加载模型权重文件出错

[shallwing]

我在下载了yolov5_l.pth文件，然后将其放在model_data中，之后运行程序，程序报错说模型文件不匹配，这是怎么回事？

File "G:\Pycharm\SHALLWING\yolov5-pytorch\yolo.py", line 113, in generate self.net.load_state_dict(torch.load(self.model_path, map_location=device)) File "D:\Program Files\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 2041, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for YoloBody: Unexpected key(s) in state_dict: "backbone.dark2.1.m.1.cv1.conv.weight", "backbone.dark2.1.m.1.cv1.bn.weight", "backbone.dark2.1.m.1.cv1.bn.bias", "backbone.dark2.1.m.1.cv1.bn.running_mean", "backbone.dark2.1.m.1.cv1.bn.running_var", "backbone.dark2.1.m.1.cv1.bn.num_batches_tracked", "backbone.dark2.1.m.1.cv2.conv.weight", "backbone.dark2.1.m.1.cv2.bn.weight", "backbone.dark2.1.m.1.cv2.bn.bias", "backbone.dark2.1.m.1.cv2.bn.running_mean", "backbone.dark2.1.m.1.cv2.bn.running_var", "backbone.dark2.1.m.1.cv2.bn.num_batches_tracked", "backbone.dark2.1.m.2.cv1.conv.weight", "backbone.dark2.1.m.2.cv1.bn.weight", "backbone.dark2.1.m.2.cv1.bn.bias", "backbone.dark2.1.m.2.cv1.bn.running_mean", "backbone.dark2.1.m.2.cv1.bn.running_var", "backbone.dark2.1.m.2.cv1.bn.num_batches_tracked", "backbone.dark2.1.m.2.cv2.conv.weight", "backbone.dark2.1.m.2.cv2.bn.weight", "backbone.dark2.1.m.2.cv2.bn.bias", "backbone.dark2.1.m.2.cv2.bn.running_mean", "backbone.dark2.1.m.2.cv2.bn.running_var", "backbone.dark2.1.m.2.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.3.cv1.conv.weight", "backbone.dark3.1.m.3.cv1.bn.weight", "backbone.dark3.1.m.3.cv1.bn.bias", "backbone.dark3.1.m.3.cv1.bn.running_mean", "backbone.dark3.1.m.3.cv1.bn.running_var", "backbone.dark3.1.m.3.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.3.cv2.conv.weight", "backbone.dark3.1.m.3.cv2.bn.weight", "backbone.dark3.1.m.3.cv2.bn.bias", "backbone.dark3.1.m.3.cv2.bn.running_mean", "backbone.dark3.1.m.3.cv2.bn.running_var", "backbone.dark3.1.m.3.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.4.cv1.conv.weight", "backbone.dark3.1.m.4.cv1.bn.weight", "backbone.dark3.1.m.4.cv1.bn.bias", "backbone.dark3.1.m.4.cv1.bn.running_mean", "backbone.dark3.1.m.4.cv1.bn.running_var", "backbone.dark3.1.m.4.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.4.cv2.conv.weight", "backbone.dark3.1.m.4.cv2.bn.weight", "backbone.dark3.1.m.4.cv2.bn.bias", "backbone.dark3.1.m.4.cv2.bn.running_mean", "backbone.dark3.1.m.4.cv2.bn.running_var", "backbone.dark3.1.m.4.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.5.cv1.conv.weight", "backbone.dark3.1.m.5.cv1.bn.weight", "backbone.dark3.1.m.5.cv1.bn.bias", "backbone.dark3.1.m.5.cv1.bn.running_mean", "backbone.dark3.1.m.5.cv1.bn.running_var", "backbone.dark3.1.m.5.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.5.cv2.conv.weight", "backbone.dark3.1.m.5.cv2.bn.weight", "backbone.dark3.1.m.5.cv2.bn.bias", "backbone.dark3.1.m.5.cv2.bn.running_mean", "backbone.dark3.1.m.5.cv2.bn.running_var", "backbone.dark3.1.m.5.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.6.cv1.conv.weight", "backbone.dark3.1.m.6.cv1.bn.weight", "backbone.dark3.1.m.6.cv1.bn.bias", "backbone.dark3.1.m.6.cv1.bn.running_mean", "backbone.dark3.1.m.6.cv1.bn.running_var", "backbone.dark3.1.m.6.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.6.cv2.conv.weight", "backbone.dark3.1.m.6.cv2.bn.weight", "backbone.dark3.1.m.6.cv2.bn.bias", "backbone.dark3.1.m.6.cv2.bn.running_mean", "backbone.dark3.1.m.6.cv2.bn.running_var", "backbone.dark3.1.m.6.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.7.cv1.conv.weight", "backbone.dark3.1.m.7.cv1.bn.weight", "backbone.dark3.1.m.7.cv1.bn.bias", "backbone.dark3.1.m.7.cv1.bn.running_mean", "backbone.dark3.1.m.7.cv1.bn.running_var", "backbone.dark3.1.m.7.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.7.cv2.conv.weight", "backbone.dark3.1.m.7.cv2.bn.weight", "backbone.dark3.1.m.7.cv2.bn.bias", "backbone.dark3.1.m.7.cv2.bn.running_mean", "backbone.dark3.1.m.7.cv2.bn.running_var", "backbone.dark3.1.m.7.cv2.bn.num_batches_tracked", "backbone.dark3.1.m.8.cv1.conv.weight", "backbone.dark3.1.m.8.cv1.bn.weight", "backbone.dark3.1.m.8.cv1.bn.bias", "backbone.dark3.1.m.8.cv1.bn.running_mean", "backbone.dark3.1.m.8.cv1.bn.running_var", "backbone.dark3.1.m.8.cv1.bn.num_batches_tracked", "backbone.dark3.1.m.8.cv2.conv.weight", "backbone.dark3.1.m.8.cv2.bn.weight", "backbone.dark3.1.m.8.cv2.bn.bias", "backbone.dark3.1.m.8.cv2.bn.running_mean", "backbone.dark3.1.m.8.cv2.bn.running_var", "backbone.dark3.1.m.8.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.3.cv1.conv.weight", "backbone.dark4.1.m.3.cv1.bn.weight", "backbone.dark4.1.m.3.cv1.bn.bias", "backbone.dark4.1.m.3.cv1.bn.running_mean", "backbone.dark4.1.m.3.cv1.bn.running_var", "backbone.dark4.1.m.3.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.3.cv2.conv.weight", "backbone.dark4.1.m.3.cv2.bn.weight", "backbone.dark4.1.m.3.cv2.bn.bias", "backbone.dark4.1.m.3.cv2.bn.running_mean", "backbone.dark4.1.m.3.cv2.bn.running_var", "backbone.dark4.1.m.3.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.4.cv1.conv.weight", "backbone.dark4.1.m.4.cv1.bn.weight", "backbone.dark4.1.m.4.cv1.bn.bias", "backbone.dark4.1.m.4.cv1.bn.running_mean", "backbone.dark4.1.m.4.cv1.bn.running_var", "backbone.dark4.1.m.4.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.4.cv2.conv.weight", "backbone.dark4.1.m.4.cv2.bn.weight", "backbone.dark4.1.m.4.cv2.bn.bias", "backbone.dark4.1.m.4.cv2.bn.running_mean", "backbone.dark4.1.m.4.cv2.bn.running_var", "backbone.dark4.1.m.4.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.5.cv1.conv.weight", "backbone.dark4.1.m.5.cv1.bn.weight", "backbone.dark4.1.m.5.cv1.bn.bias", "backbone.dark4.1.m.5.cv1.bn.running_mean", "backbone.dark4.1.m.5.cv1.bn.running_var", "backbone.dark4.1.m.5.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.5.cv2.conv.weight", "backbone.dark4.1.m.5.cv2.bn.weight", "backbone.dark4.1.m.5.cv2.bn.bias", "backbone.dark4.1.m.5.cv2.bn.running_mean", "backbone.dark4.1.m.5.cv2.bn.running_var", "backbone.dark4.1.m.5.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.6.cv1.conv.weight", "backbone.dark4.1.m.6.cv1.bn.weight", "backbone.dark4.1.m.6.cv1.bn.bias", "backbone.dark4.1.m.6.cv1.bn.running_mean", "backbone.dark4.1.m.6.cv1.bn.running_var", "backbone.dark4.1.m.6.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.6.cv2.conv.weight", "backbone.dark4.1.m.6.cv2.bn.weight", "backbone.dark4.1.m.6.cv2.bn.bias", "backbone.dark4.1.m.6.cv2.bn.running_mean", "backbone.dark4.1.m.6.cv2.bn.running_var", "backbone.dark4.1.m.6.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.7.cv1.conv.weight", "backbone.dark4.1.m.7.cv1.bn.weight", "backbone.dark4.1.m.7.cv1.bn.bias", "backbone.dark4.1.m.7.cv1.bn.running_mean", "backbone.dark4.1.m.7.cv1.bn.running_var", "backbone.dark4.1.m.7.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.7.cv2.conv.weight", "backbone.dark4.1.m.7.cv2.bn.weight", "backbone.dark4.1.m.7.cv2.bn.bias", "backbone.dark4.1.m.7.cv2.bn.running_mean", "backbone.dark4.1.m.7.cv2.bn.running_var", "backbone.dark4.1.m.7.cv2.bn.num_batches_tracked", "backbone.dark4.1.m.8.cv1.conv.weight", "backbone.dark4.1.m.8.cv1.bn.weight", "backbone.dark4.1.m.8.cv1.bn.bias", "backbone.dark4.1.m.8.cv1.bn.running_mean", "backbone.dark4.1.m.8.cv1.bn.running_var", "backbone.dark4.1.m.8.cv1.bn.num_batches_tracked", "backbone.dark4.1.m.8.cv2.conv.weight", "backbone.dark4.1.m.8.cv2.bn.weight", "backbone.dark4.1.m.8.cv2.bn.bias", "backbone.dark4.1.m.8.cv2.bn.running_mean", "backbone.dark4.1.m.8.cv2.bn.running_var", "backbone.dark4.1.m.8.cv2.bn.num_batches_tracked", "backbone.dark5.2.m.1.cv1.conv.weight", "backbone.dark5.2.m.1.cv1.bn.weight", "backbone.dark5.2.m.1.cv1.bn.bias", "backbone.dark5.2.m.1.cv1.bn.running_mean", "backbone.dark5.2.m.1.cv1.bn.running_var", "backbone.dark5.2.m.1.cv1.bn.num_batches_tracked", "backbone.dark5.2.m.1.cv2.conv.weight", "backbone.dark5.2.m.1.cv2.bn.weight", "backbone.dark5.2.m.1.cv2.bn.bias", "backbone.dark5.2.m.1.cv2.bn.running_mean", "backbone.dark5.2.m.1.cv2.bn.running_var", "backbone.dark5.2.m.1.cv2.bn.num_batches_tracked", "backbone.dark5.2.m.2.cv1.conv.weight", "backbone.dark5.2.m.2.cv1.bn.weight", "backbone.dark5.2.m.2.cv1.bn.bias", "backbone.dark5.2.m.2.cv1.bn.running_mean", "backbone.dark5.2.m.2.cv1.bn.running_var", "backbone.dark5.2.m.2.cv1.bn.num_batches_tracked", "backbone.dark5.2.m.2.cv2.conv.weight", "backbone.dark5.2.m.2.cv2.bn.weight", "backbone.dark5.2.m.2.cv2.bn.bias", "backbone.dark5.2.m.2.cv2.bn.running_mean", "backbone.dark5.2.m.2.cv2.bn.running_var", "backbone.dark5.2.m.2.cv2.bn.num_batches_tracked", "conv3_for_upsample1.m.1.cv1.conv.weight", "conv3_for_upsample1.m.1.cv1.bn.weight", "conv3_for_upsample1.m.1.cv1.bn.bias", "conv3_for_upsample1.m.1.cv1.bn.running_mean", "conv3_for_upsample1.m.1.cv1.bn.running_var", "conv3_for_upsample1.m.1.cv1.bn.num_batches_tracked", "conv3_for_upsample1.m.1.cv2.conv.weight", "conv3_for_upsample1.m.1.cv2.bn.weight", "conv3_for_upsample1.m.1.cv2.bn.bias", "conv3_for_upsample1.m.1.cv2.bn.running_mean", "conv3_for_upsample1.m.1.cv2.bn.running_var", "conv3_for_upsample1.m.1.cv2.bn.num_batches_tracked", "conv3_for_upsample1.m.2.cv1.conv.weight", "conv3_for_upsample1.m.2.cv1.bn.weight", "conv3_for_upsample1.m.2.cv1.bn.bias", "conv3_for_upsample1.m.2.cv1.bn.running_mean", "conv3_for_upsample1.m.2.cv1.bn.running_var", "conv3_for_upsample1.m.2.cv1.bn.num_batches_tracked", "conv3_for_upsample1.m.2.cv2.conv.weight", "conv3_for_upsample1.m.2.cv2.bn.weight", "conv3_for_upsample1.m.2.cv2.bn.bias", "conv3_for_upsample1.m.2.cv2.bn.running_mean", "conv3_for_upsample1.m.2.cv2.bn.running_var", "conv3_for_upsample1.m.2.cv2.bn.num_batches_tracked", "conv3_for_upsample2.m.1.cv1.conv.weight", "conv3_for_upsample2.m.1.cv1.bn.weight", "conv3_for_upsample2.m.1.cv1.bn.bias", 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"conv3_for_downsample1.m.1.cv1.conv.weight", "conv3_for_downsample1.m.1.cv1.bn.weight", "conv3_for_downsample1.m.1.cv1.bn.bias", "conv3_for_downsample1.m.1.cv1.bn.running_mean", "conv3_for_downsample1.m.1.cv1.bn.running_var", "conv3_for_downsample1.m.1.cv1.bn.num_batches_tracked", "conv3_for_downsample1.m.1.cv2.conv.weight", "conv3_for_downsample1.m.1.cv2.bn.weight", "conv3_for_downsample1.m.1.cv2.bn.bias", "conv3_for_downsample1.m.1.cv2.bn.running_mean", "conv3_for_downsample1.m.1.cv2.bn.running_var", "conv3_for_downsample1.m.1.cv2.bn.num_batches_tracked", "conv3_for_downsample1.m.2.cv1.conv.weight", "conv3_for_downsample1.m.2.cv1.bn.weight", "conv3_for_downsample1.m.2.cv1.bn.bias", "conv3_for_downsample1.m.2.cv1.bn.running_mean", "conv3_for_downsample1.m.2.cv1.bn.running_var", "conv3_for_downsample1.m.2.cv1.bn.num_batches_tracked", "conv3_for_downsample1.m.2.cv2.conv.weight", "conv3_for_downsample1.m.2.cv2.bn.weight", "conv3_for_downsample1.m.2.cv2.bn.bias", "conv3_for_downsample1.m.2.cv2.bn.running_mean", "conv3_for_downsample1.m.2.cv2.bn.running_var", "conv3_for_downsample1.m.2.cv2.bn.num_batches_tracked", "conv3_for_downsample2.m.1.cv1.conv.weight", "conv3_for_downsample2.m.1.cv1.bn.weight", "conv3_for_downsample2.m.1.cv1.bn.bias", "conv3_for_downsample2.m.1.cv1.bn.running_mean", "conv3_for_downsample2.m.1.cv1.bn.running_var", "conv3_for_downsample2.m.1.cv1.bn.num_batches_tracked", "conv3_for_downsample2.m.1.cv2.conv.weight", "conv3_for_downsample2.m.1.cv2.bn.weight", "conv3_for_downsample2.m.1.cv2.bn.bias", "conv3_for_downsample2.m.1.cv2.bn.running_mean", "conv3_for_downsample2.m.1.cv2.bn.running_var", "conv3_for_downsample2.m.1.cv2.bn.num_batches_tracked", "conv3_for_downsample2.m.2.cv1.conv.weight", "conv3_for_downsample2.m.2.cv1.bn.weight", "conv3_for_downsample2.m.2.cv1.bn.bias", "conv3_for_downsample2.m.2.cv1.bn.running_mean", "conv3_for_downsample2.m.2.cv1.bn.running_var", "conv3_for_downsample2.m.2.cv1.bn.num_batches_tracked", "conv3_for_downsample2.m.2.cv2.conv.weight", "conv3_for_downsample2.m.2.cv2.bn.weight", "conv3_for_downsample2.m.2.cv2.bn.bias", "conv3_for_downsample2.m.2.cv2.bn.running_mean", "conv3_for_downsample2.m.2.cv2.bn.running_var", "conv3_for_downsample2.m.2.cv2.bn.num_batches_tracked". size mismatch for backbone.stem.conv.conv.weight: copying a param with shape torch.Size([64, 12, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 12, 3, 3]). size mismatch for backbone.stem.conv.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for backbone.stem.conv.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for backbone.stem.conv.bn.running_mean: copying a param