code: def Coord1dPosEncoding(q_len, exponential=False, normalize=True):
      cpe = (
          2
          * (
              torch.linspace(0, 1, q_len).reshape(-1, 1)
              ** (0.5 if exponential else 1)
          )
          - 1
      )
      if normalize:
          cpe = cpe - cpe.mean()
          cpe = cpe / (cpe.std() * 10)
      return cpe
  
imports: import math
  import numpy
  from typing import Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from ..common._base_windows import BaseWindows
  from ..losses.pytorch import MAE
label_desc: Use image node_id 4 for calling a global function with example usage: Coord1dPosEncoding(q_len, exponential, normalize) and returns: cpe