import torch from setuptools import setup, find_packages import subprocess import sys import warnings import os # ninja build does not work unless include_dirs are abs path this_dir = os.path.dirname(os.path.abspath(__file__)) 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, Apex will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n' 'Volta (compute capability 7.0), and Turing (compute capability 7.5).\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: os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5" print("torch.__version__ = ", torch.__version__) TORCH_MAJOR = int(torch.__version__.split('.')[0]) TORCH_MINOR = int(torch.__version__.split('.')[1]) if TORCH_MAJOR == 0 and TORCH_MINOR < 4: raise RuntimeError("Apex requires Pytorch 0.4 or newer.\n" + "The latest stable release can be obtained from https://pytorch.org/") cmdclass = {} ext_modules = [] extras = {} if "--pyprof" in sys.argv: with open('requirements.txt') as f: required_packages = f.read().splitlines() extras['pyprof'] = required_packages try: sys.argv.remove("--pyprof") except: pass else: warnings.warn("Option --pyprof not specified. Not installing PyProf dependencies!") if "--cpp_ext" in sys.argv or "--cuda_ext" in sys.argv: if TORCH_MAJOR == 0: raise RuntimeError("--cpp_ext requires Pytorch 1.0 or later, " "found torch.__version__ = {}".format(torch.__version__)) from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension if "--cpp_ext" in sys.argv: from torch.utils.cpp_extension import CppExtension sys.argv.remove("--cpp_ext") ext_modules.append( CppExtension('apex_C', ['csrc/flatten_unflatten.cpp',])) def check_cuda_torch_binary_vs_bare_metal(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] 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) or (bare_metal_minor != torch_binary_minor): raise RuntimeError("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. " "You can try commenting out this check (at your own risk).") # 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_ge_1_1 = [] if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0): version_ge_1_1 = ['-DVERSION_GE_1_1'] version_ge_1_3 = [] if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 2): version_ge_1_3 = ['-DVERSION_GE_1_3'] version_ge_1_5 = [] if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 4): version_ge_1_5 = ['-DVERSION_GE_1_5'] version_dependent_macros = version_ge_1_1 + version_ge_1_3 + version_ge_1_5 if "--cuda_ext" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--cuda_ext") if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--cuda_ext was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: check_cuda_torch_binary_vs_bare_metal(torch.utils.cpp_extension.CUDA_HOME) ext_modules.append( CUDAExtension(name='amp_C', sources=['csrc/amp_C_frontend.cpp', 'csrc/multi_tensor_sgd_kernel.cu', 'csrc/multi_tensor_scale_kernel.cu', 'csrc/multi_tensor_axpby_kernel.cu', 'csrc/multi_tensor_l2norm_kernel.cu', 'csrc/multi_tensor_lamb_stage_1.cu', 'csrc/multi_tensor_lamb_stage_2.cu', 'csrc/multi_tensor_adam.cu', 'csrc/multi_tensor_adagrad.cu', 'csrc/multi_tensor_novograd.cu', 'csrc/multi_tensor_lamb.cu'], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros, 'nvcc':['-lineinfo', '-O3', # '--resource-usage', '--use_fast_math'] + version_dependent_macros})) ext_modules.append( CUDAExtension(name='syncbn', sources=['csrc/syncbn.cpp', 'csrc/welford.cu'], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros, 'nvcc':['-O3'] + version_dependent_macros})) ext_modules.append( CUDAExtension(name='fused_layer_norm_cuda', sources=['csrc/layer_norm_cuda.cpp', 'csrc/layer_norm_cuda_kernel.cu'], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros, 'nvcc':['-maxrregcount=50', '-O3', '--use_fast_math'] + version_dependent_macros})) ext_modules.append( CUDAExtension(name='mlp_cuda', sources=['csrc/mlp.cpp', 'csrc/mlp_cuda.cu'], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros, 'nvcc':['-O3'] + version_dependent_macros})) if "--bnp" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--bnp") from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--bnp was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: ext_modules.append( CUDAExtension(name='bnp', sources=['apex/contrib/csrc/groupbn/batch_norm.cu', 'apex/contrib/csrc/groupbn/ipc.cu', 'apex/contrib/csrc/groupbn/interface.cpp', 'apex/contrib/csrc/groupbn/batch_norm_add_relu.cu'], include_dirs=[os.path.join(this_dir, 'csrc')], extra_compile_args={'cxx': [] + version_dependent_macros, 'nvcc':['-DCUDA_HAS_FP16=1', '-D__CUDA_NO_HALF_OPERATORS__', '-D__CUDA_NO_HALF_CONVERSIONS__', '-D__CUDA_NO_HALF2_OPERATORS__'] + version_dependent_macros})) if "--xentropy" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--xentropy") from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--xentropy was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: ext_modules.append( CUDAExtension(name='xentropy_cuda', sources=['apex/contrib/csrc/xentropy/interface.cpp', 'apex/contrib/csrc/xentropy/xentropy_kernel.cu'], include_dirs=[os.path.join(this_dir, 'csrc')], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros, 'nvcc':['-O3'] + version_dependent_macros})) if "--deprecated_fused_adam" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--deprecated_fused_adam") from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--deprecated_fused_adam was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: ext_modules.append( CUDAExtension(name='fused_adam_cuda', sources=['apex/contrib/csrc/optimizers/fused_adam_cuda.cpp', 'apex/contrib/csrc/optimizers/fused_adam_cuda_kernel.cu'], include_dirs=[os.path.join(this_dir, 'csrc')], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros, 'nvcc':['-O3', '--use_fast_math'] + version_dependent_macros})) if "--deprecated_fused_lamb" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--deprecated_fused_lamb") from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--deprecated_fused_lamb was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: ext_modules.append( CUDAExtension(name='fused_lamb_cuda', sources=['apex/contrib/csrc/optimizers/fused_lamb_cuda.cpp', 'apex/contrib/csrc/optimizers/fused_lamb_cuda_kernel.cu', 'csrc/multi_tensor_l2norm_kernel.cu'], include_dirs=[os.path.join(this_dir, 'csrc')], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros, 'nvcc':['-O3', '--use_fast_math'] + version_dependent_macros})) # Check, if ATen/CUDAGenerator.h is found, otherwise use the new ATen/CUDAGeneratorImpl.h, due to breaking change in https://github.com/pytorch/pytorch/pull/36026 generator_flag = [] torch_dir = torch.__path__[0] if os.path.exists(os.path.join(torch_dir, 'include', 'ATen', 'CUDAGenerator.h')): generator_flag = ['-DOLD_GENERATOR'] if "--fast_multihead_attn" in sys.argv: from torch.utils.cpp_extension import CUDAExtension sys.argv.remove("--fast_multihead_attn") from torch.utils.cpp_extension import BuildExtension cmdclass['build_ext'] = BuildExtension.with_options(use_ninja=False) if torch.utils.cpp_extension.CUDA_HOME is None: raise RuntimeError("--fast_multihead_attn was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") else: subprocess.run(["git", "submodule", "update", "--init", "apex/contrib/csrc/multihead_attn/cutlass"]) ext_modules.append( CUDAExtension(name='fast_self_multihead_attn', sources=['apex/contrib/csrc/multihead_attn/self_multihead_attn.cpp', 'apex/contrib/csrc/multihead_attn/self_multihead_attn_cuda.cu'], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros + generator_flag, 'nvcc':['-O3', '-gencode', 'arch=compute_70,code=sm_70', '-I./apex/contrib/csrc/multihead_attn/cutlass/', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr', '--expt-extended-lambda', '--use_fast_math'] + version_dependent_macros + generator_flag})) ext_modules.append( CUDAExtension(name='fast_self_multihead_attn_norm_add', sources=['apex/contrib/csrc/multihead_attn/self_multihead_attn_norm_add.cpp', 'apex/contrib/csrc/multihead_attn/self_multihead_attn_norm_add_cuda.cu'], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros + generator_flag, 'nvcc':['-O3', '-gencode', 'arch=compute_70,code=sm_70', '-I./apex/contrib/csrc/multihead_attn/cutlass/', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr', '--expt-extended-lambda', '--use_fast_math'] + version_dependent_macros + generator_flag})) ext_modules.append( CUDAExtension(name='fast_encdec_multihead_attn', sources=['apex/contrib/csrc/multihead_attn/encdec_multihead_attn.cpp', 'apex/contrib/csrc/multihead_attn/encdec_multihead_attn_cuda.cu'], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros + generator_flag, 'nvcc':['-O3', '-gencode', 'arch=compute_70,code=sm_70', '-I./apex/contrib/csrc/multihead_attn/cutlass/', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr', '--expt-extended-lambda', '--use_fast_math'] + version_dependent_macros + generator_flag})) ext_modules.append( CUDAExtension(name='fast_encdec_multihead_attn_norm_add', sources=['apex/contrib/csrc/multihead_attn/encdec_multihead_attn_norm_add.cpp', 'apex/contrib/csrc/multihead_attn/encdec_multihead_attn_norm_add_cuda.cu'], extra_compile_args={'cxx': ['-O3',] + version_dependent_macros + generator_flag, 'nvcc':['-O3', '-gencode', 'arch=compute_70,code=sm_70', '-I./apex/contrib/csrc/multihead_attn/cutlass/', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr', '--expt-extended-lambda', '--use_fast_math'] + version_dependent_macros + generator_flag})) setup( name='apex', version='0.1', packages=find_packages(exclude=('build', 'csrc', 'include', 'tests', 'dist', 'docs', 'tests', 'examples', 'apex.egg-info',)), description='PyTorch Extensions written by NVIDIA', ext_modules=ext_modules, cmdclass=cmdclass, extras_require=extras, )