Record the little trick when defining the model loading --state_dict or the strict function of torch.nn.Module.load_state_dict() - Code World

Record the little trick when defining the model loading --state_dict or the strict function of torch.nn.Module.load_state_dict()

Enterprise 2023-12-17 12:41:33 views: null

NoSuchKey

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Origin blog.csdn.net/qq_40962125/article/details/134639968

Record the little trick when defining the model loading --state_dict or the strict function of torch.nn.Module.load_state_dict()

When PyTorch loads the model, an error occurs: RuntimeError: Error(s) in loading state_dict for *****: Missing key(s) in state_dict:

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

PyTorch loading model model.load_state_dict() problem, Unexpected key(s) in state_dict: "module.features.., Expected.

Error when using pytorch's parallel test network: RuntimeError: Error(s) in loading state_dict for DataParallel

Unexpected key(s) in state_dict: “model“

RuntimeError: Error(s) in loading state_dict for DataParallel:

Error(s) in loading state_dict for ResNet problem solving

解决RuntimeError: Error(s) in loading state_dict for ResNet: Missing key(s) in state_dict: “conv1.0...

Run test error: RuntimeError: Error (s) in loading state_dict for F3Net: Missing key (s) in state_dict :( has solutions)

Raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError

【解决报错】RuntimeError: Error(s) in loading state_dict for Net:size mismatch for classifier.

Unexpected key(s) in state_dict solution

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

Loading model appears in load_state_dict raise RuntimeError('Error(s) in loading state_dict

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torch.save(model.state_dict(), ‘best_model.pth‘)

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