#ミニバッチ学習
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 = x_train[batch_mask]

print(batch_mask)

#ミニバッチ学習
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 = x_train[batch_mask]

print(batch_mask)
