class_docstr: Transpose module for torch.nn.Sequential().
class_docstr_tok: ["Transpose","module","for","torch.nn.Sequential","(",")","."]
docstr: Initialize Transpose module.
docstr_tok: ["Initialize","Transpose","module","."]
code: def __init__(self, dim1: int, dim2: int):
      """Initialize Transpose module."""
      super().__init__()
      self.dim1 = dim1
      self.dim2 = dim2
  
imports: import math
  from typing import Optional, Tuple, Union
  import torch
  from espnet2.gan_tts.vits.transform import piecewise_rational_quadratic_transform
label_desc: Use image node_id 1 to create a new Transpose object from inherited base classes: torch.nn with example: obj = Transpose(dim1, dim2)