--------------------------------------------------------------------------- RuntimeError Traceback (most recent call last) Cell In[24], line 298 295 else: 296 download_weights(backbone) --> 298 model = PSPNet(num_classes=num_classes, backbone=backbone, downsample_factor=downsample_factor, pretrained=pretrained, pretrained_model_path=pretrained_model_path, aux_branch=aux_branch) 299 if not pretrained: 300 weights_init(model) Cell In[5], line 145, in PSPNet.__init__(self, num_classes, downsample_factor, backbone, pretrained, pretrained_model_path, aux_branch) 143 norm_layer = nn.BatchNorm2d 144 if backbone=="resnet50": --> 145 self.backbone = Resnet(downsample_factor, pretrained, pretrained_model_path) 146 aux_channel = 1024 147 out_channel = 2048 Cell In[5], line 13, in Resnet.__init__(self, dilate_scale, pretrained, pretrained_model_path) 11 super(Resnet, self).__init__() 12 from functools import partial ---> 13 model = resnet50(pretrained, pretrained_model_path) 15 #--------------------------------------------------------------------------------------------# 16 # 根据下采样因子修改卷积的步长与膨胀系数 17 # 当downsample_factor=16的时候，我们最终获得两个特征层，shape分别是：30,30,1024和30,30,2048 18 #--------------------------------------------------------------------------------------------# 19 if dilate_scale == 8: Cell In[4], line 173, in resnet50(pretrained, pretrained_model_path, **kwargs) 170 state_dict = torch.load(pretrained_model_path, map_location=device) 171 # Load the state dictionary into the model 172 # 将加载的参数字典加载到模型中 --> 173 model.load_state_dict(state_dict, strict=False) 174 # 打印加载成功的信息 175 print("Model weights have been loaded.") File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py:2041, in Module.load_state_dict(self, state_dict, strict) 2036 error_msgs.insert( 2037 0, 'Missing key(s) in state_dict: {}. '.format( 2038 ', '.join('"{}"'.format(k) for k in missing_keys))) 2040 if len(error_msgs) > 0: -> 2041 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( 2042 self.__class__.__name__, "\n\t".join(error_msgs))) 2043 return _IncompatibleKeys(missing_keys, unexpected_keys) RuntimeError: Error(s) in loading state_dict for ResNet: size mismatch for bn1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for bn1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for bn1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for bn1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for layer1.0.conv1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]). size mismatch for layer1.0.downsample.0.weight: copying a param with shape torch.Size([256, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 128, 1, 1]).这个警告是哪里出错了