pytorch載入自定義網路權重
阿新 • • 發佈:2019-02-04
在將自定義的網路權重載入到網路中時,報錯:
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.
我們一步一步分析。
模型網路權重儲存額程式碼是:torch.save(net.state_dict(),'net.pkl')
(1)檢視獲取模型權重的原始碼:
pytorch原始碼: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'] """
將網路中所有的狀態儲存到一個字典中了,我自己構建的就是一個字典,沒問題!
(2)檢視儲存模型權重的原始碼:
pytorch原始碼: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.
函式功能是將字典儲存為磁碟檔案(二進位制資料),那麼我們在torch.load()時,就是在記憶體中載入二進位制資料,這就是報錯點。
解決方案:將字典儲存為BytesIO檔案之後,模型再net.load_state_dict()
#b為自定義的字典 torch.save(b,'new.pkl') net.load_state_dict(torch.load(b))
解決方法很簡單,主要記錄解決思路。