TF:Tensorflow结构简单应用,随机生成100个数,利用Tensorflow训练使其逼近已知线性直线的效率和截距—Jason niu
import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import tensorflow as tf import numpy as np x_data = np.random.rand(100).astype(np.float32) y_data = x_data*0.1 + 0.3 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.train.GradientDescentOptimizer(0.5) train = optimizer.minimize(loss) #init = tf.initialize_all_variables() init = tf.global_variables_initializer() ### create tensorflow structure end ### sess = tf.Session() sess.run(init) for step in range(201): sess.run(train) if step % 10 == 0: print(step, sess.run(Weights), sess.run(biases))
不念过去,不畏将来!
理想,信仰,使命感……
愿你出走半生,归来仍是少年……