When you save a PyTorch model’s state, you need to save the actual state dictionary, not a reference to the method that returns it.
In Python, model.state_dict without parentheses refers to the method object itself, while model.state_dict() with
parentheses calls the method and returns the state dictionary.
If you save the method reference, PyTorch will serialize a function object instead of the model’s parameters and buffers. When you later try to
load this saved file, PyTorch expects a dictionary but receives a function object, causing an AttributeError: 'function' object has no attribute
'copy'.
This error typically occurs during model loading when PyTorch tries to call .copy() on what it expects to be a state dictionary but is
actually a function object.
What is the potential impact?
This issue causes runtime errors when loading saved models, leading to:
- Application crashes during model loading
- Failed deployments in production environments
- Interrupted training workflows
- Loss of training progress if the error is discovered late
Code examples
Noncompliant code example
import torch
import torch.nn as nn
model = nn.Linear(10, 1)
# Saves method reference instead of state dictionary
torch.save(model.state_dict, 'model.pth') # Noncompliant
Compliant solution
import torch
import torch.nn as nn
model = nn.Linear(10, 1)
# Calls method to get and save the state dictionary
torch.save(model.state_dict(), 'model.pth')
Documentation
