# coding: UTF-8

import numpy as np
from dataset.mnist import load_mnist

(x_train,t_train), (x_test,t_test) = load_mnist(normalize=True, one_hot_label=True)

print(x_train.shape)
print(t_train.shape)

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]

print(np.random.choice(60000, 10))
