code: def get_distance_map(position):
      ship_pos = transform_position(position)
      distance_y = np.ones((size, size)) * np.arange(21)
      distance_x = distance_y.T
      delta_distance_x = abs(distance_x - ship_pos[0])
      delta_distance_y = abs(distance_y - ship_pos[1])
      offset_distance_x = size - delta_distance_x
      offset_distance_y = size - delta_distance_y
      distance_x = np.where(
          delta_distance_x < offset_distance_x,
          delta_distance_x,
          offset_distance_x,
      )
      distance_y = np.where(
          delta_distance_y < offset_distance_y,
          delta_distance_y,
          offset_distance_y,
      )
      distance_map = distance_x + distance_y
  
      return distance_map.reshape((1, size, size))
  
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 2 for calling a global function with example usage: get_distance_map(position) and returns: distance_map