|
||||
}
|
||||
|
||||
void check_dim_size(
|
||||
|
||||
@ -6,7 +6,6 @@
|
||||
#include <c10/core/thread_pool.h>
|
||||
#include <c10/util/flat_hash_map.h>
|
||||
#include <c10/util/llvmMathExtras.h>
|
||||
#include <iostream>
|
||||
#include <optional>
|
||||
|
||||
#include <deque>
|
||||
@ -50,57 +49,19 @@ namespace {
|
||||
constexpr size_t MAX_SIZE_INDEX = 64;
|
||||
}
|
||||
|
||||
// A large reserved pinned memory segment that is created in advance which is used
|
||||
// to allocate small pinned memory requests to avoid calling into expensive APIs.
|
||||
// We never free this memory and move up the pointer as we allocate new blocks
|
||||
// and when blocks are freed, they are cached in the free lists.
|
||||
struct PinnedReserveSegment {
|
||||
PinnedReserveSegment(void *start, size_t size) : start_(start), size_(size),
|
||||
current_ptr_(start_), initialized_(true) {}
|
||||
|
||||
PinnedReserveSegment() : start_(nullptr), size_(0), current_ptr_(nullptr), initialized_(false) {}
|
||||
|
||||
bool initialized() {
|
||||
return initialized_;
|
||||
}
|
||||
|
||||
void* allocate(size_t bytes) {
|
||||
std::lock_guard<std::mutex> guard(mutex_);
|
||||
|
||||
// Round up the requested size to 4KB boundary for all including the small ones.
|
||||
size_t rounded_bytes = (bytes + 4096 - 1) & ~(4096 - 1);
|
||||
|
||||
if (((uint8_t*)current_ptr_ + rounded_bytes) > ((uint8_t*)start_ + size_)) {
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
void* ptr = current_ptr_;
|
||||
current_ptr_ = (uint8_t*)current_ptr_ + rounded_bytes;
|
||||
return ptr;
|
||||
}
|
||||
|
||||
bool owns(void* ptr) {
|
||||
return ptr >= start_ && ptr < (uint8_t*)start_ + size_;
|
||||
}
|
||||
|
||||
std::mutex mutex_;
|
||||
void* start_;
|
||||
size_t size_;
|
||||
void* current_ptr_;
|
||||
bool initialized_;
|
||||
};
|
||||
|
||||
// Struct containing memory allocator summary statistics for host.
|
||||
struct TORCH_API HostStats {
|
||||
// COUNT: total allocations (active)
|
||||
Stat active_requests;
|
||||
// SUM: bytes allocated/reserved by this memory alocator. (active)
|
||||
Stat active_bytes;
|
||||
// COUNT: total allocations (active + free)
|
||||
Stat allocations;
|
||||
// SUM: bytes allocated/reserved by this memory alocator. This accounts
|
||||
// for both free and in-use blocks.
|
||||
// COUNT: allocations requested by client code. Note that active
|
||||
// count can be extracted by looking at current allocations
|
||||
Stat allocation;
|
||||
// COUNT: number of allocated segments from host memory allocation.
|
||||
Stat segment;
|
||||
|
||||
// SUM: bytes allocated by this memory alocator. Note that active bytes
|
||||
// can be extracted by looking at current bytes allocated
|
||||
Stat allocated_bytes;
|
||||
// SUM: bytes reserved by this memory allocator (both free and used)
|
||||
Stat reserved_bytes;
|
||||
|
||||
// SUM: time spent in cudaHostAlloc/cudaHostRegister in microseconds
|
||||
DurationStat host_alloc_time;
|
||||
@ -114,9 +75,6 @@ struct TORCH_API HostStats {
|
||||
|
||||
// COUNT: number of times cudaHostFree/cudaHostUnregister was called.
|
||||
int64_t num_host_free = 0; // This is derived from segment or timing
|
||||
|
||||
// Count of cudaHostAlloc/cudaHostRegister per bucket
|
||||
std::vector<int64_t> bucket_allocation = std::vector<int64_t>(MAX_SIZE_INDEX);
|
||||
};
|
||||
|
||||
// Struct containing memory allocator summary statistics for host, as they
|
||||
@ -124,22 +82,17 @@ struct TORCH_API HostStats {
|
||||
// avoid locking the allocator while collecting stats.
|
||||
struct alignas(64) HostStatsStaged {
|
||||
std::mutex timing_mutex_;
|
||||
// COUNT: total allocations (active + free)
|
||||
// COUNT: allocations requested by client code resulting in a new segment/block allocation
|
||||
// LOCK: access to this stat is protected by the allocator's blocks_mutex_
|
||||
Stat allocation;
|
||||
// SUM: bytes within active memory blocks, including blocks that are
|
||||
// currently in the free list.
|
||||
// LOCK: access to this stat is protected by the allocator's blocks_mutex_
|
||||
Stat allocations;
|
||||
// SUM: bytes allocated/reserved by this memory alocator. This accounts
|
||||
// for both free and in-use blocks.
|
||||
Stat allocated_bytes;
|
||||
// COUNT: number of allocations per bucket (active)
|
||||
// LOCK: access to this stat is protected by the per bucket free_list_[index].mutex_
|
||||
std::vector<Stat> active_bucket_stats = std::vector<Stat>(MAX_SIZE_INDEX);
|
||||
// SUM: bytes of allocation per bucket (active)
|
||||
// LOCK: access to this stat is protected by the per bucket free_list_[index].mutex_
|
||||
std::vector<Stat> active_bytes_bucket_stats = std::vector<Stat>(MAX_SIZE_INDEX);
|
||||
// COUNT: number of allocations per bucket (active + free)
|
||||
// COUNT: number of allocations per bucket
|
||||
// LOCK: access to this stat is protected by the per bucket free_list_[index].mutex_
|
||||
std::vector<Stat> allocation_bucket_stats = std::vector<Stat>(MAX_SIZE_INDEX);
|
||||
// SUM: bytes of allocation per bucket (active + free)
|
||||
// SUM: bytes of allocation per bucket
|
||||
// LOCK: access to this stat is protected by the per bucket free_list_[index].mutex_
|
||||
std::vector<Stat> allocated_bytes_bucket_stats = std::vector<Stat>(MAX_SIZE_INDEX);
|
||||
// SUM: time spent in cudaHostAlloc/cudaHostRegister
|
||||
@ -258,6 +211,12 @@ struct CachingHostAllocatorImpl {
|
||||
// Check in the recently freed blocks with pending events to see if we
|
||||
// can reuse them. Call get_free_block again after processing events
|
||||
if (pinned_use_background_threads()) {
|
||||
process_events_for_specific_size(roundSize);
|
||||
block = get_free_block(roundSize);
|
||||
if (block) {
|
||||
return {block->ptr_, reinterpret_cast<void*>(block)};
|
||||
}
|
||||
|
||||
// Launch the background thread and process events in a loop.
|
||||
static bool background_thread_flag [[maybe_unused]] = [this] {
|
||||
getBackgroundThreadPool()->run([&]() {
|
||||
@ -319,6 +278,8 @@ struct CachingHostAllocatorImpl {
|
||||
auto index = size_index(block->size_);
|
||||
std::lock_guard<std::mutex> g(free_list_[index].mutex_);
|
||||
free_list_[index].list_.push_back(block);
|
||||
stats_.allocation_bucket_stats[index].decrease(1);
|
||||
stats_.allocated_bytes_bucket_stats[index].decrease(block->size_);
|
||||
} else {
|
||||
// restore these events that record by used streams.
|
||||
std::lock_guard<std::mutex> g(events_mutex_);
|
||||
@ -378,12 +339,9 @@ struct CachingHostAllocatorImpl {
|
||||
for (auto* block : blocks_to_remove) {
|
||||
blocks_.erase(block);
|
||||
ptr_to_block_.erase(block->ptr_);
|
||||
auto index = size_index(block->size_);
|
||||
free_block(block);
|
||||
stats_.allocations.decrease(1);
|
||||
stats_.allocation.decrease(1);
|
||||
stats_.allocated_bytes.decrease(block->size_);
|
||||
stats_.allocation_bucket_stats[index].decrease(1);
|
||||
stats_.allocated_bytes_bucket_stats[index].decrease(block->size_);
|
||||
free_block(block);
|
||||
delete block;
|
||||
}
|
||||
}
|
||||
@ -430,17 +388,16 @@ struct CachingHostAllocatorImpl {
|
||||
// per bucket (we pick index 0 arbitrarily). These are also all the host
|
||||
// allocations, not taking into account caching and free lists.
|
||||
if (i == 0) {
|
||||
stats.allocations = stats_.allocations;
|
||||
stats.allocated_bytes = stats_.allocated_bytes;
|
||||
stats.num_host_alloc = stats.allocations.allocated;
|
||||
stats.num_host_free = stats.allocations.freed;
|
||||
stats.segment = stats_.allocation;
|
||||
stats.reserved_bytes = stats_.allocated_bytes;
|
||||
stats.num_host_alloc = stats.segment.allocated;
|
||||
stats.num_host_free = stats.segment.freed;
|
||||
}
|
||||
|
||||
// Bucket stats need to be merged with the slow-path stats. We do this in
|
||||
// a best effort manner, since we can't really replay the cached events per bucket.
|
||||
add_bucket_stats(stats.active_requests, stats_.active_bucket_stats[i]);
|
||||
add_bucket_stats(stats.active_bytes, stats_.active_bytes_bucket_stats[i]);
|
||||
stats.bucket_allocation[i] = stats_.allocation_bucket_stats[i].allocated;
|
||||
add_bucket_stats(stats.allocation, stats_.allocation_bucket_stats[i]);
|
||||
add_bucket_stats(stats.allocated_bytes, stats_.allocated_bytes_bucket_stats[i]);
|
||||
}
|
||||
|
||||
// Get the timing stats
|
||||
@ -464,11 +421,9 @@ struct CachingHostAllocatorImpl {
|
||||
std::lock_guard<std::mutex> gb(blocks_mutex_, std::adopt_lock);
|
||||
|
||||
if (i == 0) {
|
||||
stats_.allocations.reset_accumulated();
|
||||
stats_.allocation.reset_accumulated();
|
||||
stats_.allocated_bytes.reset_accumulated();
|
||||
}
|
||||
stats_.active_bucket_stats[i].reset_accumulated();
|
||||
stats_.active_bytes_bucket_stats[i].reset_accumulated();
|
||||
stats_.allocation_bucket_stats[i].reset_accumulated();
|
||||
stats_.allocated_bytes_bucket_stats[i].reset_accumulated();
|
||||
}
|
||||
@ -491,11 +446,9 @@ struct CachingHostAllocatorImpl {
|
||||
std::lock_guard<std::mutex> gb(blocks_mutex_, std::adopt_lock);
|
||||
|
||||
if (i == 0) {
|
||||
stats_.allocations.reset_peak();
|
||||
stats_.allocation.reset_peak();
|
||||
stats_.allocated_bytes.reset_peak();
|
||||
}
|
||||
stats_.active_bucket_stats[i].reset_peak();
|
||||
stats_.active_bytes_bucket_stats[i].reset_peak();
|
||||
stats_.allocation_bucket_stats[i].reset_peak();
|
||||
stats_.allocated_bytes_bucket_stats[i].reset_peak();
|
||||
}
|
||||
@ -512,7 +465,7 @@ struct CachingHostAllocatorImpl {
|
||||
virtual void add_allocated_block(B* block) {
|
||||
std::lock_guard<std::mutex> g(blocks_mutex_);
|
||||
blocks_.insert(block);
|
||||
stats_.allocations.increase(1);
|
||||
stats_.allocation.increase(1);
|
||||
stats_.allocated_bytes.increase(block->size_);
|
||||
ptr_to_block_.insert({block->ptr_, block});
|
||||
|
||||
@ -525,8 +478,6 @@ struct CachingHostAllocatorImpl {
|
||||
std::lock_guard<std::mutex> g(free_list_[index].mutex_);
|
||||
stats_.allocation_bucket_stats[index].increase(1);
|
||||
stats_.allocated_bytes_bucket_stats[index].increase(size);
|
||||
stats_.active_bucket_stats[index].increase(1);
|
||||
stats_.active_bytes_bucket_stats[index].increase(size);
|
||||
}
|
||||
}
|
||||
|
||||
@ -537,8 +488,8 @@ struct CachingHostAllocatorImpl {
|
||||
B* block = free_list_[index].list_.back();
|
||||
free_list_[index].list_.pop_back();
|
||||
block->allocated_ = true;
|
||||
stats_.active_bucket_stats[index].increase(1);
|
||||
stats_.active_bytes_bucket_stats[index].increase(size);
|
||||
stats_.allocation_bucket_stats[index].increase(1);
|
||||
stats_.allocated_bytes_bucket_stats[index].increase(size);
|
||||
return block;
|
||||
}
|
||||
return nullptr;
|
||||
@ -632,8 +583,8 @@ struct CachingHostAllocatorImpl {
|
||||
auto index = size_index(block->size_);
|
||||
std::lock_guard<std::mutex> g(free_list_[index].mutex_);
|
||||
free_list_[index].list_.push_back(block);
|
||||
stats_.active_bucket_stats[index].decrease(1);
|
||||
stats_.active_bytes_bucket_stats[index].decrease(size);
|
||||
stats_.allocation_bucket_stats[index].decrease(1);
|
||||
stats_.allocated_bytes_bucket_stats[index].decrease(size);
|
||||
if (size != -1) {
|
||||
return;
|
||||
}
|
||||
|
||||
@ -49,7 +49,7 @@ static void check_unique_names(DimnameList names) {
|
||||
}
|
||||
|
||||
void check_names_valid_for(const TensorBase& tensor, DimnameList names) {
|
||||
impl::check_names_valid_for(tensor.unsafeGetTensorImpl(), names);
|
||||
return impl::check_names_valid_for(tensor.unsafeGetTensorImpl(), names);
|
||||
}
|
||||
|
||||
void check_names_valid_for(size_t tensor_dim, DimnameList names) {
|
||||
|
||||
@ -2,7 +2,6 @@
|
||||
#include <c10/core/impl/PythonDispatcherTLS.h>
|
||||
#include <ATen/core/PythonFallbackKernel.h>
|
||||
#include <c10/core/SafePyObject.h>
|
||||
#include <ATen/record_function.h>
|
||||
|
||||
namespace {
|
||||
|
||||
@ -54,24 +53,20 @@ void pythonFallback(const c10::OperatorHandle& op, c10::DispatchKeySet dispatch_
|
||||
TORCH_INTERNAL_ASSERT(tls_on_entry.has_value());
|
||||
// c10::impl::ForceDispatchKeyGuard dispatcher_guard(tls_on_entry.value());
|
||||
// StashTLSOnEntryGuard stash_guard;
|
||||
c10::impl::ExcludeDispatchKeyGuard exclude_guard(after_Python_keyset);
|
||||
c10::impl::ExcludeDispatchKeyGuard guard(after_Python_keyset);
|
||||
|
||||
const auto& schema = op.schema();
|
||||
const auto num_arguments = schema.arguments().size();
|
||||
|
||||
// If Torch Dispatch Mode is active, use its PyInterpreter for dispatch
|
||||
const auto mode_stack_len = c10::impl::TorchDispatchModeTLS::stack_len();
|
||||
if (mode_stack_len > 0) {
|
||||
RECORD_FUNCTION("PythonDispatchMode", torch::jit::last(*stack, num_arguments));
|
||||
const auto& cur_torch_dispatch_mode_state = c10::impl::TorchDispatchModeTLS::get_stack_at(mode_stack_len - 1);
|
||||
cur_torch_dispatch_mode_state->pyinterpreter()->dispatch(op, stack);
|
||||
return;
|
||||
}
|
||||
|
||||
RECORD_FUNCTION("PythonSubclass", torch::jit::last(*stack, num_arguments));
|
||||
|
||||
// Otherwise, find a PyInterpreter on a Tensor
|
||||
|
||||
const auto& schema = op.schema();
|
||||
const auto num_arguments = schema.arguments().size();
|
||||
// It is safe to dispatch on the very first Tensor with a pyobj_interpreter
|
||||
// without checking the interpreters of any of the arguments, because when
|
||||
// we actually run dispatch(), we will take out PyObjects in the context
|
||||
|
||||
@ -138,7 +138,7 @@ void Tensor::_backward(TensorList inputs,
|
||||
const std::optional<Tensor>& gradient,
|
||||
std::optional<bool> keep_graph,
|
||||
bool create_graph) const {
|
||||
impl::GetVariableHooks()->_backward(*this, inputs, gradient, keep_graph, create_graph);
|
||||
return impl::GetVariableHooks()->_backward(*this, inputs, gradient, keep_graph, create_graph);
|
||||
}
|
||||
|
||||
const TensorBase& TensorBase::requires_grad_(bool _requires_grad) const {
|
||||
@ -173,12 +173,4 @@ unsigned TensorBase::_register_hook(std::function<TensorBase(const TensorBase&)>
|
||||
return impl::GetVariableHooks()->_register_hook(*this, std::move(hook));
|
||||
}
|
||||
|
||||
std::optional<ScalarType> TensorBase::grad_dtype() const {
|
||||
return impl::GetVariableHooks()->grad_dtype(*this);
|
||||
}
|
||||
|
||||
void TensorBase::set_grad_dtype(const std::optional<ScalarType>& grad_dtype) const {
|
||||
return impl::GetVariableHooks()->set_grad_dtype(*this, grad_dtype);
|
||||
}
|
||||
|
||||
} // namespace at
|
||||
|
||||
@ -930,10 +930,6 @@ public:
|
||||
|
||||
const TensorBase& requires_grad_(bool _requires_grad=true) const;
|
||||
|
||||
std::optional<ScalarType> grad_dtype() const;
|
||||
|
||||
void set_grad_dtype(const std::optional<ScalarType>& grad_dtype) const;
|
||||
|
||||
// View Variables
|
||||
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
|
||||
@ -117,7 +117,7 @@ C10_HOST_DEVICE inline T cauchy(T val, T median, T sigma) {
|
||||
template <>
|
||||
C10_HOST_DEVICE inline double cauchy(double val, double median, double sigma) {
|
||||
// https://en.wikipedia.org/wiki/Cauchy_distribution#Cumulative_distribution_function
|
||||
return median + sigma * at::tan(c10::pi<double> * (val - 0.5));
|
||||
return median + sigma * at::tan(c10::pi<double> * (val - static_cast<double>(0.5)));
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@ -68,8 +68,6 @@ struct TORCH_API VariableHooksInterface {
|
||||
const c10::OperatorHandle& op,
|
||||
c10::DispatchKeySet dispatch_keys,
|
||||
torch::jit::Stack* stack) const = 0;
|
||||
virtual std::optional<c10::ScalarType> grad_dtype(const TensorBase&) const = 0;
|
||||
virtual void set_grad_dtype(const TensorBase&, const std::optional<c10::ScalarType>&) const = 0;
|
||||
};
|
||||
|
||||
TORCH_API void SetVariableHooks(VariableHooksInterface* hooks);
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
|
||||
namespace c10 {
|
||||
|
||||
inline BoxedKernel::BoxedKernel() : boxed_kernel_func_(nullptr) {}
|
||||
inline BoxedKernel::BoxedKernel() : functor_(), boxed_kernel_func_(nullptr) {}
|
||||
|
||||
inline BoxedKernel::BoxedKernel(
|
||||
std::unique_ptr<OperatorKernel> functor,
|
||||
|
||||
@ -20,7 +20,9 @@ make_unique_base(Args&&... args) {
|
||||
} // namespace detail
|
||||
|
||||
inline KernelFunction::KernelFunction()
|
||||
: unboxed_kernel_func_(nullptr), sym_unboxed_kernel_func_(nullptr) {}
|
||||
: boxed_kernel_func_(),
|
||||
unboxed_kernel_func_(nullptr),
|
||||
sym_unboxed_kernel_func_(nullptr) {}
|
||||
|
||||
inline KernelFunction::~KernelFunction() {
|
||||
if (tokens_) {
|
||||
|
||||
@ -76,7 +76,13 @@ void _print_dispatch_trace(const std::string& label, const std::string& op_name,
|
||||
|
||||
OpRegistrationListener::~OpRegistrationListener()= default;
|
||||
|
||||
Dispatcher::Dispatcher(): backendFallbackKernels_(), listeners_(std::make_unique<detail::RegistrationListenerList>()), guard_(std::make_shared<Guard>())
|
||||
Dispatcher::Dispatcher()
|
||||
: operators_()
|
||||
, operatorLookupTable_()
|
||||
, backendFallbackKernels_()
|
||||
, listeners_(std::make_unique<detail::RegistrationListenerList>())
|
||||
, cond_var_()
|
||||
, guard_(std::make_shared<Guard>())
|
||||
{}
|
||||
|
||||
Dispatcher::~Dispatcher() {
|
||||
|
||||
@ -96,7 +96,7 @@ class TORCH_API Dispatcher final {
|
||||
friend class TypedOperatorHandle;
|
||||
|
||||
struct Guard final {
|
||||
Guard() : alive(true) {}
|
||||
Guard() : alive(true), mutex() {}
|
||||
std::atomic<bool> alive;
|
||||
std::mutex mutex;
|
||||
};
|
||||
@ -496,7 +496,7 @@ class TORCH_API OperatorHandle {
|
||||
}
|
||||
|
||||
void checkInvariants() const {
|
||||
operatorDef_->op.checkInvariants();
|
||||
return operatorDef_->op.checkInvariants();
|
||||
}
|
||||
|
||||
c10::ArrayRef<at::Tag> getTags() const {
|
||||
@ -932,7 +932,7 @@ inline void Dispatcher::redispatchBoxed(
|
||||
}
|
||||
#endif
|
||||
const auto& kernel = entry.lookup(dispatchKeySet);
|
||||
kernel.callBoxed(op, dispatchKeySet, stack);
|
||||
return kernel.callBoxed(op, dispatchKeySet, stack);
|
||||
}
|
||||
|
||||
} // namespace c10
|
||||
|
||||
@ -62,7 +62,17 @@ static const auto& getDispatchTableIndexToKey() {
|
||||
}
|
||||
|
||||
OperatorEntry::OperatorEntry(OperatorName&& operator_name)
|
||||
: name_(std::move(operator_name)), dispatchTable_(), dispatchKeyExtractor_(DispatchKeyExtractor::makeUninitialized()), is_observed_(ObservedOperators::isObserved(name_))
|
||||
: name_(std::move(operator_name))
|
||||
, schema_()
|
||||
#ifndef C10_MOBILE
|
||||
, tags_()
|
||||
#endif
|
||||
, dispatchTable_()
|
||||
, dispatchKeyExtractor_(DispatchKeyExtractor::makeUninitialized())
|
||||
, kernels_()
|
||||
, cpp_signature_()
|
||||
, sym_cpp_signature_()
|
||||
, is_observed_(ObservedOperators::isObserved(name_))
|
||||
{
|
||||
// Pick up any backend fallbacks that were registered prior to this
|
||||
// OperatorEntry being created.
|
||||
|
||||
@ -357,7 +357,7 @@ IValue IValue::equals(const IValue& rhs) const {
|
||||
case Tag::Enum:
|
||||
return lhs.toEnumHolder()->is(*rhs.toEnumHolder());
|
||||
case Tag::Uninitialized:
|
||||
// Uninitialized ivalues show up in no-ops when the compiler can prove a
|
||||
// Unitialized ivalues show up in no-ops when the compiler can prove a
|
||||
// value will never be used. Just return false on any equality comparison.
|
||||
return false;
|
||||
}
|
||||
|
||||
@ -114,7 +114,7 @@ constexpr bool allowlist_contains(std::string_view allowlist, std::string_view i
|
||||
}
|
||||
next++;
|
||||
} else {
|
||||
if (allowlist.substr(cur) == item) {
|
||||
if (allowlist.substr(cur).compare(item) == 0) {
|
||||
return true;
|
||||
}
|
||||
break;
|
||||
|
||||
@ -73,7 +73,7 @@ c10::FunctionSchema RegisterOperators::inferSchemaFromKernels_(
|
||||
|
||||
std::optional<FunctionSchema> inferred_schema = std::nullopt;
|
||||
for (const auto& kernel : options.kernels) {
|
||||
if (nullptr != kernel.inferred_function_schema) {
|
||||
if (nullptr != kernel.inferred_function_schema.get()) {
|
||||
if (!inferred_schema.has_value()) {
|
||||
inferred_schema = *kernel.inferred_function_schema;
|
||||
break;
|
||||
|
||||
@ -411,6 +411,7 @@ public:
|
||||
|
||||
Options()
|
||||
: schemaOrName_(std::nullopt)
|
||||
, kernels()
|
||||
, aliasAnalysisKind_(std::nullopt)
|
||||
{}
|
||||
|
||||
@ -419,6 +420,7 @@ public:
|
||||
struct KernelRegistrationConfig final {
|
||||
KernelRegistrationConfig()
|
||||
: dispatch_key(std::nullopt)
|
||||
, func()
|
||||
, cpp_signature(std::nullopt)
|
||||
, inferred_function_schema(nullptr)
|
||||
{}
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user