code: def __init__(
      self,
      in_channels,
      out_channels,
  ):
      super().__init__()
      self.proj = nn.Sequential(
          nn.Conv2D(
              in_channels,
              out_channels // 2,
              kernel_size=3,
              stride=2,
              padding=1,
          ),
          SyncBatchNorm(out_channels // 2),
          nn.GELU(),
          nn.Conv2D(
              out_channels // 2,
              out_channels,
              kernel_size=3,
              stride=2,
              padding=1,
          ),
          SyncBatchNorm(out_channels),
      )
  
imports: import math
  import numpy
  import paddle
  import paddle.nn
  from paddle.nn import Conv2D
  from paddle.nn.initializer import Assign, Normal
  from paddleseg.cvlibs import manager
  from paddleseg.models.backbones.transformer_utils import DropPath, ones_, to_2tuple, zeros_
  from paddleseg.models.layers import SyncBatchNorm
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new StemConv object from inherited base classes: nn with example: obj = StemConv(in_channels, out_channels)