model.load_state_dict(checkpoint[‘state_dict‘]) KeyError: ‘state_dict‘ 原创 AI韬哥 2023-05-18 17:25:30 ©著作权 文章标签 系统 文章分类 Python 后端开发 修改args.py parser.add_argument('--resume', default=None, type=str, metavar='PATH', help='path to latest checkpoint') default...
However, here, I received a KeyError when loading the weights of the layer that got spectral_norm applied to it. This does not happen if I remove the spectral_norm or if I had common normalization modules such as nn.BatchNorm2d or nn.InstanceNorm2d. I may have missed something in the ...
上述代码只有在模型是在一块GPU上训练时才有效,如果模型在多个GPU上训练,那么在CPU上加载时,会得到类似如下错误: KeyError: ‘unexpected key “module.conv1.weight” in state_dict’ 原因是在使用多GPU训练并保存模型时,模型的参数名都带上了module前缀,因此可以在加载模型时,把key中的这个前缀去掉: # 原始通过...
上述代码只有在模型是在一块GPU上训练时才有效,如果模型在多个GPU上训练,那么在CPU上加载时,会得到类似如下错误: KeyError: ‘unexpected key “module.conv1.weight” in state_dict’ 原因是在使用多GPU训练并保存模型时,模型的参数名都带上了module前缀,因此可以在加载模型时,把key中的这个前缀去掉: # 原始通过...
KeyError: ‘unexpected key “module.conv1.weight” in state_dict’ 原因是在使用多GPU训练并保存模型时,模型的参数名都带上了module前缀,因此可以在加载模型时,把key中的这个前缀去掉: # 原始通过DataParallel保存的文件 state_dict = torch.load('myfile.pth.tar') ...
items(): if name not in ignored_keys: # changed here if name not in own_state: raise KeyError('unexpected key "{}" in state_dict' .format(name)) if isinstance(param, Parameter): # backwards compatibility for serialized parameters param = param.data own_state[name].copy_(param) # ...
model.load_state_dict(pretrained_state_dict)exceptKeyErrorase: print(f"NOTE: Currently model{e}doesn't have pretrained weights, therefore a model with randomly initialized"" weights is returned.")returnmodel 开发者ID:zhoudaxia233,项目名称:EfficientUnet-PyTorch,代码行数:21,代码来源:efficientnet.py ...
model.load_state_dict(checkpoint[‘state_dict‘]) KeyError: ‘state_dict‘ 修改args.py parser.add_argument('--resume', default=None, type=str, metavar='PATH', help='path to latest checkpoint')default=None 系统 原创 AI韬哥 2023-05-18 17:25:30 ...
After I fine-tuned a mobilenet model and save the parameters of the trained mobilenet model, I try to load a model with the parameters, but such error happened.
Hi, I encountered this bug: optimizer.step() exp_avg.mul_(beta1).add_(1 - beta1, grad) TypeError: add_ received an invalid combination of arguments - got (float, torch.cuda.FloatTensor), but expected one of: * (float value) * (torch.Floa...