import sys, os
import numpy as np
from dataset.mnist import load_mnist

sys.path.append(os.pardir)
(x_train, t_train), (x_test, t_test) = load_mnist(normalize=True, one_hot_label=True)

# x_train [60000, 784(28x28)]
# t_train [60000, 10]

# batch (random)
train_size = x_train.shape[0]
batch_size = 10
batch_mask = np.random.choice(train_size, batch_size)
x_batch = x_train[batch_mask]
t_batch = t_train[batch_mask]