code: def linear_space(past_seq_len, future_seq_len):
      ls = np.arange(-past_seq_len, future_seq_len, 1) / future_seq_len
      b_ls = np.abs(np.flip(ls[:past_seq_len]))
      f_ls = ls[past_seq_len:]
      return b_ls, f_ls
  
imports: import pickle
  import random
  from time import time
  from typing import Union
  import numpy
  import torch
  from torch import nn, optim
  from torch.nn import functional
  from torch.nn.functional import mse_loss, l1_loss, binary_cross_entropy, cross_entropy
  from torch.optim import Optimizer
  from .utils import PYTORCH_REGRESSION_LOSS_MAP
  from pytorch_lightning import seed_everything
label_desc: Use image node_id 3 for calling a global function with example usage: linear_space(past_seq_len, future_seq_len) and returns: b_ls,  f_ls