code: def make_triangular_kernel(kernel_size: int) -> torch.Tensor:
      fsize = (kernel_size + 1) // 2
      if fsize % 2 == 0:
          fsize -= 1
      f = torch.ones((1, 1, fsize), dtype=torch.float).div(fsize)
      padding = (kernel_size - fsize) // 2 + fsize // 2
      return F.conv1d(f, f, padding=padding).reshape(-1)
  
imports: from __future__ import annotations
  import torch
  from torch.nn import functional
  from torch.nn.modules.loss import _Loss
  from monai.networks.layers import gaussian_1d, separable_filtering
  from monai.utils import LossReduction
  from monai.utils.module import look_up_option
label_desc: Use image node_id 2 for calling a global function with example usage: make_triangular_kernel(kernel_size) and returns: F