ColossalAI/setup.py

import os
import subprocess
import sys

from setuptools import find_packages, setup

# ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))
build_cuda_ext = True
ext_modules = []

if '--no_cuda_ext' in sys.argv:
    sys.argv.remove('--no_cuda_ext')
    build_cuda_ext = False


def get_cuda_bare_metal_version(cuda_dir):
    raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
    output = raw_output.split()
    release_idx = output.index("release") + 1
    release = output[release_idx].split(".")
    bare_metal_major = release[0]
    bare_metal_minor = release[1][0]

    return raw_output, bare_metal_major, bare_metal_minor


def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
    raw_output, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(cuda_dir)
    torch_binary_major = torch.version.cuda.split(".")[0]
    torch_binary_minor = torch.version.cuda.split(".")[1]

    print("\nCompiling cuda extensions with")
    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.')
        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. ")
    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')
        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:
                os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0"
            else:
                os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
        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.")
        return False
    return True


def append_nvcc_threads(nvcc_extra_args):
    _, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(CUDA_HOME)
    if int(bare_metal_major) >= 11 and int(bare_metal_minor) >= 2:
        return nvcc_extra_args + ["--threads", "4"]
    return nvcc_extra_args


def fetch_requirements(path):
    with open(path, 'r') as fd:
        return [r.strip() for r in fd.readlines()]


if build_cuda_ext:
    try:
        import torch
        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/")
    except ImportError:
        print('torch is not found. CUDA extension will not be installed')
        build_cuda_ext = False

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
    # and
    # https://github.com/NVIDIA/apex/issues/456
    # https://github.com/pytorch/pytorch/commit/eb7b39e02f7d75c26d8a795ea8c7fd911334da7e#diff-4632522f237f1e4e728cb824300403ac
    version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']

    def cuda_ext_helper(name, sources, 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,
                                                 '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']))

    cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
    _, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
    if int(bare_metal_major) >= 11:
        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']

    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))

    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))

    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))

setup(
    name='colossalai',
    version='0.0.2',
    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',
    ext_modules=ext_modules,
    cmdclass={'build_ext': BuildExtension} if ext_modules else {},
    install_requires=fetch_requirements('requirements/requirements.txt'),
    extras_require={
        'zero': fetch_requirements('requirements/requirements-zero.txt'),
    }
)