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()
def state_dict(self, destination=None, prefix='', keep_vars=False):
r"""Returns a dictionary containing a whole state of the module.
Both parameters and persistent buffers (e.g. running averages) are
included. Keys are corresponding parameter and buffer names.
Returns:
dict:
a dictionary containing a whole state of the module
Example::
>>> module.state_dict().keys()
['bias', 'weight']
"""
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()
def save(obj, f, pickle_module=pickle, pickle_protocol=DEFAULT_PROTOCOL):
"""Saves an object to a disk file.
See also: :ref:`recommend-saving-models`
Args:
obj: saved object
f: a file-like object (has to implement write and flush) or a string
containing a file name
pickle_module: module used for pickling metadata and objects
pickle_protocol: can be specified to override the default protocol
.. warning::
If you are using Python 2, torch.save does NOT support StringIO.StringIO
as a valid file-like object. This is because the write method should return
the number of bytes written; StringIO.write() does not do this.
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()
#b为自定义的字典 torch.save(b,'new.pkl') 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【听图阁-专注于Python设计】。