mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 00:20:18 +01:00
b1d62febd0
This reverts commit 08dae945ae.
Reverted https://github.com/pytorch/pytorch/pull/154595 on behalf of https://github.com/malfet due to It breaks on some local setup with no clear diagnostic, but looks like it fails to find cuFile ([comment](https://github.com/pytorch/pytorch/pull/154595#issuecomment-2997959344))
259 lines
9.0 KiB
Python
Executable File
259 lines
9.0 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# encoding: UTF-8
|
|
|
|
import os
|
|
import shutil
|
|
from subprocess import check_call, check_output
|
|
|
|
|
|
def list_dir(path: str) -> list[str]:
|
|
"""'
|
|
Helper for getting paths for Python
|
|
"""
|
|
return check_output(["ls", "-1", path]).decode().split("\n")
|
|
|
|
|
|
def build_ArmComputeLibrary() -> None:
|
|
"""
|
|
Using ArmComputeLibrary for aarch64 PyTorch
|
|
"""
|
|
print("Building Arm Compute Library")
|
|
acl_build_flags = [
|
|
"debug=0",
|
|
"neon=1",
|
|
"opencl=0",
|
|
"os=linux",
|
|
"openmp=1",
|
|
"cppthreads=0",
|
|
"arch=armv8a",
|
|
"multi_isa=1",
|
|
"fixed_format_kernels=1",
|
|
"build=native",
|
|
]
|
|
acl_install_dir = "/acl"
|
|
acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
|
|
if os.path.isdir(acl_install_dir):
|
|
shutil.rmtree(acl_install_dir)
|
|
if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
|
|
check_call(
|
|
[
|
|
"git",
|
|
"clone",
|
|
"https://github.com/ARM-software/ComputeLibrary.git",
|
|
"-b",
|
|
"v25.02",
|
|
"--depth",
|
|
"1",
|
|
"--shallow-submodules",
|
|
]
|
|
)
|
|
|
|
check_call(
|
|
["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
|
|
cwd=acl_checkout_dir,
|
|
)
|
|
for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
|
|
shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
|
|
|
|
|
|
def replace_tag(filename) -> None:
|
|
with open(filename) as f:
|
|
lines = f.readlines()
|
|
for i, line in enumerate(lines):
|
|
if line.startswith("Tag:"):
|
|
lines[i] = line.replace("-linux_", "-manylinux_2_28_")
|
|
print(f"Updated tag from {line} to {lines[i]}")
|
|
break
|
|
|
|
with open(filename, "w") as f:
|
|
f.writelines(lines)
|
|
|
|
|
|
def package_cuda_wheel(wheel_path, desired_cuda) -> None:
|
|
"""
|
|
Package the cuda wheel libraries
|
|
"""
|
|
folder = os.path.dirname(wheel_path)
|
|
wheelname = os.path.basename(wheel_path)
|
|
os.mkdir(f"{folder}/tmp")
|
|
os.system(f"unzip {wheel_path} -d {folder}/tmp")
|
|
libs_to_copy = [
|
|
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12",
|
|
"/usr/local/cuda/lib64/libcudnn.so.9",
|
|
"/usr/local/cuda/lib64/libcublas.so.12",
|
|
"/usr/local/cuda/lib64/libcublasLt.so.12",
|
|
"/usr/local/cuda/lib64/libcudart.so.12",
|
|
"/usr/local/cuda/lib64/libcufft.so.11",
|
|
"/usr/local/cuda/lib64/libcusparse.so.12",
|
|
"/usr/local/cuda/lib64/libcusparseLt.so.0",
|
|
"/usr/local/cuda/lib64/libcusolver.so.11",
|
|
"/usr/local/cuda/lib64/libcurand.so.10",
|
|
"/usr/local/cuda/lib64/libnvJitLink.so.12",
|
|
"/usr/local/cuda/lib64/libnvrtc.so.12",
|
|
"/usr/local/cuda/lib64/libcudnn_adv.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_cnn.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_graph.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_ops.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9",
|
|
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9",
|
|
"/lib64/libgomp.so.1",
|
|
"/usr/lib64/libgfortran.so.5",
|
|
"/acl/build/libarm_compute.so",
|
|
"/acl/build/libarm_compute_graph.so",
|
|
"/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
|
|
"/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
|
|
"/usr/local/lib/libnvpl_lapack_core.so.0",
|
|
"/usr/local/lib/libnvpl_blas_core.so.0",
|
|
]
|
|
|
|
if "129" in desired_cuda:
|
|
libs_to_copy += [
|
|
"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.9",
|
|
"/usr/local/cuda/lib64/libcufile.so.0",
|
|
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
|
|
]
|
|
|
|
# Copy libraries to unzipped_folder/a/lib
|
|
for lib_path in libs_to_copy:
|
|
lib_name = os.path.basename(lib_path)
|
|
shutil.copy2(lib_path, f"{folder}/tmp/torch/lib/{lib_name}")
|
|
os.system(
|
|
f"cd {folder}/tmp/torch/lib/; "
|
|
f"patchelf --set-rpath '$ORIGIN' --force-rpath {folder}/tmp/torch/lib/{lib_name}"
|
|
)
|
|
|
|
# Make sure the wheel is tagged with manylinux_2_28
|
|
for f in os.scandir(f"{folder}/tmp/"):
|
|
if f.is_dir() and f.name.endswith(".dist-info"):
|
|
replace_tag(f"{f.path}/WHEEL")
|
|
break
|
|
|
|
os.mkdir(f"{folder}/cuda_wheel")
|
|
os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
|
|
shutil.move(
|
|
f"{folder}/cuda_wheel/{wheelname}",
|
|
f"{folder}/{wheelname}",
|
|
copy_function=shutil.copy2,
|
|
)
|
|
os.system(f"rm -rf {folder}/tmp/ {folder}/cuda_wheel/")
|
|
|
|
|
|
def complete_wheel(folder: str) -> str:
|
|
"""
|
|
Complete wheel build and put in artifact location
|
|
"""
|
|
wheel_name = list_dir(f"/{folder}/dist")[0]
|
|
|
|
# Please note for cuda we don't run auditwheel since we use custom script to package
|
|
# the cuda dependencies to the wheel file using update_wheel() method.
|
|
# However we need to make sure filename reflects the correct Manylinux platform.
|
|
if "pytorch" in folder and not enable_cuda:
|
|
print("Repairing Wheel with AuditWheel")
|
|
check_call(["auditwheel", "repair", f"dist/{wheel_name}"], cwd=folder)
|
|
repaired_wheel_name = list_dir(f"/{folder}/wheelhouse")[0]
|
|
|
|
print(f"Moving {repaired_wheel_name} wheel to /{folder}/dist")
|
|
os.rename(
|
|
f"/{folder}/wheelhouse/{repaired_wheel_name}",
|
|
f"/{folder}/dist/{repaired_wheel_name}",
|
|
)
|
|
else:
|
|
repaired_wheel_name = wheel_name.replace(
|
|
"linux_aarch64", "manylinux_2_28_aarch64"
|
|
)
|
|
print(f"Renaming {wheel_name} wheel to {repaired_wheel_name}")
|
|
os.rename(
|
|
f"/{folder}/dist/{wheel_name}",
|
|
f"/{folder}/dist/{repaired_wheel_name}",
|
|
)
|
|
|
|
print(f"Copying {repaired_wheel_name} to artifacts")
|
|
shutil.copy2(
|
|
f"/{folder}/dist/{repaired_wheel_name}", f"/artifacts/{repaired_wheel_name}"
|
|
)
|
|
|
|
return repaired_wheel_name
|
|
|
|
|
|
def parse_arguments():
|
|
"""
|
|
Parse inline arguments
|
|
"""
|
|
from argparse import ArgumentParser
|
|
|
|
parser = ArgumentParser("AARCH64 wheels python CD")
|
|
parser.add_argument("--debug", action="store_true")
|
|
parser.add_argument("--build-only", action="store_true")
|
|
parser.add_argument("--test-only", type=str)
|
|
parser.add_argument("--enable-mkldnn", action="store_true")
|
|
parser.add_argument("--enable-cuda", action="store_true")
|
|
return parser.parse_args()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
"""
|
|
Entry Point
|
|
"""
|
|
args = parse_arguments()
|
|
enable_mkldnn = args.enable_mkldnn
|
|
enable_cuda = args.enable_cuda
|
|
branch = check_output(
|
|
["git", "rev-parse", "--abbrev-ref", "HEAD"], cwd="/pytorch"
|
|
).decode()
|
|
|
|
print("Building PyTorch wheel")
|
|
build_vars = "CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
|
|
# MAX_JOB=5 is not required for CPU backend (see commit 465d98b)
|
|
if enable_cuda:
|
|
build_vars = "MAX_JOBS=5 " + build_vars
|
|
|
|
override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
|
|
desired_cuda = os.getenv("DESIRED_CUDA")
|
|
if override_package_version is not None:
|
|
version = override_package_version
|
|
build_vars += (
|
|
f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version} PYTORCH_BUILD_NUMBER=1 "
|
|
)
|
|
elif branch in ["nightly", "main"]:
|
|
build_date = (
|
|
check_output(["git", "log", "--pretty=format:%cs", "-1"], cwd="/pytorch")
|
|
.decode()
|
|
.replace("-", "")
|
|
)
|
|
version = (
|
|
check_output(["cat", "version.txt"], cwd="/pytorch").decode().strip()[:-2]
|
|
)
|
|
if enable_cuda:
|
|
build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date}+{desired_cuda} PYTORCH_BUILD_NUMBER=1 "
|
|
else:
|
|
build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date} PYTORCH_BUILD_NUMBER=1 "
|
|
elif branch.startswith(("v1.", "v2.")):
|
|
build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1 "
|
|
|
|
if enable_mkldnn:
|
|
build_ArmComputeLibrary()
|
|
print("build pytorch with mkldnn+acl backend")
|
|
build_vars += (
|
|
"USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
|
|
"ACL_ROOT_DIR=/acl "
|
|
"LD_LIBRARY_PATH=/pytorch/build/lib:/acl/build:$LD_LIBRARY_PATH "
|
|
"ACL_INCLUDE_DIR=/acl/build "
|
|
"ACL_LIBRARY=/acl/build "
|
|
)
|
|
if enable_cuda:
|
|
build_vars += "BLAS=NVPL "
|
|
else:
|
|
build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/OpenBLAS "
|
|
else:
|
|
print("build pytorch without mkldnn backend")
|
|
|
|
os.system(f"cd /pytorch; {build_vars} python3 setup.py bdist_wheel")
|
|
if enable_cuda:
|
|
print("Updating Cuda Dependency")
|
|
filename = os.listdir("/pytorch/dist/")
|
|
wheel_path = f"/pytorch/dist/{filename[0]}"
|
|
package_cuda_wheel(wheel_path, desired_cuda)
|
|
pytorch_wheel_name = complete_wheel("/pytorch/")
|
|
print(f"Build Complete. Created {pytorch_wheel_name}..")
|