Use of permute in RCNN

[jtquisenberry]

On lines 53 and 61 of Text-Classification-Models-Pytorch/Model_RCNN/model.py , function permute is used.

input_features = torch.cat([lstm_out,embedded_sent], 2).permute(1,0,2)
...
linear_output = linear_output.permute(0,2,1) # Reshaping fot max_pool

Could you please explain why it is necessary or useful to permute the dimensions of these tensors?