code: def get_depthwise_conv(dim, kernel_size=3):
      if isinstance(kernel_size, int):
          kernel_size = to_2tuple(kernel_size)
      padding = tuple([k // 2 for k in kernel_size])
      return Conv2D(
          dim,
          dim,
          kernel_size,
          padding=padding,
          bias_attr=True,
          groups=dim,
      )
  
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 for calling a global function with example usage: get_depthwise_conv(dim, kernel_size) and returns: Conv2D