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fix format setup.py (#343)

pull/394/head
xyupeng 2022-03-09 15:11:35 +08:00 committed by Frank Lee
parent 148207048e
commit af801cb4df
1 changed files with 73 additions and 82 deletions
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155
setup.py
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@ -34,31 +34,33 @@ def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
print(raw_output + "from " + cuda_dir + "/bin\n")
if bare_metal_major != torch_binary_major:
print(
f'The detected CUDA version ({raw_output}) mismatches the version that was used to compile PyTorch ({torch.version.cuda}). CUDA extension will not be installed.')
print(f'The detected CUDA version ({raw_output}) mismatches the version that was used to compile PyTorch '
f'({torch.version.cuda}). CUDA extension will not be installed.')
return False
if bare_metal_minor != torch_binary_minor:
print("\nWarning: Cuda extensions are being compiled with a version of Cuda that does "
+ "not match the version used to compile Pytorch binaries. "
+ "Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda)
+ "In some cases, a minor-version mismatch will not cause later errors: "
+ "https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. ")
"not match the version used to compile Pytorch binaries. "
f"Pytorch binaries were compiled with Cuda {torch.version.cuda}.\n"
"In some cases, a minor-version mismatch will not cause later errors: "
"https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. ")
return True
def check_cuda_availability(cuda_dir):
if not torch.cuda.is_available():
# https://github.com/NVIDIA/apex/issues/486
# Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query torch.cuda.get_device_capability(),
# which will fail if you are compiling in an environment without visible GPUs (e.g. during an nvidia-docker build command).
print('\nWarning: Torch did not find available GPUs on this system.\n',
'If your intention is to cross-compile, this is not an error.\n'
'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n'
'Volta (compute capability 7.0), Turing (compute capability 7.5),\n'
'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
'If you wish to cross-compile for a single specific architecture,\n'
'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
# Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query
# torch.cuda.get_device_capability(), which will fail if you are compiling in an environment
# without visible GPUs (e.g. during an nvidia-docker build command).
print(
'\nWarning: Torch did not find available GPUs on this system.\n',
'If your intention is to cross-compile, this is not an error.\n'
'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n'
'Volta (compute capability 7.0), Turing (compute capability 7.5),\n'
'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
'If you wish to cross-compile for a single specific architecture,\n'
'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
_, bare_metal_major, _ = get_cuda_bare_metal_version(cuda_dir)
if int(bare_metal_major) == 11:
@ -68,8 +70,8 @@ def check_cuda_availability(cuda_dir):
return False
if cuda_dir is None:
print(
"nvcc was not found. CUDA extension will not be installed. If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
print("nvcc was not found. CUDA extension will not be installed. If you're installing within a container from "
"https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
return False
return True
@ -99,15 +101,14 @@ def get_version():
if build_cuda_ext:
try:
import torch
from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension,
CUDAExtension)
from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CUDAExtension)
print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__))
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
if TORCH_MAJOR < 1 or (TORCH_MAJOR == 1 and TORCH_MINOR < 8):
raise RuntimeError("Colossal-AI requires Pytorch 1.8 or newer.\n"
+ "The latest stable release can be obtained from https://pytorch.org/")
"The latest stable release can be obtained from https://pytorch.org/")
except ImportError:
print('torch is not found. CUDA extension will not be installed')
build_cuda_ext = False
@ -115,7 +116,6 @@ if build_cuda_ext:
if build_cuda_ext:
build_cuda_ext = check_cuda_availability(CUDA_HOME) and check_cuda_torch_binary_vs_bare_metal(CUDA_HOME)
if build_cuda_ext:
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
@ -125,22 +125,20 @@ if build_cuda_ext:
version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
def cuda_ext_helper(name, sources, extra_cuda_flags, extra_cxx_flags=[]):
return CUDAExtension(name=name,
sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in sources],
include_dirs=[os.path.join(
this_dir, 'colossalai/kernel/cuda_native/csrc/kernels/include')],
extra_compile_args={'cxx': ['-O3'] + version_dependent_macros + extra_cxx_flags,
'nvcc': append_nvcc_threads(['-O3',
'--use_fast_math'] + version_dependent_macros + extra_cuda_flags)})
return CUDAExtension(
name=name,
sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in sources],
include_dirs=[os.path.join(this_dir, 'colossalai/kernel/cuda_native/csrc/kernels/include')],
extra_compile_args={
'cxx': ['-O3'] + version_dependent_macros + extra_cxx_flags,
'nvcc': append_nvcc_threads(['-O3', '--use_fast_math'] + version_dependent_macros + extra_cuda_flags)
})
ext_modules.append(cuda_ext_helper('colossal_C',
['colossal_C_frontend.cpp',
'multi_tensor_sgd_kernel.cu',
'multi_tensor_scale_kernel.cu',
'multi_tensor_adam.cu',
'multi_tensor_l2norm_kernel.cu',
'multi_tensor_lamb.cu'],
['-lineinfo']))
ext_modules.append(
cuda_ext_helper('colossal_C', [
'colossal_C_frontend.cpp', 'multi_tensor_sgd_kernel.cu', 'multi_tensor_scale_kernel.cu',
'multi_tensor_adam.cu', 'multi_tensor_l2norm_kernel.cu', 'multi_tensor_lamb.cu'
], ['-lineinfo']))
cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
@ -148,65 +146,58 @@ if build_cuda_ext:
cc_flag.append('-gencode')
cc_flag.append('arch=compute_80,code=sm_80')
extra_cuda_flags = ['-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda']
extra_cuda_flags = [
'-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr',
'--expt-extended-lambda'
]
ext_modules.append(cuda_ext_helper('colossal_scaled_upper_triang_masked_softmax',
['scaled_upper_triang_masked_softmax.cpp',
'scaled_upper_triang_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(
cuda_ext_helper('colossal_scaled_upper_triang_masked_softmax',
['scaled_upper_triang_masked_softmax.cpp', 'scaled_upper_triang_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('colossal_scaled_masked_softmax',
['scaled_masked_softmax.cpp', 'scaled_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(
cuda_ext_helper('colossal_scaled_masked_softmax',
['scaled_masked_softmax.cpp', 'scaled_masked_softmax_cuda.cu'], extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('colossal_moe_cuda',
['moe_cuda.cpp', 'moe_cuda_kernel.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(
cuda_ext_helper('colossal_moe_cuda', ['moe_cuda.cpp', 'moe_cuda_kernel.cu'], extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-maxrregcount=50']
ext_modules.append(cuda_ext_helper('colossal_layer_norm_cuda',
['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(
cuda_ext_helper('colossal_layer_norm_cuda', ['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu'],
extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-std=c++14',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_HALF2_OPERATORS__',
'-DTHRUST_IGNORE_CUB_VERSION_CHECK']
extra_cuda_flags = [
'-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '-U__CUDA_NO_HALF2_OPERATORS__',
'-DTHRUST_IGNORE_CUB_VERSION_CHECK'
]
ext_modules.append(
cuda_ext_helper('colossal_multihead_attention', [
'multihead_attention_1d.cpp', 'kernels/cublas_wrappers.cu', 'kernels/transform_kernels.cu',
'kernels/dropout_kernels.cu', 'kernels/normalize_kernels.cu', 'kernels/softmax_kernels.cu',
'kernels/general_kernels.cu', 'kernels/cuda_util.cu'
], extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('colossal_multihead_attention',
['multihead_attention_1d.cpp',
'kernels/cublas_wrappers.cu',
'kernels/transform_kernels.cu',
'kernels/dropout_kernels.cu',
'kernels/normalize_kernels.cu',
'kernels/softmax_kernels.cu',
'kernels/general_kernels.cu',
'kernels/cuda_util.cu'],
extra_cuda_flags + cc_flag))
extra_cxx_flags = ['-std=c++14', '-lcudart', '-lcublas', '-g', '-Wno-reorder', '-fopenmp', '-march=native']
ext_modules.append(cuda_ext_helper('cpu_adam',
['cpu_adam.cpp'],
extra_cuda_flags,
extra_cxx_flags))
ext_modules.append(cuda_ext_helper('cpu_adam', ['cpu_adam.cpp'], extra_cuda_flags, extra_cxx_flags))
setup(
name='colossalai',
version=get_version(),
packages=find_packages(exclude=('benchmark',
'docker',
'tests',
'docs',
'examples',
'tests',
'scripts',
'requirements',
'*.egg-info',)),
packages=find_packages(exclude=(
'benchmark',
'docker',
'tests',
'docs',
'examples',
'tests',
'scripts',
'requirements',
'*.egg-info',
)),
description='An integrated large-scale model training system with efficient parallelization techniques',
long_description=fetch_readme(),
long_description_content_type='text/markdown',