code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      padding="same",
      num_groups=32,
      act_type=None,
      **kwargs,
  ):
      super().__init__()
      self._conv = nn.Conv2D(
          in_channels,
          out_channels,
          kernel_size,
          padding=padding,
          **kwargs,
      )
  
      if "data_format" in kwargs:
          data_format = kwargs["data_format"]
      else:
          data_format = "NCHW"
      self._group_norm = nn.GroupNorm(
          num_groups, out_channels, data_format=data_format
      )
      self._act_type = act_type
      if act_type is not None:
          self._act = layers.Activation(act_type)
  
imports: import os
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
label_desc: Use image node_id 1 to create a new ConvGNAct object from inherited base classes: nn with example: obj = ConvGNAct(in_channels, out_channels, kernel_size, padding, num_groups, act_type)