class_docstr: This module returns a view of the tensor input with its dimensions permuted.
  Args:
      dims (List[int]): The desired ordering of dimensions
class_docstr_tok: ["This","module","returns","a","view","of","the","tensor","input","with","its","dimensions","permuted",".","Args",":","dims","(","List","[","int","]",")",":","The","desired","ordering","of","dimensions"]
code: def forward(self, x: Tensor) -> Tensor:
      return torch.permute(x, self.dims)
  
imports: from typing import List, Optional
  import torch
  from torch import Tensor, nn
  from torch.nn import functional
  from cvnets.layers import Dropout, LinearLayer, StochasticDepth, get_normalization_layer
  from cvnets.layers.activation import build_activation_layer
  from cvnets.modules import BaseModule
label_desc: Use image node_id 2 for calling the Permute obj's underlying member method code with example usage: obj.forward(x) and returns: torch