code: def __init__(
      self, in_channels: int, out_channels: int, kernel_size: int
  ) -> None:
      super().__init__()
      self.conv1 = ConvNormAct(
          in_channels, out_channels, 1, act="none"
      )  # point-wise
      self.conv2 = ConvNormAct(
          out_channels, out_channels, kernel_size, groups=out_channels
      )
  
imports: from __future__ import annotations
  from typing import NamedTuple
  from torch import nn
  from kornia.contrib.models.common import ConvNormAct
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK
label_desc: Use image node_id 1 to create a new LightConvNormAct object from inherited base classes: nn with example: obj = LightConvNormAct(in_channels, out_channels, kernel_size)