code: def __init__(self, num_classes, fp16=False):
      super(SyntheticDataset, self).__init__()
      self.num_classes = num_classes
      self.fp16 = fp16
      self.label_list = np.random.randint(
          0, num_classes, (5179510,), dtype=np.int32
      )
      self.num_samples = len(self.label_list)
  
imports: import pickle
  import paddle
  import os
  import cv2
  import six
  import random
  import paddle
  import numpy
  import logging
  from PIL import Image
  from io import BytesIO
  from datasets.kv_helper import read_img_from_bin
label_desc: Use image node_id 1 to create a new SyntheticDataset object from inherited base classes: paddle.io with example: obj = SyntheticDataset(num_classes, fp16)