code: def haar_transform(x):
      """
      Discrete Haar transform.
  
      Performs a Haar transform along the final dimension.
      This is the inverse of :func:`inverse_haar_transform`.
  
      :param Tensor x: The input signal.
      :rtype: Tensor
      """
      n = x.size(-1) // 2
      even, odd, end = (
          x[..., 0 : n + n : 2],
          x[..., 1 : n + n : 2],
          x[..., n + n :],
      )
      hi = _ROOT_TWO_INVERSE * (even - odd)
      lo = _ROOT_TWO_INVERSE * (even + odd)
      if n >= 2:
          lo = haar_transform(lo)
      x = torch.cat([lo, hi, end], dim=-1)
      return x
  
imports: import math
  import torch
  from torch.fft import irfft, rfft
  from ..None import settings
label_desc: Use image node_id 13 for calling a global function with example usage: haar_transform(x) and returns: x