code: def __init__(self, in_channels, **kwargs):
      super(SAST_Header2, self).__init__()
      out_channels = [64, 64, 128]
      self.tvo_conv = nn.Sequential(
          ConvBNLayer(
              in_channels,
              out_channels[0],
              1,
              1,
              act="relu",
              name="f_tvo1",
          ),
          ConvBNLayer(
              out_channels[0],
              out_channels[1],
              3,
              1,
              act="relu",
              name="f_tvo2",
          ),
          ConvBNLayer(
              out_channels[1],
              out_channels[2],
              1,
              1,
              act="relu",
              name="f_tvo3",
          ),
          ConvBNLayer(
              out_channels[2], 8, 3, 1, act=None, name="f_tvo4"
          ),
      )
      self.tco_conv = nn.Sequential(
          ConvBNLayer(
              in_channels,
              out_channels[0],
              1,
              1,
              act="relu",
              name="f_tco1",
          ),
          ConvBNLayer(
              out_channels[0],
              out_channels[1],
              3,
              1,
              act="relu",
              name="f_tco2",
          ),
          ConvBNLayer(
              out_channels[1],
              out_channels[2],
              1,
              1,
              act="relu",
              name="f_tco3",
          ),
          ConvBNLayer(
              out_channels[2], 2, 3, 1, act=None, name="f_tco4"
          ),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from paddle import ParamAttr
label_desc: Use image node_id 1 to create a new SAST_Header2 object from inherited base classes: nn with example: obj = SAST_Header2(in_channels)