code: def Conv3x3BnReLU(filters, use_batchnorm, name=None):
      kwargs = get_submodules()
  
      def wrapper(input_tensor):
          return Conv2dBn(
              filters,
              kernel_size=3,
              activation="relu",
              kernel_initializer="he_uniform",
              padding="same",
              use_batchnorm=use_batchnorm,
              name=name,
              **kwargs,
          )(input_tensor)
  
      return wrapper
  
file_path: segmentation_models/segmentation_models/models/unet.py
imports: from keras_applications import get_submodules_from_kwargs
  from ._common_blocks import Conv2dBn
  from ._utils import freeze_model, filter_keras_submodules
  from ..backbones.backbones_factory import Backbones
label_desc: Use image node_id 2 for calling a global function with example usage: Conv3x3BnReLU(filters, use_batchnorm, name) and returns: wrapper, Conv2dBn