tensorflow

tensorflow

W3Cschool中tensorflow官方文档中tensorflow构建图的代码是tensorflow1.x的版本
本文给出tensorflow2.x的代码以供入门萌新学习

import tensorflow as tf
import numpy as np
tf.compat.v1.disable_eager_execution() #经常会用到这个
# 使用 NumPy 生成假数据(phony data), 总共 100 个点.
x_data = np.float32(np.random.rand(2, 100)) # 随机输入
y_data = np.dot([0.100, 0.200], x_data) + 0.300

# 构造一个线性模型
#
b = tf.Variable(tf.zeros([1]))
W = tf.Variable(tf.compat.v1.random_uniform([1, 2], -1.0, 1.0))
y = tf.matmul(W, x_data) + b

# 最小化方差
loss = tf.compat.v1.reduce_mean(tf.square(y - y_data))
optimizer = tf.compat.v1.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)

# 初始化变量
init = tf.compat.v1.initialize_all_variables()

# 启动图 (graph)
sess = tf.compat.v1.Session()
sess.run(init)

# 拟合平面
xrange = 201
for step in range(xrange):
    sess.run(train)
    if step % 20 == 0:
        print(step, sess.run(W), sess.run(b))