parameters: (self, current_node)
docstring: The entry point for quantizing nodes to eight bit and back.
docstring_summary: The entry point for quantizing nodes to eight bit and back.
docstring_tokens: The entry point for quantizing nodes to eight bit and back .
function: def quantize_nodes_recursively(self, current_node):
      """The entry point for quantizing nodes to eight bit and back."""
      for input_node_name in current_node.input:
        input_node_name = node_name_from_input(input_node_name)
        if input_node_name in self.already_visited:
          continue
        input_node = self.nodes_map[input_node_name]
        self.quantize_nodes_recursively(input_node)
      self.already_visited[current_node.name] = True
      nodes_to_quantize = ["Conv2D", "BiasAdd", "MatMul"]
      if any(current_node.op in s for s in nodes_to_quantize):
        for input_name in current_node.input:
          input_name = node_name_from_input(input_name)
          input_node = self.nodes_map[input_name]
          self.quantize_node(input_node)
        self.quantize_node(current_node)
      else:
        new_node = tf.NodeDef()
        new_node.CopyFrom(current_node)
        self.add_output_graph_node(new_node)
function_tokens: def quantize_nodes_recursively ( self , current_node ) : for input_node_name in current_node . input : input_node_name = node_name_from_input ( input_node_name ) if input_node_name in self . already_visited : continue input_node = self . nodes_map [ input_node_name ] self . quantize_nodes_recursively ( input_node ) self . already_visited [ current_node . name ] = True nodes_to_quantize = [ "Conv2D" , "BiasAdd" , "MatMul" ] if any ( current_node . op in s for s in nodes_to_quantize ) : for input_name in current_node . input : input_name = node_name_from_input ( input_name ) input_node = self . nodes_map [ input_name ] self . quantize_node ( input_node ) self . quantize_node ( current_node ) else : new_node = tf . NodeDef ( ) new_node . CopyFrom ( current_node ) self . add_output_graph_node ( new_node )