code: def get_logits(self, image):
      with argscope(
          [Conv2D, MaxPooling, GlobalAvgPooling, BatchNorm],
          data_format=self.data_format,
      ):
          return resnet_backbone(
              image,
              self.num_blocks,
              preact_group if self.mode == "preact" else resnet_group,
              self.block_func,
          )
  
file_path: tensorpack/examples/ResNet/imagenet-resnet.py
imports: import argparse
  import os
  from tensorpack import QueueInput, TFDatasetInput, logger
  from tensorpack.callbacks import *
  from tensorpack.dataflow import FakeData
  from tensorpack.models import *
  from tensorpack.tfutils import argscope, SmartInit
  from tensorpack.train import SyncMultiGPUTrainerReplicated, TrainConfig, launch_train_with_config
  from tensorpack.utils.gpu import get_num_gpu
  from imagenet_utils import ImageNetModel, eval_classification, get_imagenet_dataflow, get_imagenet_tfdata
  import resnet_model
  from resnet_model import preact_group, resnet_backbone, resnet_group
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.get_logits(image) and returns: resnet_backbone