class_docstr: ### Average pool shortening
  
  This down-samples by a given factor with average pooling
docstr: * `k` is the shortening factor
code: def __init__(self, k: int):
      """
      * `k` is the shortening factor
      """
      super().__init__()
      # Average pooling layer
      self.pool = nn.AvgPool1d(k, ceil_mode=True)
  
imports: from typing import List
  import torch
  from torch import nn
  from labml_helpers.module import Module
  from labml_nn.transformers import MultiHeadAttention, TransformerLayer
  from labml_nn.transformers.feed_forward import FeedForward
  from labml_nn.transformers.utils import subsequent_mask
label_desc: Use image node_id 1 to create a new AvgPoolShortening object from inherited base classes: Module with example: obj = AvgPoolShortening(k)