mirror of https://github.com/hpcaitech/ColossalAI
[builder] polish builder with better base class (#2216)
* [builder] polish builder * remove printpull/2226/head
parent
3b1b91eaf4
commit
54de05da5d
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@ -30,13 +30,31 @@ class Builder(object):
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else:
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else:
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return os.path.join(Path(__file__).parent.parent.absolute(), code_path)
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return os.path.join(Path(__file__).parent.parent.absolute(), code_path)
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def get_cuda_include(self):
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def get_cuda_home_include(self):
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"""
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return include path inside the cuda home.
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"""
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from torch.utils.cpp_extension import CUDA_HOME
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from torch.utils.cpp_extension import CUDA_HOME
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if CUDA_HOME is None:
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if CUDA_HOME is None:
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raise RuntimeError("CUDA_HOME is None, please set CUDA_HOME to compile C++/CUDA kernels in ColossalAI.")
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raise RuntimeError("CUDA_HOME is None, please set CUDA_HOME to compile C++/CUDA kernels in ColossalAI.")
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cuda_include = os.path.join(CUDA_HOME, "include")
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cuda_include = os.path.join(CUDA_HOME, "include")
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return cuda_include
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return cuda_include
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# functions must be overrided begin
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def sources_files(self):
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raise NotImplementedError
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def include_dirs(self):
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raise NotImplementedError
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def cxx_flags(self):
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raise NotImplementedError
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def nvcc_flags(self):
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raise NotImplementedError
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# functions must be overrided over
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def strip_empty_entries(self, args):
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def strip_empty_entries(self, args):
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'''
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'''
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Drop any empty strings from the list of compile and link flags
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Drop any empty strings from the list of compile and link flags
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@ -57,10 +75,10 @@ class Builder(object):
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start_build = time.time()
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start_build = time.time()
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op_module = load(name=self.name,
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op_module = load(name=self.name,
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sources=self.strip_empty_entries(self.sources),
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sources=self.strip_empty_entries(self.sources_files()),
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extra_include_paths=self.strip_empty_entries(self.extra_include_paths),
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extra_include_paths=self.strip_empty_entries(self.include_dirs()),
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extra_cflags=self.extra_cxx_flags,
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extra_cflags=self.cxx_flags(),
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extra_cuda_cflags=self.extra_cuda_flags,
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extra_cuda_cflags=self.nvcc_flags(),
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extra_ldflags=[],
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extra_ldflags=[],
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verbose=verbose)
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verbose=verbose)
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@ -69,3 +87,18 @@ class Builder(object):
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print(f"Time to load {self.name} op: {build_duration} seconds")
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print(f"Time to load {self.name} op: {build_duration} seconds")
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return op_module
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return op_module
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def builder(self, name) -> 'CUDAExtension':
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"""
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get a CUDAExtension instance used for setup.py
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"""
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from torch.utils.cpp_extension import CUDAExtension
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return CUDAExtension(
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name=name,
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sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in self.sources_files()],
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include_dirs=self.include_dirs(),
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extra_compile_args={
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'cxx': self.cxx_flags(),
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'nvcc': self.nvcc_flags()
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})
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@ -12,68 +12,31 @@ class CPUAdamBuilder(Builder):
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self.name = CPUAdamBuilder.NAME
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self.name = CPUAdamBuilder.NAME
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super().__init__()
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super().__init__()
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self.sources = [self.colossalai_src_path(path) for path in self.sources_files()]
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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self.extra_include_paths = [self.colossalai_src_path(path) for path in self.include_paths()]
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self.extra_cxx_flags = ['-std=c++14', '-lcudart', '-lcublas', '-g', '-Wno-reorder', '-fopenmp', '-march=native']
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# necessary 4 functions
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self.extra_cuda_flags = [
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def sources_files(self):
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ret = [
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os.path.join(CPUAdamBuilder.BASE_DIR, "csrc/cpu_adam.cpp"),
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]
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return [self.colossalai_src_path(path) for path in ret]
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def include_dirs(self):
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return [
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self.colossalai_src_path(os.path.join(CPUAdamBuilder.BASE_DIR, "includes")),
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self.get_cuda_home_include()
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]
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def cxx_flags(self):
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extra_cxx_flags = ['-std=c++14', '-lcudart', '-lcublas', '-g', '-Wno-reorder', '-fopenmp', '-march=native']
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return ['-O3'] + self.version_dependent_macros + extra_cxx_flags
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def nvcc_flags(self):
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extra_cuda_flags = [
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'-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__',
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'-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__',
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'-U__CUDA_NO_HALF2_OPERATORS__', '-DTHRUST_IGNORE_CUB_VERSION_CHECK'
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'-U__CUDA_NO_HALF2_OPERATORS__', '-DTHRUST_IGNORE_CUB_VERSION_CHECK'
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]
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]
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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def sources_files(self):
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return append_nvcc_threads(['-O3', '--use_fast_math'] + self.version_dependent_macros + extra_cuda_flags)
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return [
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os.path.join(CPUAdamBuilder.BASE_DIR, "csrc/cpu_adam.cpp"),
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]
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def include_paths(self):
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# necessary 4 functions
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return [os.path.join(CPUAdamBuilder.BASE_DIR, "includes"), self.get_cuda_include()]
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def strip_empty_entries(self, args):
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'''
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Drop any empty strings from the list of compile and link flags
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'''
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return [x for x in args if len(x) > 0]
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def builder(self, name) -> 'CUDAExtension':
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"""
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get a CUDAExtension instance used for setup.py
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"""
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from torch.utils.cpp_extension import CUDAExtension
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return CUDAExtension(
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name=name,
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sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in self.sources],
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include_dirs=self.extra_include_paths,
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extra_compile_args={
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'cxx': ['-O3'] + self.version_dependent_macros + self.extra_cxx_flags,
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'nvcc':
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append_nvcc_threads(['-O3', '--use_fast_math'] + self.version_dependent_macros +
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self.extra_cuda_flags)
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})
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def load(self, verbose=True):
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"""
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load and compile cpu_adam lib at runtime
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Args:
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verbose (bool, optional): show detailed info. Defaults to True.
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"""
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import time
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from torch.utils.cpp_extension import load
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start_build = time.time()
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op_module = load(name=self.name,
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sources=self.strip_empty_entries(self.sources),
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extra_include_paths=self.strip_empty_entries(self.extra_include_paths),
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extra_cflags=self.extra_cxx_flags,
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extra_cuda_cflags=self.extra_cuda_flags,
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extra_ldflags=[],
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verbose=verbose)
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build_duration = time.time() - start_build
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if verbose:
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print(f"Time to load {self.name} op: {build_duration} seconds")
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return op_module
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@ -1,7 +1,4 @@
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import os
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import os
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import re
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import torch
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from .builder import Builder, get_cuda_cc_flag
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from .builder import Builder, get_cuda_cc_flag
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@ -13,33 +10,26 @@ class FusedOptimBuilder(Builder):
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def __init__(self):
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def __init__(self):
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self.name = FusedOptimBuilder.NAME
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self.name = FusedOptimBuilder.NAME
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super().__init__()
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super().__init__()
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self.extra_cxx_flags = []
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self.extra_cuda_flags = ['-lineinfo']
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self.extra_cuda_flags.extend(get_cuda_cc_flag())
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self.sources = [self.colossalai_src_path(path) for path in self.sources_files()]
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self.extra_include_paths = [self.colossalai_src_path(path) for path in self.include_paths()]
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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def sources_files(self):
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def sources_files(self):
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return [
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ret = [
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os.path.join(FusedOptimBuilder.BASE_DIR, fname) for fname in [
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self.colossalai_src_path(os.path.join(FusedOptimBuilder.BASE_DIR, fname)) for fname in [
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'colossal_C_frontend.cpp', 'multi_tensor_sgd_kernel.cu', 'multi_tensor_scale_kernel.cu',
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'colossal_C_frontend.cpp', 'multi_tensor_sgd_kernel.cu', 'multi_tensor_scale_kernel.cu',
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'multi_tensor_adam.cu', 'multi_tensor_l2norm_kernel.cu', 'multi_tensor_lamb.cu'
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'multi_tensor_adam.cu', 'multi_tensor_l2norm_kernel.cu', 'multi_tensor_lamb.cu'
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]
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]
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]
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]
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return ret
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def include_paths(self):
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def include_dirs(self):
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return [os.path.join(FusedOptimBuilder.BASE_DIR, "includes"), self.get_cuda_include()]
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ret = [os.path.join(FusedOptimBuilder.BASE_DIR, "includes"), self.get_cuda_home_include()]
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return [self.colossalai_src_path(path) for path in ret]
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def builder(self, name):
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def cxx_flags(self):
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from torch.utils.cpp_extension import CUDAExtension
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extra_cxx_flags = []
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return CUDAExtension(
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return ['-O3'] + self.version_dependent_macros + extra_cxx_flags
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name=name,
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sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in self.sources],
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def nvcc_flags(self):
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include_dirs=self.extra_include_paths,
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extra_cuda_flags = ['-lineinfo']
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extra_compile_args={
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extra_cuda_flags.extend(get_cuda_cc_flag())
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'cxx': ['-O3'] + self.version_dependent_macros + self.extra_cxx_flags,
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return ['-O3', '--use_fast_math'] + extra_cuda_flags
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'nvcc': ['-O3', '--use_fast_math'] + self.extra_cuda_flags
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})
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@ -9,41 +9,33 @@ class MultiHeadAttnBuilder(Builder):
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self.base_dir = "cuda_native/csrc"
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self.base_dir = "cuda_native/csrc"
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self.name = 'multihead_attention'
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self.name = 'multihead_attention'
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super().__init__()
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super().__init__()
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self.extra_cxx_flags = []
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self.extra_cuda_flags = [
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'-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__',
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'-U__CUDA_NO_HALF2_OPERATORS__', '-DTHRUST_IGNORE_CUB_VERSION_CHECK'
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]
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self.extra_cuda_flags.extend(get_cuda_cc_flag())
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self.sources = [self.colossalai_src_path(path) for path in self.sources_files()]
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self.extra_include_paths = [self.colossalai_src_path(path) for path in self.include_paths()]
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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self.version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
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def include_dirs(self):
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ret = []
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ret = [os.path.join(self.base_dir, "includes"), self.get_cuda_home_include()]
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ret.append(os.path.join(self.base_dir, "kernels", "include"))
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return [self.colossalai_src_path(path) for path in ret]
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def sources_files(self):
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def sources_files(self):
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return [
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ret = [
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os.path.join(self.base_dir, fname) for fname in [
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os.path.join(self.base_dir, fname) for fname in [
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'multihead_attention_1d.cpp', 'kernels/cublas_wrappers.cu', 'kernels/transform_kernels.cu',
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'multihead_attention_1d.cpp', 'kernels/cublas_wrappers.cu', 'kernels/transform_kernels.cu',
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'kernels/dropout_kernels.cu', 'kernels/normalize_kernels.cu', 'kernels/softmax_kernels.cu',
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'kernels/dropout_kernels.cu', 'kernels/normalize_kernels.cu', 'kernels/softmax_kernels.cu',
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'kernels/general_kernels.cu', 'kernels/cuda_util.cu'
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'kernels/general_kernels.cu', 'kernels/cuda_util.cu'
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]
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]
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]
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]
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return [self.colossalai_src_path(path) for path in ret]
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def include_paths(self):
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def cxx_flags(self):
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ret = []
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return ['-O3'] + self.version_dependent_macros
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ret = [os.path.join(self.base_dir, "includes"), self.get_cuda_include()]
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ret.append(os.path.join(self.base_dir, "kernels", "include"))
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def nvcc_flags(self):
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print("include_paths", ret)
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extra_cuda_flags = [
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'-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__',
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'-U__CUDA_NO_HALF2_OPERATORS__', '-DTHRUST_IGNORE_CUB_VERSION_CHECK'
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]
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extra_cuda_flags.extend(get_cuda_cc_flag())
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ret = ['-O3', '--use_fast_math'] + extra_cuda_flags
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return ret
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return ret
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def builder(self, name):
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from torch.utils.cpp_extension import CUDAExtension
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return CUDAExtension(
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name=name,
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sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in self.sources],
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include_dirs=self.extra_include_paths,
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extra_compile_args={
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'cxx': ['-O3'] + self.version_dependent_macros,
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'nvcc': ['-O3', '--use_fast_math'] + self.extra_cuda_flags
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})
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