class_docstr: ### 🚧 Attention based up-sampling
  
  egin{align}
  x &= U(x,x') + Attention \Big(Q=U(x,x'),K = x', V = x' \Big) \
  x &= x + FFN(x)
  \end{align}
  
  where $U(x,x') = x + LinearUpsampling(x')$
code: def __init__(self):
      super().__init__()
      raise NotImplementedError
  
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 AttentionBasedUpSampling object from inherited base classes: Module with example: obj = AttentionBasedUpSampling()