第一次用matplotlib.pyplot，按着视频上把代码敲出来，但是我就是跑不出那根拟合曲线，大哥们帮忙看一下

Question

为什么我的没有那个红色的线呢？

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

def add_layer(inputs,in_size,out_size,activation_function=None):
    Weights = tf.Variable(tf.random_normal([in_size,out_size]))
    biases = tf.Variable(tf.zeros([1,out_size])+0.1)  
    Wx_plus_b = tf.matmul(inputs,Weights)+biases
    if activation_function is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_function(Wx_plus_b)
    return outputs
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.float32,[None,1])

l1 = add_layer (xs,1,10,activation_function= tf.nn.relu)
prediction = add_layer(l1,10,1,activation_function= None)

loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction),
                     reduction_indices= [1]))
train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.scatter(x_data,y_data)

plt.ion()
plt.show(block=False)     #block=False
for i in range (1000):
    sess.run(train_step,feed_dict={xs:x_data,ys:y_data})
    if i % 50 == 0:
        #print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))
        try:
            ax.lines.remove(lines[0])
        except Exception:
            pass
        prediction_value = sess.run(prediction,feed_dict={xs:x_data})
        lines = ax.plot(x_data,prediction_value,'y-',lw=10)
        plt.pause(0.1)

Answer 1

不知道你看的是什么视频，以及你说的红色的线是什么线。
ax.scatter(x_data,y_data)
这里是画散点图，而不是折线

你可以看下这里
https://blog.csdn.net/bihehongcha/article/details/78636055