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Semantic segmentation Pretrained model? #8
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Hi, we do not observe the gradient problem when training upernet using the pre-trained model. The message is correct since segmentation model indeed doesnot need fc and head layers of the pre-trained classification model. |
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I use upernet_mae_swin_tiny_256_mask...py, but when I use checkpoint-99-model.pth as the backbone pretrained model. It reports this:
mmseg - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: fc_norm.weight, fc_norm.bias, head.weight, head.bias
when trainning with this model, Gradient overflow.
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