code: def __init__(
      self, input_size, hidden_size, num_embeddings, use_gru=False
  ):
      super(AttentionGRUCell, self).__init__()
      self.i2h = nn.Linear(input_size, hidden_size, bias_attr=False)
      self.h2h = nn.Linear(hidden_size, hidden_size)
      self.score = nn.Linear(hidden_size, 1, bias_attr=False)
  
      self.rnn = nn.GRUCell(
          input_size=input_size + num_embeddings,
          hidden_size=hidden_size,
      )
  
      self.hidden_size = hidden_size
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
label_desc: Use image node_id 1 to create a new AttentionGRUCell object from inherited base classes: nn with example: obj = AttentionGRUCell(input_size, hidden_size, num_embeddings, use_gru)