一个TensorFlow的例子

import tensorflow as tf

x = tf.constant(1.0, name='input')

w = tf.Variable(0.8, name='weight')

y = tf.multiply(w, x, name='output')

y_ = tf.constant(0.0, name='correct_value')

loss = tf.pow(y - y_, 2, name='loss')

train_step = tf.train.GradientDescentOptimizer(0.025).minimize(loss)

for value in [x, w, y, y_, loss]:

    tf.summary.scalar(value.op.name, value)

summaries = tf.summary.merge_all()

with tf.Session() as sess:

    summary_writer = tf.summary.FileWriter('log_simple_stats', sess.graph)

    sess.run(tf.global_variables_initializer())

    for i in range(100):

        summary_writer.add_summary(sess.run(summaries), i)

        sess.run(train_step)

巴特西

一个TensorFlow例子

一个TensorFlow的例子

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