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https://github.com/zebrajr/pytorch.git
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130d55a5f4
Summary: I am working on unifying the C++ extensions and C++ API, and one constraint for this is that we will want to be able to build the C++ API without cereal, since we won't want to ship it with the Python `torch` package. For this I introduce a `TORCH_WITH_CEREAL` option to CMake. If on, the C++ API will be built with cereal and thus serialization support. If off, serialization functions will throw exceptions, but the library will otherwise still compile the same. __This option is on by default, so for regular C++ API users nothing will change__. However, from C++ extensions, we'll be able to turn it off. This effectively means we won't be searching for any cereal headers from C++ API headers, which wouldn't be installed in the Python package. ebetica ezyang soumith Pull Request resolved: https://github.com/pytorch/pytorch/pull/11498 Differential Revision: D9784803 Pulled By: goldsborough fbshipit-source-id: 5d0a1f2501993012d28cf3d730f45932b483abc4
33 lines
985 B
Python
33 lines
985 B
Python
import argparse
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import os
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import shlex
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import subprocess
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import sys
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from setup_helpers.cuda import USE_CUDA
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if __name__ == '__main__':
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# Placeholder for future interface. For now just gives a nice -h.
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parser = argparse.ArgumentParser(description='Build libtorch')
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parser.add_argument('--use-cereal', action='store_true')
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options = parser.parse_args()
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os.environ['BUILD_TORCH'] = 'ON'
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os.environ['BUILD_TEST'] = 'ON'
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os.environ['ONNX_NAMESPACE'] = 'onnx_torch'
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os.environ['PYTORCH_PYTHON'] = sys.executable
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tools_path = os.path.dirname(os.path.abspath(__file__))
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build_pytorch_libs = os.path.join(tools_path, 'build_pytorch_libs.sh')
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command = [build_pytorch_libs, '--use-nnpack']
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if USE_CUDA:
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command.append('--use-cuda')
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if options.use_cereal:
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command.append('--use-cereal')
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command.append('caffe2')
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sys.stdout.flush()
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sys.stderr.flush()
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subprocess.check_call(command, universal_newlines=True)
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