用 TensorBoard 的好處就是不用在寫 printout 惹～

tensorboard_concept_example.py

x = tf.placeholder(.....)

# Scope: 運算區塊
with tf.name_scope("operation_scope"):
    weight = ...
    l1 = op(x, w)
    ...
    ...
    tf.summary.histogram("weight", weight) # 可以看 weight 值的分佈，只是我還不清楚分佈是指什麼
    
# Cost
with tf.name_scope("cost"):
    loss = .....
    tf.summary.scalar("loss", loss) # 把 loss 的值存起來
    
# Training
with tf.name_scope("train"):
    train = tf.train.SGD(0.01).minimize(loss)

init = tf.global_variables_initializer()

sess = tf.Session()
sess.run(init)

file_writer = tf.summary.FileWriter('/path/to/log_dir', sess.graph)
merged = tf.summary.merge_all()

# Iteration: save a group of values each iteration
for _ in range(max_iter):
    fd = ...
    summary, __ = sess.run([merged, train], feed_dict = fd)
    file_writer.add_summary(summary, _)

    
# 在跑的時候，或跑完之後，只要 /path/to/log_dir 裡面有檔案，就可以在終端機下：
#     tensorboard --logdir=/path/to/log_dir

# 然後用瀏覽器開它顯示的網址就有介面了，通常是 http://localhost:6006