tensorflow: tensorboard 探究

xdg-open 'http://localhost:6006/#histograms'
tensorboard --logdir=.

tensorboard --logdir .

log_path = './log'
N = 400

import shutil
try:
    shutil.rmtree(log_path)
except OSError:
    pass

import tensorflow as tf

k = tf.placeholder(dtype=tf.float32)

moving_mean = tf.random_normal(shape=[1000], mean=(5*k), stddev=1)
tf.summary.histogram('normal/moving_mean', moving_mean)

shrinking_mean = tf.random_normal(shape=[1000], mean=0, stddev=1-k)
tf.summary.histogram('normal/shrinking_mean', shrinking_mean)

normal_combined = tf.concat([moving_mean, shrinking_mean], axis=0)
tf.summary.histogram('normal/normal_combined', normal_combined)

gamma = tf.random_gamma(shape=[1000], alpha=k)
tf.summary.histogram('other/gamma', gamma)

poisson = tf.random_poisson(lam=k, shape=[1000])
tf.summary.histogram('other/poisson', poisson)

uniform = tf.random_uniform(shape=[1000], minval=k*10)
tf.summary.histogram('other/uniform', uniform)

all_combined = tf.concat([moving_mean, shrinking_mean, gamma, poisson, uniform], axis=0)
tf.summary.histogram('all_combined', all_combined)

summaries = tf.summary.merge_all()

sess = tf.Session()
writer = tf.summary.FileWriter(log_path)
for step in range(N):
    val = step/float(N)
    merge_op = sess.run(summaries, feed_dict={k:val})
    writer.add_summary(summary=merge_op, global_step=step)
writer.close()

python main.py

xdg-open 'http://localhost:6006/#histograms'
tensorboard --logdir=./