code: def fuse_conv_bn(model):
      is_train = False
      if model.training:
          model.eval()
          is_train = True
      fuse_list = []
      tmp_pair = [None, None]
      for name, layer in model.named_sublayers():
          if isinstance(layer, nn.Conv2D):
              tmp_pair[0] = name
          if isinstance(layer, nn.BatchNorm2D):
              tmp_pair[1] = name
  
          if tmp_pair[0] and tmp_pair[1] and len(tmp_pair) == 2:
              fuse_list.append(tmp_pair)
              tmp_pair = [None, None]
      model = fuse_layers(model, fuse_list)
      if is_train:
          model.train()
      return model
  
file_path: PaddleDetection/ppdet/utils/fuse_utils.py
imports: import copy
  import paddle
  import paddle.nn
label_desc: Use image node_id 1 for calling a global function with example usage: fuse_conv_bn(model) and returns: model