本篇博客介绍使用matplotlib实现TensorFlow训练过程的可视化,下面是代码:
# encoding:utf-8 import tensorflow as tf import numpy as np import matplotlib.pyplot as plt # 添加层 def add_layer(inputs, in_size, out_size, activation_function=None): W = tf.Variable(tf.random_normal([in_size, out_size])) b = tf.Variable(tf.zeros([1, out_size]) + 0.1) Wx_plus_b = tf.matmul(inputs, W) + b if activation_function is None: outputs = Wx_plus_b else: outputs = activation_function(Wx_plus_b) return outputs # 生成输入数据、噪点和输出数据 x_data = np.linspace(-1, 1, 300)[:, np.newaxis] noise = np.random.normal(0, 0.05, x_data.shape) y_data = np.square(x_data) - 0.5+noise xs = tf.placeholder(tf.float32, [None, 1]) ys = tf.placeholder(tf.fl