githubai写代码

import tensorflow as tf import numpy as np

# 生成一些随机数据 np.random.seed(0) x_data = np.random.rand(100).astype(np.float32) y_data = x_data * 0.1 + 0.3

# 创建tensorflow结构 Weights = tf.Variable(tf.random.uniform([1], -1.0, 1.0)) biases = tf.Variable(tf.zeros([1]))

y = Weights * x_data + biases

loss = tf.reduce_mean(tf.square(y - y_data))

optimizer = tf.compat.v1.train.GradientDescentOptimizer(0.5) train = optimizer.minimize(loss)

init = tf.compat.v1.initialize_all_variables()

# 创建tensorflow Session sess = tf.compat.v1.Session() sess.run(init)

# 训练模型 for step in range(201): sess.run(train) if step % 20 == 0: print(step, sess.run(Weights), sess.run(biases))

# 输出结果 print("训练完毕！") print("Weight: ", sess.run(Weights)) print("biases: ", sess.run(biases))