code: def gaussian_noise(x: Tensor, severity: int = 1) -> Tensor:
      """Applys gaussian noise."""
      cifar_std = [0.04, 0.06, 0.08, 0.09, 0.10]
      imagenet_std = [0.08, 0.12, 0.18, 0.26, 0.38]
      std = interpolate_severity(x, cifar_std, imagenet_std, severity)
      return (x + torch.randn_like(x) * std).clamp(min=0.0, max=1.0)
  
file_path: TorchDrift/torchdrift/data/functional/corruption_functions.py
imports: from torch import Tensor
  import torch
  import math
  import torchdrift.utils
label_desc: Use image node_id 3 for calling a global function with example usage: gaussian_noise(x, severity) and returns: unknown