code: def __init__(
      self, embedding: ABCEmbedding, hidden_size: int, vocab_size: int
  ):
      super(GRUDecoder, self).__init__()
      self.embedding = embedding
  
      self.gru = tf.keras.layers.GRU(
          hidden_size,
          return_sequences=True,
          return_state=True,
          recurrent_initializer="glorot_uniform",
      )
      self.fc = tf.keras.layers.Dense(vocab_size)
  
imports: import tensorflow
  from kashgari.embeddings.abc_embedding import ABCEmbedding
label_desc: Use image node_id 1 to create a new GRUDecoder object from inherited base classes: tf.keras with example: obj = GRUDecoder(embedding, hidden_size, vocab_size)