tensorflow中的常量 變數和佔位符

部分內容**

先給乙個例項，

#先導入tensorflow

import tensorflow as tf
# create tensorflow object called hello_constant
hello_constant = tf.constant('hello world!')
with tf.session() as sess:
# run the tf.constant operation in the session
output = sess.run(hello_constant)
print(output)

# tensor1 是乙個0維的 int32 tensor

tensor1 = tf.constant(1234) 
# tensor2 是乙個1維的 int32 tensor
tensor2 = tf.constant([123,456,789]) 
# tensor3 是乙個二維的 int32 tensor
tensor3 = tf.constant([ [123,456,789], [222,333,444] ])

x = tf.placeholder(tf.string)

with tf.session() as sess:
output = sess.run(x, feed_dict=)

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=)

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.]]

，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))

valueerror: fetch argument 'const:0' shape=() dtype=int16> cannot be interpreted as

a tensor. (tensor tensor("const:0", shape=(), dtype=int16) is not
anelement
of this graph.)

佔位符

佔位符是定義乙個可變的常量，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=)
print(output)

test string

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