# -*- coding:utf-8 -*- import tensorflow as tf import os config = tf.ConfigProto() config.gpu_options.allow_growth = True sess = tf.Session(config=config) """TensorBoard 简单例子。 tf.summary.scalar('var_name', var) # 记录标量的变化 tf.summary.histogram('vec_name', vec) # 记录向量或者矩阵，tensor的数值分布变化。 merged = tf.summary.merge_all() # 把所有的记录并把他们写到 log_dir 中 train_writer = tf.summary.FileWriter(FLAGS.log_dir + '/train', sess.graph) # 保存位置 运行完后，在命令行中输入 tensorboard --logdir=log_dir_path """ tf.app.flags.DEFINE_string('log_dir', 'summary/graph/', 'log saving path') FLAGS = tf.app.flags.FLAGS if os.path.exists(FLAGS.log_dir): os.rmdir(FLAGS.log_dir) os.makedirs(FLAGS.log_dir) print 'created log_dir path' with tf.name_scope('add_example'): a = tf.Variable(tf.truncated_normal([100,1], mean=0.5, stddev=0.5), name='var_a') tf.summary.histogram('a_hist', a) b = tf.Variable(tf.truncated_normal([100,1], mean=-0.5, stddev=1.0), name='var_b') tf.summary.histogram('b_hist', b) increase_b = tf.assign(b, b + 0.05) c = tf.add(a, b) tf.summary.histogram('c_hist', c) c_mean = tf.reduce_mean(c) tf.summary.scalar('c_mean', c_mean) merged = tf.summary.merge_all() writer = tf.summary.FileWriter(FLAGS.log_dir+'add_example', sess.graph) def main(_): sess.run(tf.global_variables_initializer()) for step in xrange(500): sess.run([merged, increase_b]) # 每步改变一次 b 的值 summary = sess.run(merged) writer.add_summary(summary, step) writer.close() if __name__ == '__main__': tf.app.run()