code: def init_population(population_size=32):
      population = []
      graph = Graph(
          4,
          input=[
              Layer(LayerType.input.value, output=[4, 5], size="x"),
              Layer(LayerType.input.value, output=[4, 5], size="y"),
          ],
          output=[
              Layer(LayerType.output.value, input=[4], size="x"),
              Layer(LayerType.output.value, input=[5], size="y"),
          ],
          hide=[
              Layer(
                  LayerType.attention.value, input=[0, 1], output=[2]
              ),
              Layer(
                  LayerType.attention.value, input=[1, 0], output=[3]
              ),
          ],
      )
      for _ in range(population_size):
          g = copy.deepcopy(graph)
          for _ in range(1):
              g.mutation()
          population.append(Individual(g, result=None))
      return population
  
imports: from graph import *
  import copy
  import json
  import logging
  import random
  import numpy
  from nni.tuner import Tuner
  from nni.utils import extract_scalar_reward
label_desc: Use image node_id 1 for calling a global function with example usage: init_population(population_size) and returns: population