when i train resnet_101, everything is ok,but when i train resnet_50(dont have R-50.pkl) ,encounter follow proplem:
RuntimeError: Error(s) in loading state_dict for GeneralizedRCNN:
size mismatch for rpn.head.cls_logits.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([15]).
size mismatch for rpn.head.cls_logits.weight: copying a param with shape torch.Size([80, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([15, 256, 1, 1]).
size mismatch for rpn.head.bbox_pred.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([60]).
size mismatch for rpn.head.bbox_pred.weight: copying a param with shape torch.Size([4, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([60, 256, 1, 1]).
according to your suggestion (python setup.py build develop)at issue #92 ,the problem has been solved,but another error has appeared like issues #65 ,
The difinite description is below:
RuntimeError: Error(s) in loading state_dict for GeneralizedRCNN:
size mismatch for rpn.head.cls_logits.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([15]).
size mismatch for rpn.head.cls_logits.weight: copying a param with shape torch.Size([80, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([15, 256, 1, 1]).
size mismatch for rpn.head.bbox_pred.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([60]).
size mismatch for rpn.head.bbox_pred.weight: copying a param with shape torch.Size([4, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([60, 256, 1, 1]).
when i train resnet_101, everything is ok,but when i train resnet_50(dont have R-50.pkl) ,encounter follow proplem:
RuntimeError: Error(s) in loading state_dict for GeneralizedRCNN: size mismatch for rpn.head.cls_logits.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([15]). size mismatch for rpn.head.cls_logits.weight: copying a param with shape torch.Size([80, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([15, 256, 1, 1]). size mismatch for rpn.head.bbox_pred.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([60]). size mismatch for rpn.head.bbox_pred.weight: copying a param with shape torch.Size([4, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([60, 256, 1, 1]).
according to your suggestion (python setup.py build develop)at issue #92 ,the problem has been solved,but another error has appeared like issues #65 , The difinite description is below: RuntimeError: Error(s) in loading state_dict for GeneralizedRCNN: size mismatch for rpn.head.cls_logits.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([15]). size mismatch for rpn.head.cls_logits.weight: copying a param with shape torch.Size([80, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([15, 256, 1, 1]). size mismatch for rpn.head.bbox_pred.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([60]). size mismatch for rpn.head.bbox_pred.weight: copying a param with shape torch.Size([4, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([60, 256, 1, 1]).