diff --git a/setup.py b/setup.py index 292f82bd0..d683a432f 100644 --- a/setup.py +++ b/setup.py @@ -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',