aqibsaeed

import tensorflow as tf
from tensorflow.keras import datasets

def get_cifar_10(batch_size = 128, test_batch_size = 128, shuffle_buffer = 1024):
  (train_images, train_labels), (test_images, test_labels) = datasets.cifar10.load_data()
  num_classes = len(np.unique(train_labels))

  train_images = train_images.astype("float32")/255
  train_images[:,:,:,0] = (train_images[:,:,:,0] - 0.4914) / 0.2023
  train_images[:,:,:,1] = (train_images[:,:,:,1] - 0.4822) / 0.1994