class_docstr: A helper class for handling relay functions from darknet model.
docstr: Parse attributes and handle the rnn layers.
docstr_tok: ["Parse","attributes","and","handle","the","rnn","layers","."]
code: def _handle_darknet_rnn_layers(self, layer_num, sym):
      """Parse attributes and handle the rnn layers."""
      attr = {}
      layer = self._net.layers[layer_num]
      processed = False
  
      layer_type = LAYERTYPE(layer.type)
      if LAYERTYPE.RNN == layer_type:
          attr.update({"n": layer.n})
          attr.update({"batch": layer.batch})
          attr.update({"num_hidden": str(layer.outputs)})
          state = self._get_rnn_state_buffer(layer, "rnn")
          for _ in range(layer.steps):
              input_layer = layer.input_layer
              prefix = "_input_" + str(layer_num)
              sym = self._get_darknet_rnn_attrs(
                  input_layer, prefix, sym
              )
  
              self_layer = layer.self_layer
              prefix = "_self_" + str(layer_num)
              state = self._get_darknet_rnn_attrs(
                  self_layer, prefix, state
              )
  
              state = sym + state
              self._outs.append(state)
  
              output_layer = layer.output_layer
              prefix = "_output_" + str(layer_num)
              sym = self._get_darknet_rnn_attrs(
                  output_layer, prefix, state
              )
  
          self._sym_array[layer_num] = sym
          processed = True
      return processed, sym
  
imports: from enum import Enum
  import numpy
  import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from .common import get_relay_op, new_var
label_desc: Use image node_id 15 for calling the GraphProto obj's underlying member method code with example usage: obj._handle_darknet_rnn_layers(layer_num, sym) and returns: processed,  sym