class_docstr: Transpose some results by given keys.
  
  Args:
      keys (Sequence[str]): Keys of results to be transposed.
      order (Sequence[int]): Order of transpose.
class_docstr_tok: ["Transpose","some","results","by","given","keys",".","Args",":","keys","(","Sequence","[","str","]",")",":","Keys","of","results","to","be","transposed",".","order","(","Sequence","[","int","]",")",":","Order","of","transpose","."]
code: def __repr__(self):
      return (
          self.__class__.__name__
          + f"(keys={self.keys}, order={self.order})"
      )
  
imports: from collections.abc import Sequence
  import annotator.uniformer.mmcv
  import numpy
  import torch
  from annotator.uniformer.mmcv.parallel import DataContainer
  from ..builder import PIPELINES
label_desc: Use image node_id 3 for calling the Transpose obj's underlying member method code with example usage: obj.__repr__() and returns: unknown