Pytorch 加载预训练模型

pretrained_dict =...

model_dict = model.state_dict()

# 1. filter out unnecessary keys
pretrained_dict = {k: v for k, vin pretrained_dict.items() if k inmodel_dict}

# 2. overwrite entries in the existing state dict

model_dict.update(pretrained_dict)

# 3. load the new state dict

model.load_state_dict(model_dict)
例如：

myNet=resnet18()
pretrained_dict=torch.load(model_weight)
model_dict=myNet.state_dict()
# 1. filter out unnecessary keys
pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict}
# 2. overwrite entries in the existing state dict
model_dict.update(pretrained_dict)
myNet.load_state_dict(model_dict)

也可以用一句话搞定：myNet.load_state_dict(torch.load(model_weight),strict=False)

ref ： https://blog.csdn.net/LXX516/article/details/80124768

         https://blog.csdn.net/lscelory/article/details/81482586

        https://blog.csdn.net/strive_for_future/article/details/83240081

       https://www.cnblogs.com/wmlj/p/9917827.html