vgg_19.py 文件源码

def run_testing(sess,ep):
    acc = 0.0
    loss = 0.0
    pre_index = 0
    add = 1000
    for it in range(10):
        batch_x = test_x[pre_index:pre_index+add]
        batch_y = test_y[pre_index:pre_index+add]
        pre_index = pre_index + add
        loss_, acc_  = sess.run([cross_entropy,accuracy],feed_dict={x:batch_x, y_:batch_y, keep_prob: 1.0, train_flag: False})
        loss += loss_ / 10.0
        acc += acc_ / 10.0
    summary = tf.Summary(value=[tf.Summary.Value(tag="test_loss", simple_value=loss), 
                            tf.Summary.Value(tag="test_accuracy", simple_value=acc)])
    return acc, loss, summary


# ========================================================== #
# ?? main()
# Training and Testing 
# Save train/teset loss and acc for visualization
# Save Model in ./model
# ========================================================== #