pytorch加载自定义网络权重的实现

在将自定义的网络权重加载到网络中时，报错：

AttributeError: 'dict' object has no attribute 'seek'. You can only torch.load from a file that is seekable. Please pre-load the data into a buffer like io.BytesIO and try to load from it instead.

我们一步一步分析。

模型网络权重保存额代码是：torch.save(net.state_dict(),'net.pkl')

（1）查看获取模型权重的源码：

pytorch源码：net.state_dict()

1. def state_dict(self, destination=None, prefix='', keep_vars=False):
2. r"""Returns a dictionary containing a whole state of the module.
3.  
4. Both parameters and persistent buffers (e.g. running averages) are
5. included. Keys are corresponding parameter and buffer names.
6.  
7. Returns:
8. dict:
9. a dictionary containing a whole state of the module
10.  
11. Example::
12.  
13. >>> module.state_dict().keys()
14. ['bias', 'weight']
15.  
16. """

将网络中所有的状态保存到一个字典中了，我自己构建的就是一个字典，没问题！

（2）查看保存模型权重的源码:

pytorch源码：torch.save()

1. def save(obj, f, pickle_module=pickle, pickle_protocol=DEFAULT_PROTOCOL):
2. """Saves an object to a disk file.
3.  
4. See also: :ref:`recommend-saving-models`
5.  
6. Args:
7. obj: saved object
8. f: a file-like object (has to implement write and flush) or a string
9. containing a file name
10. pickle_module: module used for pickling metadata and objects
11. pickle_protocol: can be specified to override the default protocol
12.  
13. .. warning::
14. If you are using Python 2, torch.save does NOT support StringIO.StringIO
15. as a valid file-like object. This is because the write method should return
16. the number of bytes written; StringIO.write() does not do this.
17.  
18. Please use something like io.BytesIO instead.

函数功能是将字典保存为磁盘文件（二进制数据），那么我们在torch.load（）时，就是在内存中加载二进制数据，这就是报错点。

解决方案：将字典保存为BytesIO文件之后，模型再net.load_state_dict()

1. #b为自定义的字典
2. torch.save(b,'new.pkl')
3. net.load_state_dict(torch.load(b))

解决方法很简单，主要记录解决思路。

以上这篇pytorch加载自定义网络权重的实现就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持我们。