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Comments (2)

elisa-aleman avatar elisa-aleman commented on August 18, 2024

I figured out a fix:

@@ -139,7 +139,10 @@ def _prepare_module_dict(model: torch.nn.Module, fx_graph):
     for nose in fx_graph.nodes:
         if node.op == 'get_attr':
             attr = _get_attrs(model, node.target)
             if isinstance(attr, nn.Module):
                 module_dict[node.target] = nn.Module()
                 special_nodes.append(node)
+            else:
+                module_dict[node.target] = attr
+                special_nodes.append(node)

patching this makes the graph build correctly if a model has nn.Parameter modules.

from mmrazor.

elisa-aleman avatar elisa-aleman commented on August 18, 2024

The previous fix trains without error but I have had issues deploying. This might be a better fix:

@@ -139,7 +139,10 @@ def _prepare_module_dict(model: torch.nn.Module, fx_graph):
     for nose in fx_graph.nodes:
         if node.op == 'get_attr':
             attr = _get_attrs(model, node.target)
             if isinstance(attr, nn.Module):
                 module_dict[node.target] = nn.Module()
                 special_nodes.append(node)
+            elif isinstance(attr, nn.Parameter):
+                module_dict[node.target] = attr
+                special_nodes.append(node)

from mmrazor.

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