code: def __init__(self, input_size, hidden_size, dropout=0.0):
      super(AttentiveLSTMLayer, self).__init__()
      self.input_size = input_size
      self.hidden_size = hidden_size
      attention_hsize = hidden_size
      self.attention_hsize = attention_hsize
  
      self.cell = LSTMCell(input_size, hidden_size)
      self.attn_layer = nn.Sequential(
          nn.Linear(2 * hidden_size + input_size, attention_hsize),
          nn.Tanh(),
          nn.Linear(attention_hsize, 1),
      )
      self.softmax = nn.Softmax(dim=0)
      self.dropout = dropout
  
imports: from typing import List, Optional
  import torch
  import torch.nn
  from ..losses.pytorch import MAE
  from ..common._base_recurrent import BaseRecurrent
  from ..common._modules import MLP
label_desc: Use image node_id 1 to create a new AttentiveLSTMLayer object from inherited base classes: nn with example: obj = AttentiveLSTMLayer(input_size, hidden_size, dropout)