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()
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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()
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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()
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#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服务器之家。
原文链接：https://blog.csdn.net/qq_34789262/article/details/83376374
