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__deepcopy__ for DualGraphModule #8708

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__deepcopy__ for DualGraphModule #8708

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616e025
Update feature_extraction.py
andreasfloros Nov 2, 2024
5bb4e4d
Merge branch 'main' into dual-graph-deepcopy
andreasfloros Nov 9, 2024
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30 changes: 29 additions & 1 deletion torchvision/models/feature_extraction.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import copy
import inspect
import math
import re
Expand All @@ -10,7 +11,7 @@
import torch
import torchvision
from torch import fx, nn
from torch.fx.graph_module import _copy_attr
from torch.fx.graph_module import _copy_attr, _USER_PRESERVED_ATTRIBUTES_KEY, _CodeOnlyModule


__all__ = ["create_feature_extractor", "get_graph_node_names"]
Expand Down Expand Up @@ -330,6 +331,33 @@ def train(self, mode=True):
self.graph = self.eval_graph
return super().train(mode=mode)

def _deepcopy_init(self):
return DualGraphModule.__init__

def __deepcopy__(self, memo):
res = type(self).__new__(type(self))
memo[id(self)] = res
fake_mod = _CodeOnlyModule(copy.deepcopy(self.__dict__, memo))
self._deepcopy_init()(res, fake_mod, fake_mod.__dict__["train_graph"], fake_mod.__dict__["eval_graph"])

# (borrowed from fx.GraphModule):
extra_preserved_attrs = [
"_state_dict_hooks",
"_load_state_dict_pre_hooks",
"_load_state_dict_post_hooks",
"_replace_hook",
"_create_node_hooks",
"_erase_node_hooks"
]
for attr in extra_preserved_attrs:
if attr in self.__dict__:
setattr(res, attr, copy.deepcopy(self.__dict__[attr], memo))
res.meta = copy.deepcopy(getattr(self, "meta", {}), memo)
if _USER_PRESERVED_ATTRIBUTES_KEY in res.meta:
for attr_name, attr in res.meta[_USER_PRESERVED_ATTRIBUTES_KEY].items():
setattr(res, attr_name, attr)
return res


def create_feature_extractor(
model: nn.Module,
Expand Down