code: def __init__(self, image_dim, question_dim, **kwargs):
      super().__init__()
  
      combine_type = kwargs["modal_combine"]["type"]
      combine_params = kwargs["modal_combine"]["params"]
      modal_combine_layer = ModalCombineLayer(
          combine_type, image_dim, question_dim, **combine_params
      )
  
      transform_type = kwargs["transform"]["type"]
      transform_params = kwargs["transform"]["params"]
      transform_layer = TransformLayer(
          transform_type,
          modal_combine_layer.out_dim,
          **transform_params,
      )
  
      normalization = kwargs["normalization"]
  
      self.module = TopDownAttention(
          modal_combine_layer, transform_layer, normalization
      )
  
      if hasattr(self.module, "out_dim"):
          self.out_dim = self.module.out_dim
  
imports: import math
  from typing import Optional, Tuple, Type
  import torch
  from mmf.modules.layers import GatedTanh, ModalCombineLayer, TransformLayer
  from torch import nn
label_desc: Use image node_id 1 to create a new AttentionLayer object from inherited base classes: nn with example: obj = AttentionLayer(image_dim, question_dim)