fmnist_data.py

import numpy as np


def load_fashion_mnist_data(no_training_samples, no_testing_samples, random_seed=0):
    np.random.seed(random_seed)

    data = np.load("/Users/arcade/PycharmProjects/set_learn/robustness_set-main copy/set_motif/fashion_mnist.npz ")

    index_train = np.arange(data["X_train"].shape[0])
    np.random.shuffle(index_train)

    index_test = np.arange(data["X_test"].shape[0])
    np.random.shuffle(index_test)

    x_train = data["X_train"][index_train[0:no_training_samples], :]
    y_train = data["Y_train"][index_train[0:no_training_samples], :]
    x_test = data["X_test"][index_test[0:no_testing_samples], :]
    y_test = data["Y_test"][index_test[0:no_testing_samples], :]

    # normalize in 0..1
    x_train = x_train.astype('float64') / 255.
    x_test = x_test.astype('float64') / 255.

    return x_train, y_train, x_test, y_test


x_train, y_train, x_test, y_test = load_fashion_mnist_data(5,0,9)
print('x_train 1', x_train[1])
print('x_train', x_train)
print('y_trian 1', y_train[1])
print('y_train', y_train)