TensorFlow使用Graph的基本操作的实现

import tensorflow as tf
import numpy as np


c = tf.constant(1.5)
g = tf.Graph()

with g.as_default():

  c1 = tf.constant(2.0)
  print(c1.graph)
  print(g)
  print(c.graph)

g2 = tf.get_default_graph()
print(g2)

tf.reset_default_graph()
g3 = tf.get_default_graph()
print(g3)

import tensorflow as tf
import numpy as np

g = tf.Graph()

with g.as_default():
  c1 = tf.constant(2.5, name='c1_constant')
  c2 = tf.Variable(1.5, dtype=tf.float32, name='c2_constant')
  add = tf.multiply(c1, c2, name='op_add')

  c_1 = g.get_tensor_by_name(name='c1_constant:0')
  c_2 = g.get_tensor_by_name(name='c2_constant:0')
  c_3 = g.get_tensor_by_name(name='op_add:0')


  print(c_1)
  print(c_2)
  print(c_3)

import tensorflow as tf
import numpy as np

a = tf.constant([[1.0, 2.0]])
b = tf.constant([[1.0], [3.0]])

tensor_1 = tf.matmul(a, b, name='matmul_1')

with tf.Session() as sess:
  sess.run(tf.global_variables_initializer())
  t1 = tf.get_default_graph().get_operation_by_name(name='matmul_1')
  t2 = tf.get_default_graph().get_tensor_by_name(name='matmul_1:0')
  print(t1)
  print('t1: ', sess.run(t1))
  print('t2: ', sess.run(t2))