code: def random_batch(batch_size, data_format, seed=None):
      """Create synthetic resnet50 images and labels for testing."""
      if seed:
          tf.random.set_seed(seed)
      shape = (
          (3, 224, 224)
          if data_format == "channels_first"
          else (224, 224, 3)
      )
      shape = (batch_size,) + shape
  
      num_classes = 1000
      images = tf.random.uniform(shape)
      labels = tf.random.uniform(
          [batch_size], minval=0, maxval=num_classes, dtype=tf.int32
      )
      one_hot = tf.one_hot(labels, num_classes)
  
      return images, one_hot
  
imports: import time
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: random_batch(batch_size, data_format, seed) and returns: images,  one_hot