我用re-resnet50替换其他特征提取网络时发生了错误，能帮我解答吗，问题如下。

[myheal000]

File "/kaggle/input/mytest068/tools/train.py", line 153, in main() File "/kaggle/input/mytest068/tools/train.py", line 149, in main meta=meta) File "/kaggle/working/newobb/mmdet/apis/train.py", line 133, in train_detector runner.run(data_loaders, cfg.workflow, cfg.total_epochs) File "/opt/conda/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 130, in run epoch_runner(data_loaders[i], **kwargs) File "/opt/conda/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 51, in train self.run_iter(data_batch, train_mode=True, **kwargs) File "/opt/conda/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 30, in run_iter **kwargs) File "/opt/conda/lib/python3.7/site-packages/mmcv/parallel/data_parallel.py", line 75, in train_step return self.module.train_step(*inputs[0], **kwargs[0]) File "/kaggle/working/newobb/mmdet/models/detectors/base.py", line 237, in train_step losses = self(**data) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/kaggle/working/newobb/mmdet/core/fp16/decorators.py", line 51, in new_func return old_func(*args, **kwargs) File "/kaggle/working/newobb/mmdet/models/detectors/base.py", line 172, in forward return self.forward_train(img, img_metas, **kwargs) File "/kaggle/working/newobb/mmdet/models/detectors/obb/obb_two_stage.py", line 154, in forward_train x = self.extract_feat(img) File "/kaggle/working/newobb/mmdet/models/detectors/obb/obb_two_stage.py", line 86, in extract_feat x = self.neck(x) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/kaggle/working/newobb/mmdet/core/fp16/decorators.py", line 51, in new_func return old_func(*args, **kwargs) File "/kaggle/working/newobb/mmdet/models/necks/fpn.py", line 173, in forward for i, lateral_conv in enumerate(self.lateral_convs) File "/kaggle/working/newobb/mmdet/models/necks/fpn.py", line 173, in for i, lateral_conv in enumerate(self.lateral_convs) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/opt/conda/lib/python3.7/site-packages/mmcv/cnn/bricks/conv_module.py", line 201, in forward x = self.conv(x) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 423, in forward return self._conv_forward(input, self.weight) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 420, in _conv_forward self.padding, self.dilation, self.groups) TypeError: conv2d(): argument 'input' (position 1) must be Tensor, not GeometricTensor

[csuhan]

You can transform a GeometricTensor to standard tensor by changing this line to outs.append(x.tensor) https://github.com/csuhan/ReDet/blob/f4a8e7dadec990f8a92437024416f0fb07a868db/mmdet/models/backbones/re_resnet.py#L529