In [1]:

    

import tensorflow as tf
import numpy as np


    

In [2]:

    

node1 = tf.constant(3.0, tf.float32)
node2 = tf.constant(4.0)
print(node2, node2)


    

    




Tensor("Const_1:0", shape=(), dtype=float32) Tensor("Const_1:0", shape=(), dtype=float32)

In [4]:

    

sess = tf.Session()


    

In [6]:

    

print(sess.run([node1, node2]))


    

    




[3.0, 4.0]

In [7]:

    

node3 = tf.add(node1, node2)


    

In [15]:

    

print('node 3: ', node3, '\n', sess.run([node3]))


    

    




node 3:  Tensor("Add:0", shape=(), dtype=float32) 
 [7.0]

In [22]:

    

a = tf.placeholder(tf.float32)
b = tf.placeholder(tf.float32)
adder_node = tf.add(a,b)
sess.run(adder_node, {a:[3,2] ,b:[3,2]})


    

    
Out[22]:





array([ 6.,  4.], dtype=float32)

In [23]:

    

weight = tf.Variable(.3, tf.float32)
bias = tf.Variable(-.5, tf.float32)
input = tf.placeholder(tf.float32)


    

In [24]:

    

linear_model = input * weight + bias


    

In [27]:

    

init = tf.global_variables_initializer()


    

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