Loads CIFAR100 dataset.

This is a dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 100 fine-grained classes that are grouped into 20 coarse-grained classes. See more info at the CIFAR homepage.

label_mode one of "fine", "coarse". If it is "fine" the category labels are the fine-grained labels, if it is "coarse" the output labels are the coarse-grained superclasses.

Tuple of Numpy arrays: (x_train, y_train), (x_test, y_test).

x_train, x_test: uint8 arrays of RGB image data with shape (num_samples, 3, 32, 32) if tf.keras.backend.image_data_format() is 'channels_first', or (num_samples, 32, 32, 3) if the data format is 'channels_last'.

y_train, y_test: uint8 arrays of category labels with shape (num_samples, 1).

ValueError in case of invalid label_mode.