class_docstr: A helper class for handling relay functions from darknet model.
docstr: To preprocess each darknet layer, some layer doesnt need processing.
docstr_tok: ["To","preprocess","each","darknet","layer",",","some","layer","doesnt","need","processing","."]
code: def _preproc_layer(self, layer, layer_num):
      """To preprocess each darknet layer, some layer doesnt need processing."""
      if layer_num == 0:
          name = "data"
          sym = new_var(name, shape=self._shape, dtype=self._dtype)
      else:
          sym = self._sym_array[layer_num - 1]
      skip_layer = False
      layer_type = LAYERTYPE(layer.type)
      if LAYERTYPE.ROUTE == layer_type:
          sym = []
          for j in range(layer.n):
              sym.append(self._sym_array[layer.input_layers[j]])
          if layer.n == 1:
              skip_layer = True
  
      elif LAYERTYPE.COST == layer_type:
          skip_layer = True
  
      elif LAYERTYPE.SHORTCUT == layer_type:
          sym = [sym, self._sym_array[layer.index]]
  
      elif LAYERTYPE.BLANK == layer_type:
          skip_layer = True
  
      if skip_layer is True:
          self._sym_array[layer_num] = sym
  
      return skip_layer, 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 10 for calling the GraphProto obj's underlying member method code with example usage: obj._preproc_layer(layer, layer_num) and returns: skip_layer,  sym