code: def linspace(
      backcast_length: int, forecast_length: int
  ) -> Tuple[np.ndarray, np.ndarray]:
      lin_space = np.linspace(
          -backcast_length,
          forecast_length,
          backcast_length + forecast_length,
          dtype=np.float32,
      )
      b_ls = lin_space[:backcast_length]
      f_ls = lin_space[backcast_length:]
      return b_ls, f_ls
  
imports: from typing import List, Tuple
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from gluonts.time_feature import get_seasonality
label_desc: Use image node_id 1 for calling a global function with example usage: linspace(backcast_length, forecast_length) and returns: b_ls,  f_ls