import tensorflow as tf

a = tf.constant(2, tf.int16)
b = tf.constant(4, tf.float32)

graph = tf.Graph()
with graph.as_default():
    a = tf.Variable(8, tf.float32)
    b = tf.Variable(tf.zeros([2, 2], tf.float32))

with tf.Session(graph=graph) as session:
    tf.global_variables_initializer().run()
    print(session.run
 
(a))
    print(session.run(b))

實驗結果：

8
[[ 0.  0.]
 [ 0.  0.]]

tensorflow在圖graph中定義了a,b兩個變數，在啟動graph時候，必須把變數載入到記憶體中（通過方法global_variables_initializer()）
，這樣才能在session中run(a),run(b)
session只能啟動graph=graph中的變數，如果變數不在graph中就會報錯。

import tensorflow as tf


graph = tf.Graph()
with graph.as_default():
    a = tf.Variable
 
(8, tf.float32)
    b = tf.Variable(tf.zeros([2, 2], tf.float32))
a = tf.constant(2, tf.int16)
b = tf.constant(4, tf.float32)
with tf.Session(graph=graph) as session:
    tf.global_variables_initializer().run()
    print(session.run(a))
    print(session.run(b))

報錯

ValueError: Fetch argument <tf.Tensor 'Const:0'
 
 shape=() dtype=int16> cannot be interpreted as a Tensor. (Tensor Tensor("Const:0", shape=(), dtype=int16) is not an element of this graph.)

變數必須初始化才會有具體的值global_variables_initializer()進行初始化，而常量就不用初始化。
佔位符
佔位符是定義一個可變的常量，佔位符賦值後不用初始化就可以獲取值。

import tensorflow as tf

x = tf.placeholder(tf.string)
y = tf.placeholder(tf.int32)
z = tf.placeholder(tf.float32)

with tf.Session() as sess:
    output = sess.run(x, feed_dict={x: 'Test String', y: 123, z: 45.67})
print(output)

實驗結果：

Test String