使用MINST数据集训练模型并动态绘制Loss和准确率的趋势图_mnist数据集绘制训练损失和准确率曲线

MINST训练的代码直接参考http://www.pianshen.com/article/3783475094/

由于显示的结果不太清晰明了，因此使用pyplot加工了下：代码如下

#coding: utf-8
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
 
mnist = input_data.read_data_sets("MNIST_data", one_hot=True)
 
input_x = tf.placeholder(tf.float32, [None, 28*28])/255  
output_y = tf.placeholder(tf.int32, [None, 10])   
input_x_images = tf.reshape(input_x, [-1, 28, 28, 1])
 
test_x = mnist.test.images[:3000]  
test_y = mnist.test.labels[:3000]  
 
conv1 = tf.layers.conv2d(inputs=input_x_images, 
                         filters=32,
                         kernel_size=[5, 5],
                         strides=1,
                         padding='same',
                         activat