strict=False True 时,代表有什么要什me,每一个键都有。 False 时,有什么我要什么,没有的不勉强。 missing_keys, unexpected_keys 返回值:缺失的键,不期望的键。
( state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) for name, child in module._modules.items(): if child is not None: load(child, prefix + name + '.') load(self) if strict: error_msg = '' if len(unexpected_keys) > 0: error_msgs.insert( ...
_load_from_state_dict def_load_from_state_dict(self,state_dict,prefix,local_metadata,strict,missing_keys,unexpected_keys,error_msgs):forhookinself._load_state_dict_pre_hooks.values():hook(state_dict,prefix,local_metadata,strict,missing_keys,unexpected_keys,error_msgs)local_name_params=itertools....
{})module._load_from_state_dict(state_dict,prefix,local_metadata,strict,missing_keys,unexpected_keys,error_msgs)forname,childinmodule._modules.items():ifchild is not None:load(child,prefix+name+'.')load(self)ifstrict:error_msg=''iflen(unexpected_keys)>0:error_msgs.insert(0,'Unexpected...
strict(bool,optional) – whether to strictly enforce that the keys instate_dictmatch the keys returned by this module’sstate_dict()function. Default:True Returns missing_keysis a list of str containing the missing keys unexpected_keysis a list of str containing the unexpected keys ...
param)，完成参数拷贝。在if strict部分中，主要判断参数拷贝过程中是否有unexpected_keys或missing_keys，如有，则抛出错误，终止执行。当然，当strict=False时，会忽略这些细节。总结而言，state_dict和load_state_dict是Pytorch中用于保存和加载模型参数的关键函数，它们通过递归方式确保模型参数的准确恢复。
strict(bool, optional) – whether to strictly enforce that the keys instate_dictmatch the keys returned by this module’sstate_dict()function. Default:True Returns missing_keysis a list of str containing the missing keys unexpected_keysis a list of str containing the unexpected keys ...
Afterwards, when I tried to evaluate the performance using the trained model "qat.pth" by loading it with load_state_dict, I encountered an error stating that the keys do not match. Looking at the error, the key names have slightly changed (some . have become _, etc.), and the existe...
if len(missing_keys) > 0: logger.warning( f"The following keys:{missing_keys} are not found in checkpoint path: {path}." @@ -533,14 +551,13 @@ def load_state_dict( else: cur_chunk_tensor = paddle.zeros( item.lengths, dtype=flat_state_dict[ item.local_tensor_index.tensor_key ...
(missing_keys, unexpected_keys)RuntimeError: Error(s)inloading state_dictforUNetGenerator:Unexpected key(s)instate_dict:"down2.1.weight","down2.1.bias","down2.1.running_mean","down2.1.running_var","down2.1.num_batches_tracked","down3.1.weight","down3.1.bias","down3.1.running_mean","down...