1
以下是一些tf.constant
顯示在tensorboard
中的工作代碼,有些不顯示。當'tf.constant`沒有顯示在'tensorboard'中時,令人困惑的情況是什麼?
但是,我不知道爲什麼這些不顯示。
誰能幫我在這裏?謝謝
import tensorflow as tf
import numpy as np
# tf.constant(value, dtype=None, shape=None,
# name='Const', verify_shape=False)
a = tf.constant([2, 2], name="a")
b = tf.constant([[0, 1], [2, 3]], name="b")
x = tf.add(a, b, name="add")
y = tf.multiply(a, b, name="mul")
# verify_shape=True, error if shape not match
# edge1 = tf.constant(2, dtype=None, shape=[2,2], name="wrong_shape", verify_shape=True)
# verify_shape=False, if shape not match, will add to match
edge2 = tf.constant(2, dtype=None, shape=[2,2], name="edge2", verify_shape=False)
# increase row by row, from left to right
edge3 = tf.constant([1,2,3,4], dtype=None, shape=[4,3], name="edge3", verify_shape=False)
# reassign works
edge2c = edge2
edge3c = edge3
edge4 = tf.constant(np.ones((2,2)), dtype=None, shape=None, name="shape22", verify_shape=False)
# increase row by row, from left to right
edge5 = tf.constant(np.ones((4,3)), dtype=None, shape=[4,3], name="shape43", verify_shape=False)
with tf.Session() as sess:
writer = tf.summary.FileWriter('./log/01_tf', sess.graph)
x, y = sess.run([x, y])
sess.run(edge4)
sess.run(edge5)
sess.run(edge2c)
sess.run(edge3c)
writer.close()
您不必重複使用'sess.run',實際上它將所有事件異步存儲到事件文件中。即使刪除所有'sess.run',該圖形也不會顯示任何差異。 –
謝謝!你是對的。 – Daniel