code: def make_gaussian_kernel(sigma: int) -> torch.Tensor:
      if sigma <= 0:
          raise ValueError(
              f"expecting positive sigma, got sigma={sigma}"
          )
      return gaussian_1d(
          sigma=torch.tensor(sigma),
          truncated=3,
          approx="sampled",
          normalize=False,
      )
  
file_path: MONAI/monai/losses/multi_scale.py
imports: from __future__ import annotations
  import torch
  from torch.nn.modules.loss import _Loss
  from monai.networks.layers import gaussian_1d, separable_filtering
  from monai.utils import LossReduction
label_desc: Use image node_id 1 for calling a global function with example usage: make_gaussian_kernel(sigma) and returns: gaussian_1d