code: def normalize_torch(targets: Tensor, threshold: Tensor) -> Tensor:
      """Normalize the targets by using the cumulative density function, PyTorch version."""
      device = targets.device
      image_threshold = threshold.cpu()
  
      dist = Normal(torch.Tensor([0]), torch.Tensor([1]))
      normalized = dist.cdf(targets.cpu() - image_threshold).to(device)
      return normalized
  
file_path: anomalib/src/anomalib/post_processing/normalization/cdf.py
imports: from __future__ import annotations
  import numpy
  import torch
  from scipy.stats import norm
  from torch import Tensor
  from torch.distributions import Normal
label_desc: Use image node_id 3 for calling a global function with example usage: normalize_torch(targets, threshold) and returns: normalized