class_docstr: Attributes:
  layer_list - a list of layer names in the Keras model
  connection_map - a map where the key is a layer, the value is a list of its successors
  reverse_connection_map - a map where the key is a layer, the value is a list of its predecessors
  keras_layer_map - a map where the key is a layer name, the value is Keras layer
  model - a reference of the keras model.
  blob_names - blob names for each one of the edge.
class_docstr_tok: ["Attributes",":","layer_list","-","a","list","of","layer","names","in","the","Keras","model","connection_map","-","a","map","where","the","key","is","a","layer",",","the","value","is","a","list","of","its","successors","reverse_connection_map","-","a","map","where","the","key","is","a","layer",",","the","value","is","a","list","of","its","predecessors","keras_layer_map","-","a","map","where","the","key","is","a","layer","name",",","the","value","is","Keras","layer","model","-","a","reference","of","the","keras","model",".","blob_names","-","blob","names","for","each","one","of","the","edge","."]
docstr: Extract the ordering of the input layers.
docstr_tok: ["Extract","the","ordering","of","the","input","layers","."]
code: def make_input_layers(self):
      """
      Extract the ordering of the input layers.
      """
      self.input_layers = []
      if hasattr(self.model, "input_layers"):
          input_keras_layers = self.model.input_layers[:]
          self.input_layers = [None] * len(input_keras_layers)
          for layer in self.layer_list:
              keras_layer = self.keras_layer_map[layer]
              if isinstance(
                  keras_layer, _keras.engine.topology.InputLayer
              ):
                  if keras_layer in input_keras_layers:
                      idx = input_keras_layers.index(keras_layer)
                      self.input_layers[idx] = layer
      elif len(self.model.inbound_nodes) <= 1:
          for ts in _to_list(self.model.input):
              # search for the InputLayer that matches this ts
              for l in self.layer_list:
                  kl = self.keras_layer_map[l]
                  if (
                      isinstance(kl, _keras.engine.topology.InputLayer)
                      and kl.input == ts
                  ):
                      self.input_layers.append(l)
      else:
          raise ValueError("Input values cannot be identified.")
  
imports: import keras
  import numpy
label_desc: Use image node_id 6 for calling the NetGraph obj's underlying member method code with example usage: obj.make_input_layers() without return types