399 lines
14 KiB
Python
399 lines
14 KiB
Python
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# Copyright (c) 2023, Albert Gu, Tri Dao.
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import sys
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import warnings
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import os
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import re
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import ast
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from pathlib import Path
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from packaging.version import parse, Version
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import platform
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import shutil
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from setuptools import setup, find_packages
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import subprocess
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import urllib.request
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import urllib.error
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from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
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import torch
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from torch.utils.cpp_extension import (
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BuildExtension,
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CppExtension,
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CUDAExtension,
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CUDA_HOME,
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HIP_HOME
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)
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with open("README.md", "r", encoding="utf-8") as fh:
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long_description = fh.read()
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# ninja build does not work unless include_dirs are abs path
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this_dir = os.path.dirname(os.path.abspath(__file__))
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PACKAGE_NAME = "mamba_ssm"
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BASE_WHEEL_URL = "https://github.com/state-spaces/mamba/releases/download/{tag_name}/{wheel_name}"
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# FORCE_BUILD: Force a fresh build locally, instead of attempting to find prebuilt wheels
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# SKIP_CUDA_BUILD: Intended to allow CI to use a simple `python setup.py sdist` run to copy over raw files, without any cuda compilation
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FORCE_BUILD = os.getenv("MAMBA_FORCE_BUILD", "FALSE") == "TRUE"
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SKIP_CUDA_BUILD = os.getenv("MAMBA_SKIP_CUDA_BUILD", "FALSE") == "TRUE"
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# For CI, we want the option to build with C++11 ABI since the nvcr images use C++11 ABI
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FORCE_CXX11_ABI = os.getenv("MAMBA_FORCE_CXX11_ABI", "FALSE") == "TRUE"
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def get_platform():
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"""
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Returns the platform name as used in wheel filenames.
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"""
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if sys.platform.startswith("linux"):
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return "linux_x86_64"
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elif sys.platform == "darwin":
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mac_version = ".".join(platform.mac_ver()[0].split(".")[:2])
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return f"macosx_{mac_version}_x86_64"
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elif sys.platform == "win32":
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return "win_amd64"
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else:
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raise ValueError("Unsupported platform: {}".format(sys.platform))
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def get_cuda_bare_metal_version(cuda_dir):
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raw_output = subprocess.check_output(
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[cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True
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)
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output = raw_output.split()
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release_idx = output.index("release") + 1
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bare_metal_ver = parse(output[release_idx].split(",")[0])
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return raw_output, bare_metal_ver
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def get_hip_version(rocm_dir):
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hipcc_bin = "hipcc" if rocm_dir is None else os.path.join(rocm_dir, "bin", "hipcc")
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try:
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raw_output = subprocess.check_output(
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[hipcc_bin, "--version"], universal_newlines=True
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)
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except Exception as e:
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print(
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f"hip installation not found: {e} ROCM_PATH={os.environ.get('ROCM_PATH')}"
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)
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return None, None
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for line in raw_output.split("\n"):
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if "HIP version" in line:
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rocm_version = parse(line.split()[-1].replace("-", "+")) # local version is not parsed correctly
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return line, rocm_version
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return None, None
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def get_torch_hip_version():
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if torch.version.hip:
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return parse(torch.version.hip.split()[-1].replace("-", "+"))
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else:
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return None
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def check_if_hip_home_none(global_option: str) -> None:
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if HIP_HOME is not None:
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return
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# warn instead of error because user could be downloading prebuilt wheels, so hipcc won't be necessary
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# in that case.
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warnings.warn(
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f"{global_option} was requested, but hipcc was not found. Are you sure your environment has hipcc available?"
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)
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def check_if_cuda_home_none(global_option: str) -> None:
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if CUDA_HOME is not None:
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return
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# warn instead of error because user could be downloading prebuilt wheels, so nvcc won't be necessary
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# in that case.
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warnings.warn(
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f"{global_option} was requested, but nvcc was not found. Are you sure your environment has nvcc available? "
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"If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, "
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"only images whose names contain 'devel' will provide nvcc."
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)
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def append_nvcc_threads(nvcc_extra_args):
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return nvcc_extra_args + ["--threads", "4"]
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cmdclass = {}
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ext_modules = []
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HIP_BUILD = bool(torch.version.hip)
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if not SKIP_CUDA_BUILD:
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print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__))
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TORCH_MAJOR = int(torch.__version__.split(".")[0])
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TORCH_MINOR = int(torch.__version__.split(".")[1])
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cc_flag = []
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if HIP_BUILD:
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check_if_hip_home_none(PACKAGE_NAME)
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rocm_home = os.getenv("ROCM_PATH")
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_, hip_version = get_hip_version(rocm_home)
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if HIP_HOME is not None:
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if hip_version < Version("6.0"):
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raise RuntimeError(
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f"{PACKAGE_NAME} is only supported on ROCm 6.0 and above. "
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"Note: make sure HIP has a supported version by running hipcc --version."
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)
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if hip_version == Version("6.0"):
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warnings.warn(
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f"{PACKAGE_NAME} requires a patch to be applied when running on ROCm 6.0. "
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"Refer to the README.md for detailed instructions.",
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UserWarning
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)
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cc_flag.append("-DBUILD_PYTHON_PACKAGE")
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else:
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check_if_cuda_home_none(PACKAGE_NAME)
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# Check, if CUDA11 is installed for compute capability 8.0
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if CUDA_HOME is not None:
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_, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME)
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if bare_metal_version < Version("11.6"):
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raise RuntimeError(
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f"{PACKAGE_NAME} is only supported on CUDA 11.6 and above. "
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"Note: make sure nvcc has a supported version by running nvcc -V."
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)
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_53,code=sm_53")
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_62,code=sm_62")
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_70,code=sm_70")
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_72,code=sm_72")
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_80,code=sm_80")
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_87,code=sm_87")
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if bare_metal_version >= Version("11.8"):
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cc_flag.append("-gencode")
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cc_flag.append("arch=compute_90,code=sm_90")
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# HACK: The compiler flag -D_GLIBCXX_USE_CXX11_ABI is set to be the same as
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# torch._C._GLIBCXX_USE_CXX11_ABI
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# https://github.com/pytorch/pytorch/blob/8472c24e3b5b60150096486616d98b7bea01500b/torch/utils/cpp_extension.py#L920
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if FORCE_CXX11_ABI:
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torch._C._GLIBCXX_USE_CXX11_ABI = True
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if HIP_BUILD:
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try:
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# set warp size based on gcn architecure
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gcn_arch_name = torch.cuda.get_device_properties(0).gcnArchName
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if "gfx10" in gcn_arch_name or "gfx11" in gcn_arch_name:
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# radeon
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warp_size = 32
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else:
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# instinct
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warp_size = 64
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except AttributeError as e:
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# fall back to crude method to set warp size
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device_name = torch.cuda.get_device_properties(0).name
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if 'instinct' in device_name.lower():
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warp_size = 64
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else:
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warp_size = 32
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extra_compile_args = {
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"cxx": ["-O3", "-std=c++17"],
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"nvcc": [
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"-O3",
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"-std=c++17",
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f"--offload-arch={os.getenv('HIP_ARCHITECTURES', 'native')}",
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"-U__CUDA_NO_HALF_OPERATORS__",
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"-U__CUDA_NO_HALF_CONVERSIONS__",
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"-DCK_FMHA_FWD_FAST_EXP2=1",
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"-fgpu-flush-denormals-to-zero",
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f"-DROCM_WARP_SIZE={warp_size}"
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]
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+ cc_flag,
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}
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else:
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extra_compile_args = {
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"cxx": ["-O3", "-std=c++17"],
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"nvcc": append_nvcc_threads(
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[
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"-O3",
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"-std=c++17",
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"-U__CUDA_NO_HALF_OPERATORS__",
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"-U__CUDA_NO_HALF_CONVERSIONS__",
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"-U__CUDA_NO_BFLOAT16_OPERATORS__",
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"-U__CUDA_NO_BFLOAT16_CONVERSIONS__",
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"-U__CUDA_NO_BFLOAT162_OPERATORS__",
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"-U__CUDA_NO_BFLOAT162_CONVERSIONS__",
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"--expt-relaxed-constexpr",
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"--expt-extended-lambda",
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"--use_fast_math",
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"--ptxas-options=-v",
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"-lineinfo",
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]
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+ cc_flag
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),
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}
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ext_modules.append(
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CUDAExtension(
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name="selective_scan_cuda",
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sources=[
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"csrc/selective_scan/selective_scan.cpp",
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"csrc/selective_scan/selective_scan_fwd_fp32.cu",
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"csrc/selective_scan/selective_scan_fwd_fp16.cu",
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"csrc/selective_scan/selective_scan_fwd_bf16.cu",
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"csrc/selective_scan/selective_scan_bwd_fp32_real.cu",
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"csrc/selective_scan/selective_scan_bwd_fp32_complex.cu",
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"csrc/selective_scan/selective_scan_bwd_fp16_real.cu",
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"csrc/selective_scan/selective_scan_bwd_fp16_complex.cu",
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"csrc/selective_scan/selective_scan_bwd_bf16_real.cu",
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"csrc/selective_scan/selective_scan_bwd_bf16_complex.cu",
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],
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extra_compile_args=extra_compile_args,
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include_dirs=[Path(this_dir) / "csrc" / "selective_scan"],
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)
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)
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def get_package_version():
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with open(Path(this_dir) / PACKAGE_NAME / "__init__.py", "r") as f:
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version_match = re.search(r"^__version__\s*=\s*(.*)$", f.read(), re.MULTILINE)
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public_version = ast.literal_eval(version_match.group(1))
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local_version = os.environ.get("MAMBA_LOCAL_VERSION")
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if local_version:
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return f"{public_version}+{local_version}"
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else:
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return str(public_version)
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def get_wheel_url():
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# Determine the version numbers that will be used to determine the correct wheel
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torch_version_raw = parse(torch.__version__)
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if HIP_BUILD:
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# We're using the HIP version used to build torch, not the one currently installed
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torch_hip_version = get_torch_hip_version()
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hip_ver = f"{torch_hip_version.major}{torch_hip_version.minor}"
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else:
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# We're using the CUDA version used to build torch, not the one currently installed
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# _, cuda_version_raw = get_cuda_bare_metal_version(CUDA_HOME)
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torch_cuda_version = parse(torch.version.cuda)
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# For CUDA 11, we only compile for CUDA 11.8, and for CUDA 12 we only compile for CUDA 12.2
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# to save CI time. Minor versions should be compatible.
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torch_cuda_version = parse("11.8") if torch_cuda_version.major == 11 else parse("12.2")
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cuda_version = f"{torch_cuda_version.major}{torch_cuda_version.minor}"
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gpu_compute_version = hip_ver if HIP_BUILD else cuda_version
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cuda_or_hip = "hip" if HIP_BUILD else "cu"
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python_version = f"cp{sys.version_info.major}{sys.version_info.minor}"
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platform_name = get_platform()
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mamba_ssm_version = get_package_version()
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torch_version = f"{torch_version_raw.major}.{torch_version_raw.minor}"
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cxx11_abi = str(torch._C._GLIBCXX_USE_CXX11_ABI).upper()
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# Determine wheel URL based on CUDA version, torch version, python version and OS
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wheel_filename = f"{PACKAGE_NAME}-{mamba_ssm_version}+{cuda_or_hip}{gpu_compute_version}torch{torch_version}cxx11abi{cxx11_abi}-{python_version}-{python_version}-{platform_name}.whl"
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wheel_url = BASE_WHEEL_URL.format(
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tag_name=f"v{mamba_ssm_version}", wheel_name=wheel_filename
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)
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return wheel_url, wheel_filename
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class CachedWheelsCommand(_bdist_wheel):
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"""
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The CachedWheelsCommand plugs into the default bdist wheel, which is ran by pip when it cannot
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find an existing wheel (which is currently the case for all installs). We use
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the environment parameters to detect whether there is already a pre-built version of a compatible
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wheel available and short-circuits the standard full build pipeline.
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"""
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def run(self):
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if FORCE_BUILD:
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return super().run()
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wheel_url, wheel_filename = get_wheel_url()
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print("Guessing wheel URL: ", wheel_url)
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try:
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urllib.request.urlretrieve(wheel_url, wheel_filename)
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# Make the archive
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# Lifted from the root wheel processing command
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# https://github.com/pypa/wheel/blob/cf71108ff9f6ffc36978069acb28824b44ae028e/src/wheel/bdist_wheel.py#LL381C9-L381C85
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if not os.path.exists(self.dist_dir):
|
||
|
|
os.makedirs(self.dist_dir)
|
||
|
|
|
||
|
|
impl_tag, abi_tag, plat_tag = self.get_tag()
|
||
|
|
archive_basename = f"{self.wheel_dist_name}-{impl_tag}-{abi_tag}-{plat_tag}"
|
||
|
|
|
||
|
|
wheel_path = os.path.join(self.dist_dir, archive_basename + ".whl")
|
||
|
|
print("Raw wheel path", wheel_path)
|
||
|
|
shutil.move(wheel_filename, wheel_path)
|
||
|
|
except urllib.error.HTTPError:
|
||
|
|
print("Precompiled wheel not found. Building from source...")
|
||
|
|
# If the wheel could not be downloaded, build from source
|
||
|
|
super().run()
|
||
|
|
|
||
|
|
setup(
|
||
|
|
name=PACKAGE_NAME,
|
||
|
|
version=get_package_version(),
|
||
|
|
packages=find_packages(
|
||
|
|
exclude=(
|
||
|
|
"build",
|
||
|
|
"csrc",
|
||
|
|
"include",
|
||
|
|
"tests",
|
||
|
|
"dist",
|
||
|
|
"docs",
|
||
|
|
"benchmarks",
|
||
|
|
"mamba_ssm.egg-info",
|
||
|
|
)
|
||
|
|
),
|
||
|
|
author="Tri Dao, Albert Gu",
|
||
|
|
author_email="tri@tridao.me, agu@cs.cmu.edu",
|
||
|
|
description="Mamba state-space model",
|
||
|
|
long_description=long_description,
|
||
|
|
long_description_content_type="text/markdown",
|
||
|
|
url="https://github.com/state-spaces/mamba",
|
||
|
|
classifiers=[
|
||
|
|
"Programming Language :: Python :: 3",
|
||
|
|
"License :: OSI Approved :: BSD License",
|
||
|
|
"Operating System :: Unix",
|
||
|
|
],
|
||
|
|
ext_modules=ext_modules,
|
||
|
|
cmdclass={"bdist_wheel": CachedWheelsCommand, "build_ext": BuildExtension}
|
||
|
|
if ext_modules
|
||
|
|
else {
|
||
|
|
"bdist_wheel": CachedWheelsCommand,
|
||
|
|
},
|
||
|
|
python_requires=">=3.7",
|
||
|
|
install_requires=[
|
||
|
|
"torch",
|
||
|
|
"packaging",
|
||
|
|
"ninja",
|
||
|
|
"einops",
|
||
|
|
"triton",
|
||
|
|
"transformers",
|
||
|
|
# "causal_conv1d>=1.2.0",
|
||
|
|
],
|
||
|
|
)
|