code: def bn2d(in_channels, bn_mom=0.1, lr_mult=1.0, **kwargs):
      assert "bias_attr" not in kwargs, "bias_attr must not in kwargs"
      param_attr = paddle.ParamAttr(learning_rate=lr_mult)
      return nn.BatchNorm2D(
          in_channels,
          momentum=bn_mom,
          weight_attr=param_attr,
          bias_attr=param_attr,
          **kwargs,
      )
  
imports: from functools import partial
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
  from paddleseg.models.backbones.transformer_utils import DropPath, Identity
  from paddleseg.cvlibs.param_init import constant_init, kaiming_normal_init, trunc_normal_init
label_desc: Use image node_id 2 for calling a global function with example usage: bn2d(in_channels, bn_mom, lr_mult) and returns: nn