You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
43 lines
1.4 KiB
43 lines
1.4 KiB
4 years ago
|
# coding: utf-8
|
||
|
|
import sys, os
|
||
|
|
sys.path.append(os.pardir) # 为了导入父目录的文件而进行的设定
|
||
|
|
import numpy as np
|
||
|
|
import matplotlib.pyplot as plt
|
||
|
|
from dataset.mnist import load_mnist
|
||
|
|
from simple_convnet import SimpleConvNet
|
||
|
|
from common.trainer import Trainer
|
||
|
|
|
||
|
|
# 读入数据
|
||
|
|
(x_train, t_train), (x_test, t_test) = load_mnist(flatten=False)
|
||
|
|
|
||
|
|
# 处理花费时间较长的情况下减少数据
|
||
|
|
#x_train, t_train = x_train[:5000], t_train[:5000]
|
||
|
|
#x_test, t_test = x_test[:1000], t_test[:1000]
|
||
|
|
|
||
|
|
max_epochs = 20
|
||
|
|
|
||
|
|
network = SimpleConvNet(input_dim=(1,28,28),
|
||
|
|
conv_param = {'filter_num': 30, 'filter_size': 5, 'pad': 0, 'stride': 1},
|
||
|
|
hidden_size=100, output_size=10, weight_init_std=0.01)
|
||
|
|
|
||
|
|
trainer = Trainer(network, x_train, t_train, x_test, t_test,
|
||
|
|
epochs=max_epochs, mini_batch_size=100,
|
||
|
|
optimizer='Adam', optimizer_param={'lr': 0.001},
|
||
|
|
evaluate_sample_num_per_epoch=1000)
|
||
|
|
trainer.train()
|
||
|
|
|
||
|
|
# 保存参数
|
||
|
|
network.save_params("params.pkl")
|
||
|
|
print("Saved Network Parameters!")
|
||
|
|
|
||
|
|
# 绘制图形
|
||
|
|
markers = {'train': 'o', 'test': 's'}
|
||
|
|
x = np.arange(max_epochs)
|
||
|
|
plt.plot(x, trainer.train_acc_list, marker='o', label='train', markevery=2)
|
||
|
|
plt.plot(x, trainer.test_acc_list, marker='s', label='test', markevery=2)
|
||
|
|
plt.xlabel("epochs")
|
||
|
|
plt.ylabel("accuracy")
|
||
|
|
plt.ylim(0, 1.0)
|
||
|
|
plt.legend(loc='lower right')
|
||
|
|
plt.show()
|