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[fx] GraphModule copy top level attributes from root #45182

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[fx] GraphModule copy top level attributes from root #45182

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[fx] GraphModule copy top level attributes from root
jerryzh168 Sep 23, 2020
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Update on "[fx] GraphModule copy top level attributes from root"
jerryzh168 Sep 23, 2020
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Update on "[fx] GraphModule copy top level attributes from root"
jerryzh168 Sep 23, 2020
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Update on "[fx] GraphModule copy top level attributes from root"
jerryzh168 Sep 24, 2020
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Update on "[fx] GraphModule copy top level attributes from root"
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jerryzh168 Sep 24, 2020
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8 changes: 8 additions & 0 deletions test/test_fx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -502,6 +502,14 @@ def forward(self, x):
traced = symbolic_trace(baz)
copied = copy.deepcopy(traced)

def test_deepcopy_preserve_attributes(self):
m = symbolic_trace(torch.nn.Conv2d(1, 1, 1))
m.attr = 3
self.assertTrue(hasattr(m, 'attr'))
m = copy.deepcopy(m)
self.assertTrue(hasattr(m, 'attr'))
self.assertTrue(hasattr(m, 'training'))

def test_unpack_list_better_error(self):
class SomeArgs(torch.nn.Module):
def forward(self, a, b):
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3 changes: 1 addition & 2 deletions torch/fx/graph_module.py
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Expand Up @@ -132,8 +132,7 @@ def __init__(self, root: Union[torch.nn.Module, Dict[str, Any]], graph: Graph):
"""
super().__init__()
if isinstance(root, torch.nn.Module):
if hasattr(root, 'training'):
self.training = root.training
self.__dict__ = root.__dict__
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for node in graph.nodes:
if node.op in ['get_attr', 'call_module']:
assert isinstance(node.target, str)
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