#coding=utf-8
import tensorflow as tf
with tf.name_scope("Scope_A"):
a = tf.add(1, 2, name = "A_add")
b = tf.mul(a, 3, name = "A_mul")
with tf.name_scope("Scope_B"):
c = tf.add(4, 5, name = "B_add")
d = tf.mul(c, 6, name = "B_mul")
e = tf.add(b, d, name = "output")
writer = tf.train.SummaryWriter('./name_scope_1', graph = tf.get_default_graph())
writer.close()
tensorboard --logdir='./name_scope_1'
image.png
#coding=utf-8
import tensorflow as tf
graph = tf.Graph()
with graph.as_default():
in_1 = tf.placeholder(tf.float32, shape = [], name = "input_a")
in_2 = tf.placeholder(tf.float32, shape = [], name = "input_b")
const = tf.constant(3, dtype = tf.float32, name = "static_value")
with tf.name_scope("Transformation"):
with tf.name_scope("A"):
A_mul = tf.mul(in_1, const)
A_out = tf.sub(A_mul, in_1)
with tf.name_scope("B"):
B_mul = tf.mul(in_2, const)
B_out = tf.sub(B_mul, in_2)
with tf.name_scope("C"):
C_div = tf.div(A_out, B_out)
C_out = tf.add(C_div, const)
with tf.name_scope("D"):
D_div = tf.div(B_out, A_out)
D_out = tf.add(D_div, const)
out = tf.maximum(C_out, D_out)
writer = tf.train.SummaryWriter('./name_scope_2', graph = graph)
writer.close()
image.png
