Making large AI models cheaper, faster and more accessible
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from .builder import Builder
from .utils import append_nvcc_threads
class CPUAdamBuilder(Builder):
NAME = "cpu_adam"
PREBUILT_IMPORT_PATH = "colossalai._C.cpu_adam"
def __init__(self):
super().__init__(name=CPUAdamBuilder.NAME, prebuilt_import_path=CPUAdamBuilder.PREBUILT_IMPORT_PATH)
self.version_dependent_macros = ["-DVERSION_GE_1_1", "-DVERSION_GE_1_3", "-DVERSION_GE_1_5"]
# necessary 4 functions
def sources_files(self):
ret = [
self.csrc_abs_path("cpu_adam.cpp"),
]
return ret
def include_dirs(self):
return [self.csrc_abs_path("includes"), self.get_cuda_home_include()]
def cxx_flags(self):
extra_cxx_flags = [
"-std=c++14",
"-std=c++17",
"-lcudart",
"-lcublas",
"-g",
"-Wno-reorder",
"-fopenmp",
"-march=native",
]
return ["-O3"] + self.version_dependent_macros + extra_cxx_flags
def nvcc_flags(self):
extra_cuda_flags = [
"-std=c++14",
"-std=c++17",
"-U__CUDA_NO_HALF_OPERATORS__",
"-U__CUDA_NO_HALF_CONVERSIONS__",
"-U__CUDA_NO_HALF2_OPERATORS__",
"-DTHRUST_IGNORE_CUB_VERSION_CHECK",
]
ret = ["-O3", "--use_fast_math"] + self.version_dependent_macros + extra_cuda_flags
return append_nvcc_threads(ret)