class_docstr: Average attention with window.
  See "Accelerating Neural Transformer via an Average Attention Network"
  for more details.
code: def __init__(self, embed_dim, dropout=0.0, bias=True, window_size=0):
      super().__init__(embed_dim, dropout, bias)
      self.window_size = window_size
  
imports: import torch
  import torch.nn.functional
  from fairseq import utils
  from fairseq.incremental_decoding_utils import with_incremental_state
  from torch import nn
label_desc: Use image node_id 1 to create a new AverageWindowAttention object from inherited base classes: AverageAttention with example: obj = AverageWindowAttention(embed_dim, dropout, bias, window_size)