# local shape should match the one in checkpoint error_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ' 'the shape in current model is {}.' .format(key, input_param.shape, param.shape)) continue if isinstance(input_param, Parameter): # backwards com...
=param.shape:# local shape should match the one in checkpointerror_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ''the shape in current model is {}.'.format(key,input_param.shape,param.shape))continueifisinstance(input_param,Parameter):# backwards compa...
RuntimeError: Error(s) in loading state_dict for DataParallel: size mismatch for module.fish.fish.9.4.1.weight: copying a param with shape torch.Size([1056]) from checkpoint, the shape in current model is torch.Size([1000, 1056, 1, 1]). ...
= param.shape: # local shape should match the one in checkpoint error_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ' 'the shape in current model is {}.' .format(key, input_param.shape, param.shape)) continue if isinstance(input_param, Parameter)...
model.state_dict()其实返回的是一个OrderDict,存储了网络结构的名字和对应的参数,下面看看源代码如何实现的。 state_dict 代码语言:javascript 复制 # torch.nn.modules.module.pyclassModule(object):defstate_dict(self,destination=None,prefix='',keep_vars=False):ifdestination is None:destination=OrderedDict(...
# RuntimeError is raised by PyTorch if there is a size mismatch between modules # of the same name. This will still partially assign values to those layers that # have not changed shape. except (KeyError, ValueError, RuntimeError) as err: logger.warning(f"Failed to load for module {name...
error_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ' 'the shape in current model is {}.' .format(key, input_param.shape, param.shape)) continue if isinstance(input_param, Parameter): # backwards compatibility for serialized parameters ...
error_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ' 'the shape in current model is {}.' .format(key, input_param.shape, param.shape)) continue if isinstance(input_param, Parameter): # backwards compatibility for serialized parameters ...
= param.shape: # local shape should match the one in checkpoint error_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ' 'the shape in current model is {}.' .format(key, input_param.shape, param.shape)) continue if isinstance(input_param, Parameter)...
=param.shape:# local shape should match the one in checkpointerror_msgs.append('size mismatch for {}: copying a param with shape {} from checkpoint, ''the shape in current model is {}.'.format(key,input_param.shape,param.shape))continueifisinstance(input_param,Parameter):# backwards compa...