RuntimeError: Expected 4-dimensional input for 4-dimensional weight [64, 256, 3, 3], but got 3-dimensional input of size [5, 160, 160] instead

[w1125]

修改dbnetpp模型，希望将neck中的fpn换成pfpn，在pfpn代码中加入如下代码：
for i, out in enumerate(outs):
outs[i] = F.interpolate(
outs[i], size=outs[0].shape[2:], mode='nearest') # list
out = torch.cat(outs, dim=1)
print(out.shape) # torch.Size([8, 1280, 160, 160])
if self.asf_cfg is not None:
asf_feature = self.asf_conv(out)
attention = self.asf_attn(asf_feature)
enhanced_feature = []
for i, out in enumerate(out):
enhanced_feature.append(attention[:, i:i + 1] * out[i])
out = torch.cat(enhanced_feature, dim=1)
print(out.shape) # torch.Size([8, 5, 160, 160])
if self.conv_after_concat:
out = self.out_conv(out)
print(out.shape) # torch.Size([8, 5, 160, 160])
return tuple(out)
报错：
Traceback (most recent call last):
File "tools/train.py", line 231, in
main()
File "tools/train.py", line 220, in main
train_detector(
File "/root/mmocr/mmocr/apis/train.py", line 155, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 31, in run_iter
outputs = self.model.train_step(data_batch, self.optimizer,
File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 77, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "/root/miniconda3/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 248, in train_step
losses = self(**data)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func
return old_func(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 172, in forward
return self.forward_train(img, img_metas, **kwargs)
File "/root/mmocr/mmocr/models/textdet/detectors/single_stage_text_detector.py", line 37, in forward_train
preds = self.bbox_head(x[0])
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/mmocr/mmocr/models/textdet/dense_heads/db_head.py", line 80, in forward
prob_map = self.binarize(inputs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/container.py", line 141, in forward
input = module(input)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 446, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 442, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Expected 4-dimensional input for 4-dimensional weight [64, 256, 3, 3], but got 3-dimensional input of size [5, 160, 160] instead
请问该如何解决这个问题，另外，如果不要新增代码（即不加入特征融合模块），模型能够顺利构建并训练，希望能得到一些建议，感谢回复。