class_docstr: A transition used for refining the output of the last stage.
  
  Args:
      in_channels (int): Number of input channels.
      out_channels (int): Number of output channels.
      num_inputs (int): Number of inputs of the FPN features.
      kernel_size (int): Kernel size for the conv. Default: 3.
code: def __init__(
      self,
      in_channels,
      out_channels,
      num_inputs,
      kernel_size=3,
      init_cfg=None,
      **kwargs,
  ):
      super().__init__(in_channels, out_channels, init_cfg)
      self.num_inputs = num_inputs
      self.conv_out = ConvModule(
          in_channels,
          out_channels,
          kernel_size,
          padding=(kernel_size - 1) // 2,
          **kwargs,
      )
  
imports: import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule
  from mmengine.model import BaseModule
  from mmdet.registry import MODELS
label_desc: Use image node_id 1 to create a new LastConv object from inherited base classes: Transition with example: obj = LastConv(in_channels, out_channels, num_inputs, kernel_size, init_cfg)