error(s) in loading state_dict for dataparallel:
时间: 2023-06-05 15:48:06 浏览: 229
这个错误提示是在加载PyTorch模型时出现的,通常是由于使用了DataParallel并行训练模型,但在加载模型时没有正确地指定设备或GPU数量导致的。
解决方法通常是在加载模型时指定正确的设备或GPU数量,或者在训练模型时使用torch.nn.parallel.DistributedDataParallel代替DataParallel,以便更好地支持分布式训练。
相关问题
Error(s) in loading state_dict for DataParallel:
This error occurs when trying to load the state_dict of a model trained using DataParallel in PyTorch. The error message may contain more specific information about the issue, but generally it indicates that the state_dict cannot be loaded because it was saved using DataParallel and the current model is not using DataParallel.
To resolve this error, you can either modify your model to use DataParallel when loading the state_dict, or modify the state_dict to remove references to DataParallel.
To modify your model to use DataParallel when loading the state_dict, you can wrap your model in DataParallel before loading the state_dict, like so:
```
model = nn.DataParallel(model)
model.load_state_dict(state_dict)
```
If you want to modify the state_dict to remove references to DataParallel, you can use the following code:
```
state_dict = {k.replace('module.', ''): v for k, v in state_dict.items()}
model.load_state_dict(state_dict)
```
This code removes the 'module.' prefix from the keys in the state_dict, which is added automatically by DataParallel.
RuntimeError: Error(s) in loading state_dict for DataParallel:
这个错误通常是因为模型训练时使用了 `DataParallel` 来并行化模型,但是在加载模型时没有正确处理 `DataParallel` 的参数。你可以尝试以下两种方法来解决这个问题:
1. 使用单 GPU 训练模型,这样在加载时就不会出现 `DataParallel` 的问题。
2. 在加载模型之前先将 `DataParallel` 中的参数去掉,可以使用以下代码:
```python
state_dict = torch.load(PATH)
from collections import OrderedDict
new_state_dict = OrderedDict()
for k, v in state_dict.items():
name = k[7:] # remove `module.`
new_state_dict[name] = v
model.load_state_dict(new_state_dict)
```
这个代码会将原来带有 `module.` 前缀的参数名字去掉,然后加载到模型中。这样就可以解决 `DataParallel` 的问题了。