mirror of https://github.com/hpcaitech/ColossalAI
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52 lines
1.5 KiB
52 lines
1.5 KiB
import torch |
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from .builder import Builder |
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from .utils import append_nvcc_threads |
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class SmoothquantBuilder(Builder): |
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NAME = "cu_smoothquant" |
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PREBUILT_IMPORT_PATH = "colossalai._C.cu_smoothquant" |
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def __init__(self): |
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super().__init__(name=SmoothquantBuilder.NAME, prebuilt_import_path=SmoothquantBuilder.PREBUILT_IMPORT_PATH) |
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def include_dirs(self): |
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ret = [self.csrc_abs_path("smoothquant"), self.get_cuda_home_include()] |
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return ret |
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def sources_files(self): |
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ret = [ |
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self.csrc_abs_path(fname) |
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for fname in [ |
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"smoothquant/binding.cpp", |
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"smoothquant/linear.cu", |
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] |
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] |
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return ret |
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def cxx_flags(self): |
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return ["-O3"] + self.version_dependent_macros |
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def nvcc_flags(self): |
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compute_capability = torch.cuda.get_device_capability() |
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cuda_arch = compute_capability[0] * 100 + compute_capability[1] * 10 |
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extra_cuda_flags = [ |
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"-v", |
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f"-DCUDA_ARCH={cuda_arch}", |
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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_HALF2_OPERATORS__", |
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"-DTHRUST_IGNORE_CUB_VERSION_CHECK", |
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] |
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ret = ["-O3", "--use_fast_math"] + self.version_dependent_macros + extra_cuda_flags |
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return append_nvcc_threads(ret) |
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def builder(self): |
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try: |
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super().builder() |
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except: |
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warnings.warn("build smoothquant lib not successful")
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