code: def _cudnn_rnn_backward(op: ops.Operation, *grads):
      """Gradients for the CudnnRNN op."""
      if not op.get_attr("is_training"):
          raise ValueError(
              "To use CudnnRNN in gradients, is_training must be set to True."
          )
      return gen_cudnn_rnn_ops.cudnn_rnn_backprop(
          input=op.inputs[0],
          input_h=op.inputs[1],
          input_c=op.inputs[2],
          params=op.inputs[3],
          output=op.outputs[0],
          output_h=op.outputs[1],
          output_c=op.outputs[2],
          output_backprop=grads[0],
          output_h_backprop=grads[1],
          output_c_backprop=grads[2],
          reserve_space=op.outputs[3],
          dropout=op.get_attr("dropout"),
          seed=op.get_attr("seed"),
          seed2=op.get_attr("seed2"),
          rnn_mode=op.get_attr("rnn_mode"),
          input_mode=op.get_attr("input_mode"),
          direction=op.get_attr("direction"),
      )
  
imports: from tensorflow.python.framework import ops
  from tensorflow.python.ops import gen_cudnn_rnn_ops
label_desc: Use image node_id 1 for calling a global function with example usage: _cudnn_rnn_backward(op) and returns: gen_cudnn_rnn_ops