/
generate_binary_build_matrix.py
256 lines (223 loc) · 10 KB
/
generate_binary_build_matrix.py
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#!/usr/bin/env python3
"""Generates a matrix to be utilized through github actions
Will output a condensed version of the matrix if on a pull request that only
includes the latest version of python we support built on three different
architectures:
* CPU
* Latest CUDA
* Latest ROCM
"""
from typing import Dict, List, Tuple, Optional
CUDA_ARCHES = ["11.6", "11.7", "11.8"]
ROCM_ARCHES = ["5.2", "5.3"]
def arch_type(arch_version: str) -> str:
if arch_version in CUDA_ARCHES:
return "cuda"
elif arch_version in ROCM_ARCHES:
return "rocm"
else: # arch_version should always be "cpu" in this case
return "cpu"
WHEEL_CONTAINER_IMAGES = {
**{
gpu_arch: f"pytorch/manylinux-builder:cuda{gpu_arch}"
for gpu_arch in CUDA_ARCHES
},
**{
gpu_arch: f"pytorch/manylinux-builder:rocm{gpu_arch}"
for gpu_arch in ROCM_ARCHES
},
"cpu": "pytorch/manylinux-builder:cpu",
}
CONDA_CONTAINER_IMAGES = {
**{gpu_arch: f"pytorch/conda-builder:cuda{gpu_arch}" for gpu_arch in CUDA_ARCHES},
"cpu": "pytorch/conda-builder:cpu",
}
PRE_CXX11_ABI = "pre-cxx11"
CXX11_ABI = "cxx11-abi"
RELEASE = "release"
DEBUG = "debug"
LIBTORCH_CONTAINER_IMAGES: Dict[Tuple[str, str], str] = {
**{
(gpu_arch, PRE_CXX11_ABI): f"pytorch/manylinux-builder:cuda{gpu_arch}"
for gpu_arch in CUDA_ARCHES
},
**{
(gpu_arch, CXX11_ABI): f"pytorch/libtorch-cxx11-builder:cuda{gpu_arch}"
for gpu_arch in CUDA_ARCHES
},
**{
(gpu_arch, PRE_CXX11_ABI): f"pytorch/manylinux-builder:rocm{gpu_arch}"
for gpu_arch in ROCM_ARCHES
},
**{
(gpu_arch, CXX11_ABI): f"pytorch/libtorch-cxx11-builder:rocm{gpu_arch}"
for gpu_arch in ROCM_ARCHES
},
("cpu", PRE_CXX11_ABI): "pytorch/manylinux-builder:cpu",
("cpu", CXX11_ABI): "pytorch/libtorch-cxx11-builder:cpu",
}
FULL_PYTHON_VERSIONS = ["3.8", "3.9", "3.10"]
def translate_desired_cuda(gpu_arch_type: str, gpu_arch_version: str) -> str:
return {
"cpu": "cpu",
"cuda": f"cu{gpu_arch_version.replace('.', '')}",
"rocm": f"rocm{gpu_arch_version}",
}.get(gpu_arch_type, gpu_arch_version)
def list_without(in_list: List[str], without: List[str]) -> List[str]:
return [item for item in in_list if item not in without]
def generate_conda_matrix(os: str) -> List[Dict[str, str]]:
ret: List[Dict[str, str]] = []
arches = ["cpu"]
python_versions = list(FULL_PYTHON_VERSIONS)
if os == "linux":
# NOTE: We only build 3.11 on linux right now as many dependencies
# are yet not available on conda
python_versions.append("3.11")
if os == "linux" or os == "windows":
arches += CUDA_ARCHES
for python_version in python_versions:
# We don't currently build conda packages for rocm
for arch_version in arches:
gpu_arch_type = arch_type(arch_version)
gpu_arch_version = "" if arch_version == "cpu" else arch_version
ret.append(
{
"python_version": python_version,
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"container_image": CONDA_CONTAINER_IMAGES[arch_version],
"package_type": "conda",
"build_name": f"conda-py{python_version}-{gpu_arch_type}{gpu_arch_version}".replace(
".", "_"
),
}
)
return ret
def generate_libtorch_matrix(os: str, abi_version: str,
arches: Optional[List[str]] = None,
libtorch_variants: Optional[List[str]] = None) -> List[Dict[str, str]]:
if arches is None:
arches = ["cpu"]
if os == "linux":
arches += CUDA_ARCHES
arches += ROCM_ARCHES
elif os == "windows":
arches += CUDA_ARCHES
if libtorch_variants is None:
libtorch_variants = [
"shared-with-deps",
"shared-without-deps",
"static-with-deps",
"static-without-deps",
]
ret: List[Dict[str, str]] = []
for arch_version in arches:
for libtorch_variant in libtorch_variants:
# one of the values in the following list must be exactly
# CXX11_ABI, but the precise value of the other one doesn't
# matter
gpu_arch_type = arch_type(arch_version)
gpu_arch_version = "" if arch_version == "cpu" else arch_version
# ROCm builds without-deps failed even in ROCm runners; skip for now
if gpu_arch_type == "rocm" and "without-deps" in libtorch_variant:
continue
ret.append(
{
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"libtorch_variant": libtorch_variant,
"libtorch_config": abi_version if os == "windows" else "",
"devtoolset": abi_version if os != "windows" else "",
"container_image": LIBTORCH_CONTAINER_IMAGES[
(arch_version, abi_version)
] if os != "windows" else "",
"package_type": "libtorch",
"build_name": f"libtorch-{gpu_arch_type}{gpu_arch_version}-{libtorch_variant}-{abi_version}".replace(
".", "_"
),
}
)
return ret
def generate_wheels_matrix(os: str,
arches: Optional[List[str]] = None,
python_versions: Optional[List[str]] = None) -> List[Dict[str, str]]:
package_type = "wheel"
if os == "linux":
# NOTE: We only build manywheel packages for linux
package_type = "manywheel"
if python_versions is None:
# Define default python version
python_versions = list(FULL_PYTHON_VERSIONS)
if os == "linux":
# NOTE: We only build 3.11 wheel on linux as 3.11 is not
# available on conda right now
python_versions.append("3.11")
if arches is None:
# Define default compute archivectures
arches = ["cpu"]
if os == "linux":
arches += CUDA_ARCHES + ROCM_ARCHES
elif os == "windows":
arches += CUDA_ARCHES
ret: List[Dict[str, str]] = []
for python_version in python_versions:
for arch_version in arches:
gpu_arch_type = arch_type(arch_version)
gpu_arch_version = "" if arch_version == "cpu" else arch_version
# Skip rocm 3.11 binaries for now as the docker image are not correct
if python_version == "3.11" and gpu_arch_type == "rocm":
continue
# special 11.7 wheels package without dependencies
# dependency downloaded via pip install
if arch_version == "11.7" and os == "linux":
ret.append(
{
"python_version": python_version,
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"pytorch_extra_install_requirements":
"nvidia-cuda-nvrtc-cu11==11.7.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu11==11.7.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu11==11.7.101; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu11==8.5.0.96; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu11==11.10.3.66; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu11==10.2.10.91; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu11==11.4.0.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu11==11.7.4.91; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu11==2.14.3; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu11==11.7.91; platform_system == 'Linux' and platform_machine == 'x86_64'",
"build_name":
f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-with-pypi-cudnn"
.replace(
".", "_"
),
}
)
ret.append(
{
"python_version": python_version,
"gpu_arch_type": gpu_arch_type,
"gpu_arch_version": gpu_arch_version,
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}".replace(
".", "_"
),
}
)
return ret