In [1]:

    

import tensorflow as tf
import tensorflow as tf

a=tf.constant([2.33,3.0,3.5,4.0],shape=[1,4],name='x')
b=tf.constant([4.5,6.5,7.0,8.5],shape=[1,4],name='y')
with tf.name_scope("mean"):
    with tf.name_scope("mean_x_y"):
        x1=tf.reduce_mean(a)
        y1=tf.reduce_mean(b)
        sess=tf.Session()
    print("mean of a and b")    
    print(sess.run(x1))
    print(sess.run(y1))
    
with tf.name_scope("variance"):
    with tf.name_scope("scope_sub1"):
        x=tf.subtract(a,x1)
        sess1=tf.Session()
    print(sess1.run(x))
    with tf.name_scope("scope_sub2"):
        y=tf.subtract(b,y1)
        sess2=tf.Session()
    print(sess2.run(y))
    with tf.name_scope("scope_square"):
        a1=tf.multiply(x,x)
        sess3=tf.Session()
    print(sess3.run(a1))
    with tf.name_scope("scope_summation"):
        var=tf.reduce_sum(a1)
        sess4=tf.Session()
    print("variance")
    print(sess4.run(var))
    
with tf.name_scope("covariance"):
    with tf.name_scope("multiplication"):
        mul1=tf.multiply(a,b)
        sess5=tf.Session()
    print(sess5.run(mul1))
    with tf.name_scope("scope_summation2"):
        covar=tf.reduce_sum(mul1)
        sess6=tf.Session()
    print("covariance")
    print(sess6.run(covar))


    

    




mean of a and b
3.2075
6.625
[[-0.87750006 -0.20749998  0.29250002  0.79250002]]
[[-2.125 -0.125  0.375  1.875]]
[[ 0.77000636  0.04305624  0.08555626  0.62805629]]
variance
1.52668
[[ 10.48499966  19.5         24.5         34.        ]]
covariance
88.485

In [6]:

    

##(a-b)^2

import tensorflow as tf
v1=tf.constant(3)
v2=tf.constant(4)
with tf.name_scope("MyOperationGroup"):
    with tf.name_scope("Scope_A"):
        a = tf.multiply(v1,v1)
        b = tf.multiply(v2,v2)
with tf.name_scope("Scope_B"):
    c = tf.add(a, b, name="And_These_ones")
    d = tf.multiply(v1, v2, name="Multiply_these_numbers")

with tf.name_scope("Scope_C"):
    e = tf.multiply(2, d, name="B_add")

g = tf.subtract(c,e)


with tf.Session() as sess:
    writer = tf.summary.FileWriter("/tmp/tboard/output_la1", sess.graph)
    print(sess.run(g))
    writer.close()


    

    




1

In [9]:

    

import tensorflow as tf
v3=tf.constant(3)
v4=tf.constant(2)
with tf.name_scope("MyOperationGroup"):
    with tf.name_scope("Scope_A"):
        a = tf.multiply(v3,v3) 
        b = tf.multiply(v4,v4)   
with tf.name_scope("Scope_B"):
    c = tf.add(a, b, name="And_These_ones")
    d = tf.multiply(v3, v4, name="Multiply_these_numbers")

with tf.name_scope("Scope_C"):
    e=tf.subtract(c,d, name="subtrating")
    #e = tf.multiply(2, d, name="B_add")
    f=tf.add(v3,v4)
    
with tf.name_scope("Scope_D"):
    g = tf.multiply(f,e)


with tf.Session() as sess:
    writer = tf.summary.FileWriter("/tmp/tboard/output_la2", sess.graph)
    print(sess.run(g))
    writer.close()


    

    




35

In [ ]: