Making large AI models cheaper, faster and more accessible
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import os
from .builder import Builder
from .utils import append_nvcc_threads, get_cuda_cc_flag
class LayerNormBuilder(Builder):
NAME = "layernorm"
PREBUILT_IMPORT_PATH = "colossalai._C.layernorm"
def __init__(self):
super().__init__(name=LayerNormBuilder.NAME, prebuilt_import_path=LayerNormBuilder.PREBUILT_IMPORT_PATH)
def sources_files(self):
ret = [self.csrc_abs_path(fname) for fname in ['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu']]
return ret
def include_dirs(self):
ret = [self.csrc_abs_path('kernels/include'), self.get_cuda_home_include()]
return ret
def cxx_flags(self):
return ['-O3'] + self.version_dependent_macros
def nvcc_flags(self):
extra_cuda_flags = ['-maxrregcount=50']
extra_cuda_flags.extend(get_cuda_cc_flag())
ret = ['-O3', '--use_fast_math'] + extra_cuda_flags + self.version_dependent_macros
return append_nvcc_threads(ret)