class_docstr: Stack windowed inputs (x(t-m+1), ... x(t)).
class_docstr_tok: ["Stack","windowed","inputs","(","x","(","t-m+1",")",",","...","x","(","t",")",")","."]
docstr: Return shape of preprocessed input.
docstr_tok: ["Return","shape","of","preprocessed","input","."]
code: def output_shape(self):
      """Return shape of preprocessed input."""
      return (self.__history_len,) + self._input_shape
  
imports: from abc import ABCMeta, abstractmethod
  from collections import deque
  import numpy
  from PIL import Image
label_desc: Use image node_id 2 for calling the SlidingWindow obj's underlying member method code with example usage: obj.output_shape() and returns: unknown