docstr: Reorder the decoder incremental state.
  
  See ``TorchGeneratorModel.reorder_decoder_incremental_state`` for a description.
  
  Here, incremental_state is a dict whose keys are layer indices and whose values
  are dicts containing the incremental state for that layer.
docstr_tok: ["Reorder","the","decoder","incremental","state",".","See","``","TorchGeneratorModel.reorder_decoder_incremental_state","``","for","a","description",".","Here",",","incremental_state","is","a","dict","whose","keys","are","layer","indices","and","whose","values","are","dicts","containing","the","incremental","state","for","that","layer","."]
code: def reorder_decoder_incremental_state(
      self, incremental_state: Dict[int, dict], inds: th.Tensor
  ) -> Dict[int, dict]:
      """
      Reorder the decoder incremental state.
  
      See ``TorchGeneratorModel.reorder_decoder_incremental_state`` for a description.
  
      Here, incremental_state is a dict whose keys are layer indices and whose values
      are dicts containing the incremental state for that layer.
      """
      return {
          idx: layer.reorder_incremental_state(
              incremental_state[idx], inds
          )
          for idx, layer in enumerate(self.decoder.transformer.layers)
      }
  
file_path: ParlAI/projects/wizard_of_wikipedia/generator/modules.py
imports: from typing import Dict
  import numpy
  import torch
  import torch.nn
  from parlai.utils.torch import neginf
  from parlai.agents.transformer.modules import TransformerGeneratorModel
label_desc: Use image node_id 3 for calling the EndToEndModel obj's underlying member method code with example usage: obj.reorder_decoder_incremental_state(incremental_state, inds) and returns: unknown