mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
6edf340338
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38157 This removes the error prone process of assembling `torch/__init__.pyi` (and frequently forgetting to expose things), since now we can simply rely on the true source file to get things done. Most of the old codegen in gen_pyi.py is now rerouted to various files: - `torch/_C/__init__.pyi` (the dumping pile of all misc bindings) - `torch/_C/_nn.pyi` (NN function bindings) - `torch/_C/_VariableFunctions.pyi` (torch function bindings) `torch.types` grew a bunch more definitions that previously where defined in `torch/__init__.pyi` Some miscellaneous changes - Fixed a bug where we treat single TensorList argument as implying varargs are accepted. This is actually only supported on IntList. This means we can correctly generate a stub for dequantize. - Add missing manual stub for nonzero - Switched torch/onnx/operators.py to directly refer to _C module, since apparently mypy doesn't think that methods prefixed with underscores get reexported. This may be a recurring theme; maybe we need to find a better way to solve it. Because I was really lazy, I dumped namedtuple definitions in both `torch._C` and `torch._C._VariableFunctions`. This is definitely wrong. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Test Plan: Imported from OSS Differential Revision: D21497400 Pulled By: ezyang fbshipit-source-id: 07b126141c82efaca37be27c07255cb2b9b3f064
17 lines
336 B
Python
17 lines
336 B
Python
import torch
|
|
import sys
|
|
import types
|
|
|
|
|
|
class VFModule(types.ModuleType):
|
|
vf: types.ModuleType
|
|
|
|
def __init__(self, name):
|
|
super(VFModule, self).__init__(name)
|
|
self.vf = torch._C._VariableFunctions
|
|
|
|
def __getattr__(self, attr):
|
|
return getattr(self.vf, attr)
|
|
|
|
sys.modules[__name__] = VFModule(__name__)
|