code: def DoubleConv3x3BnReLU(filters, use_batchnorm, name=None):
      name1, name2 = None, None
      if name is not None:
          name1 = name + "a"
          name2 = name + "b"
  
      def wrapper(input_tensor):
          x = Conv3x3BnReLU(filters, use_batchnorm, name=name1)(
              input_tensor
          )
          x = Conv3x3BnReLU(filters, use_batchnorm, name=name2)(x)
          return x
  
      return wrapper
  
file_path: segmentation_models/segmentation_models/models/fpn.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 3 for calling a global function with example usage: DoubleConv3x3BnReLU(filters, use_batchnorm, name) and returns: wrapper, x