Using Unet
/content/LTUDA/code/test.py:44: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
net.load_state_dict(torch.load(args.reload_path))
Traceback (most recent call last):
File "/content/LTUDA/code/test.py", line 191, in
test()
File "/content/LTUDA/code/test.py", line 75, in test
outputs = net(data_bat, linear_classifier=False, ulp_classifier=True)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, *kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl
return forward_call(args, **kwargs)
TypeError: unet_proto.forward() got an unexpected keyword argument 'linear_classifier'
weng-hb
commented
3 hours ago
Using Unet /content/LTUDA/code/test.py:44: FutureWarning: You are using
test()
File "/content/LTUDA/code/test.py", line 75, in test
outputs = net(data_bat, linear_classifier=False, ulp_classifier=True)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, *kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl
return forward_call(args, **kwargs)
TypeError: unet_proto.forward() got an unexpected keyword argument 'linear_classifier'
torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user viatorch.serialization.add_safe_globals. We recommend you start settingweights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. net.load_state_dict(torch.load(args.reload_path)) Traceback (most recent call last): File "/content/LTUDA/code/test.py", line 191, in