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。
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