code: def _symbol_bottom_simple(x, model_hparams, vocab_size, name, reuse):
    
    with tf.variable_scope(name, reuse=reuse):
      # Ensure the inputs are 3-D
      if len(x.get_shape()) == 4:
        x = tf.squeeze(x, axis=3)
      while len(x.get_shape()) < 3:
        x = tf.expand_dims(x, axis=-1)
  
      var = get_weights(model_hparams, vocab_size)
      x = common_layers.dropout_no_scaling(
          x, 1.0 - model_hparams.symbol_dropout)
      ret = common_layers.gather(var, x)
      if model_hparams.multiply_embedding_mode == "sqrt_depth":
        ret *= model_hparams.hidden_size**0.5
      ret *= tf.expand_dims(
          common_layers.cast_like(tf.not_equal(x, 0), ret), -1)
      return ret
docs: Bottom transformation for symbols.