class_docstr: WindowStreamingE2E constructor.
  
  :param E2E e2e: E2E ASR object
  :param recog_args: arguments for "recognize" method of E2E
code: def _input_window_for_decoder(self, use_all=False):
      if use_all:
          return (
              torch.cat(self._encoder_states, dim=0),
              torch.cat(self._ctc_posteriors, dim=0),
          )
  
      def select_unprocessed_windows(window_tensors):
          last_offset = self._offset
          offset_traversed = 0
          selected_windows = []
          for es in window_tensors:
              if offset_traversed > last_offset:
                  selected_windows.append(es)
                  continue
              offset_traversed += es.size(1)
          return torch.cat(selected_windows, dim=0)
  
      return (
          select_unprocessed_windows(self._encoder_states),
          select_unprocessed_windows(self._ctc_posteriors),
      )
  
imports: import torch
label_desc: Use image node_id 3 for calling the WindowStreamingE2E obj's underlying member method code with example usage: obj._input_window_for_decoder(use_all) and returns: select_unprocessed_windows,  select_unprocessed_windows, torch,  torch, torch