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618c6214aa
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35254 Reapply D20541090 with some BC fixes ghstack-source-id: 100733987 Test Plan: buck test mode/dev-nosan //caffe2/torch/fb/predictor/model_repo/tests:ai_infra_representative_model_shard_6_test -- 'RepresentativeModelTest\/ShardedRepresentativeModelTest\.RunModel\/0' Reviewed By: zdevito Differential Revision: D20607111 fbshipit-source-id: 80f148d860571208c93e9308128cd480ff089f74
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
import types
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import torch._C
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class _ClassNamespace(types.ModuleType):
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def __init__(self, name):
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super(_ClassNamespace, self).__init__('torch.classes' + name)
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self.name = name
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def __getattr__(self, attr):
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proxy = torch._C._get_custom_class_python_wrapper(self.name, attr)
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if proxy is None:
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raise RuntimeError('Class {}.{} not registered!'.format(self.name, attr))
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return proxy
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class _Classes(types.ModuleType):
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def __init__(self):
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super(_Classes, self).__init__('torch.classes')
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def __getattr__(self, name):
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namespace = _ClassNamespace(name)
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setattr(self, name, namespace)
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return namespace
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@property
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def loaded_libraries(self):
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return torch.ops.loaded_libraries
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def load_library(self, path):
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"""
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Loads a shared library from the given path into the current process.
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The library being loaded may run global initialization code to register
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custom classes with the PyTorch JIT runtime. This allows dynamically
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loading custom classes. For this, you should compile your class
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and the static registration code into a shared library object, and then
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call ``torch.classes.load_library('path/to/libcustom.so')`` to load the
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shared object.
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After the library is loaded, it is added to the
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``torch.classes.loaded_libraries`` attribute, a set that may be inspected
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for the paths of all libraries loaded using this function.
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Arguments:
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path (str): A path to a shared library to load.
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"""
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torch.ops.load_library(path)
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# The classes "namespace"
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classes = _Classes()
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