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* Use restat to reduce ninja rebuilding when running codegen. Usually, you're only working on one codegen file at a time, but in our old behavior, editing one would induce a rebuild of everything that depended on ANY generated file. We fix this in two steps: - Don't write the file (updating the timestamp) when the contents are unchanged. (I had to update three seperate places; shared Python library for build tools when?!) - Use the 'restat' ninja feature to avoid rebuilding when the timestamp doesn't change. Signed-off-by: Edward Z. Yang <ezyang@fb.com> * lintfix Signed-off-by: Edward Z. Yang <ezyang@fb.com> * lintfix2 Signed-off-by: Edward Z. Yang <ezyang@fb.com>
109 lines
4.1 KiB
Python
109 lines
4.1 KiB
Python
import os
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import sys
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import glob
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source_files = set(['.py', '.cpp', '.h'])
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# TODO: This is a little inaccurate, because it will also pick
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# up setup_helper scripts which don't affect code generation
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def all_generator_source():
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r = []
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for directory, _, filenames in os.walk('tools'):
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for f in filenames:
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if os.path.splitext(f)[1] in source_files:
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full = os.path.join(directory, f)
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r.append(full)
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return sorted(r)
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inputs = [
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'torch/csrc/generic/TensorMethods.cwrap',
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'torch/lib/tmp_install/share/ATen/Declarations.yaml',
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'tools/autograd/derivatives.yaml',
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] + glob.glob('torch/csrc/generic/methods/*.cwrap')
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outputs = [
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'torch/csrc/autograd/generated/Functions.cpp',
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'torch/csrc/autograd/generated/Functions.h',
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'torch/csrc/autograd/generated/python_functions.cpp',
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'torch/csrc/autograd/generated/python_functions.h',
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'torch/csrc/autograd/generated/python_nn_functions.cpp',
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'torch/csrc/autograd/generated/python_nn_functions.h',
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'torch/csrc/autograd/generated/python_nn_functions_dispatch.h',
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'torch/csrc/autograd/generated/python_variable_methods.cpp',
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'torch/csrc/autograd/generated/python_variable_methods_dispatch.h',
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'torch/csrc/autograd/generated/VariableType.cpp',
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'torch/csrc/autograd/generated/VariableType.h',
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'torch/csrc/jit/generated/aten_dispatch.cpp',
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'torch/csrc/jit/generated/aten_dispatch.h',
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]
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def generate_code_ninja(w):
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all_inputs = all_generator_source() + inputs
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cmd = "{} {}".format(sys.executable, 'tools/setup_helpers/generate_code.py')
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w.writer.build(
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outputs, 'do_cmd', all_inputs,
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variables={
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'cmd': cmd,
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# Note [Unchanging results for ninja]
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# generate_code.py will avoid bumping the timestamp on its
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# output files if the contents of the generated file did not
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# change. To let Ninja take advantage of this, it must stat
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# the output files after the build. See
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# https://groups.google.com/forum/#!topic/ninja-build/rExDmgDL2oc
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# for a more detailed discussion.
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'restat': True,
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})
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def generate_code(ninja_global=None):
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# if ninja is enabled, we just register this file as something
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# ninja will need to call if needed
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if ninja_global is not None:
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return generate_code_ninja(ninja_global)
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# cwrap depends on pyyaml, so we can't import it earlier
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root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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sys.path.insert(0, root)
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from tools.cwrap import cwrap
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from tools.cwrap.plugins.THPPlugin import THPPlugin
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from tools.cwrap.plugins.ArgcountSortPlugin import ArgcountSortPlugin
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from tools.cwrap.plugins.AutoGPU import AutoGPU
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from tools.cwrap.plugins.BoolOption import BoolOption
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from tools.cwrap.plugins.KwargsPlugin import KwargsPlugin
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from tools.cwrap.plugins.NullableArguments import NullableArguments
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from tools.cwrap.plugins.WrapDim import WrapDim
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from tools.cwrap.plugins.AssertNDim import AssertNDim
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from tools.cwrap.plugins.Broadcast import Broadcast
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from tools.cwrap.plugins.ProcessorSpecificPlugin import ProcessorSpecificPlugin
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from tools.autograd.gen_autograd import gen_autograd
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from tools.jit.gen_jit_dispatch import gen_jit_dispatch
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thp_plugin = THPPlugin()
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cwrap('torch/csrc/generic/TensorMethods.cwrap', plugins=[
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ProcessorSpecificPlugin(), BoolOption(), thp_plugin,
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AutoGPU(condition='IS_CUDA'), ArgcountSortPlugin(), KwargsPlugin(),
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AssertNDim(), WrapDim(), Broadcast()
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])
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# Build ATen based Variable classes
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autograd_gen_dir = 'torch/csrc/autograd/generated'
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jit_gen_dir = 'torch/csrc/jit/generated'
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for d in (autograd_gen_dir, jit_gen_dir):
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if not os.path.exists(d):
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os.mkdir(d)
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gen_autograd(
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'torch/lib/tmp_install/share/ATen/Declarations.yaml',
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autograd_gen_dir)
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gen_jit_dispatch(
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'torch/lib/tmp_install/share/ATen/Declarations.yaml',
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jit_gen_dir)
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# called from ninja
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if __name__ == "__main__":
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generate_code(None)
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