code/pretrained_model.py [19:30]:
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    model = models.resnet18()

    #traffic sign dataset has 43 classes   
    nfeatures = model.fc.in_features
    model.fc = nn.Linear(nfeatures, 43)

    #load model
    weights = torch.load(f'{model_dir}/model/model.pt', map_location=lambda storage, loc: storage)
    model.load_state_dict(weights)

    model.eval()
    model.cpu()
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code/pretrained_model_with_debugger_hook.py [37:48]:
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    model = models.resnet18()

    #traffic sign dataset has 43 classes   
    nfeatures = model.fc.in_features
    model.fc = nn.Linear(nfeatures, 43)

    #load model
    weights = torch.load(f'{model_dir}/model/model.pt', map_location=lambda storage, loc: storage)
    model.load_state_dict(weights)

    model.eval()
    model.cpu()
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