code: def take_action(observation, configuration):
      board = Board(observation, configuration)
      action = player.take_action(board, "predict")
      return action
  
imports: import pickle
  import base64
  import random
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Categorical
  from zerosum_env.envs.halite.helpers import *
  from zerosum_env import make, evaluate
  from collections import deque
  import os
label_desc: Use image node_id 24 for calling a global function with example usage: take_action(observation, configuration) and returns: action