code: def inputs(self):
      return [
          tf.TensorSpec([None, 224, 224, 3], tf.float32, "input"),
          tf.TensorSpec([None], tf.int32, "label"),
      ]
  
file_path: tensorpack/examples/ResNet/load-resnet.py
imports: import argparse
  import functools
  import numpy
  import re
  import cv2
  import six
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow.dataset import ILSVRCMeta
  from tensorpack.utils import logger
  from imagenet_utils import ImageNetModel, eval_classification, get_imagenet_dataflow
  from resnet_model import resnet_bottleneck, resnet_group
label_desc: Use image node_id 1 for calling the Model obj's underlying member method code with example usage: obj.inputs() and returns: list