}

// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
table BidirectionalSequenceRNNOptions {
  time_major:bool;
  fused_activation_function:ActivationFunctionType;
  merge_outputs: bool;
  asymmetric_quantize_inputs:bool;
}

enum FullyConnectedOptionsWeightsFormat: byte {
  DEFAULT = 0,
  SHUFFLED4x16INT8 = 1,
}

}

// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
table BidirectionalSequenceRNNOptions {
  time_major:bool;
  fused_activation_function:ActivationFunctionType;
  merge_outputs: bool;
  asymmetric_quantize_inputs:bool;
}

enum FullyConnectedOptionsWeightsFormat: byte {
  DEFAULT = 0,
  SHUFFLED4x16INT8 = 1,
}

}

// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
table BidirectionalSequenceRNNOptions {
  time_major:bool;
  fused_activation_function:ActivationFunctionType;
  merge_outputs: bool;
  asymmetric_quantize_inputs:bool;
}

// LINT.IfChange
enum FullyConnectedOptionsWeightsFormat: byte {
  DEFAULT = 0,
  SHUFFLED4x16INT8 = 1,
}

                                  Output(old_node, oidx), new_output);
      merged_output = merged_outputs[oidx] = xla_merge_op.output;
    }

    Node* dst = e->dst();
    int dst_idx = e->dst_input();

    s.graph()->RemoveEdge(e);
    s.graph()->AddEdge(merged_output.node(), merged_output.index(), dst,
                       dst_idx);
  }
}