Python | Tensorflow cos () method

Michael Zippo 18.07.2021

The tensorflow.math module provides support for many basic mathematical operations. The tf.cos () [alias tf.math.cos ] function provides support for the cosine function in Tensorflow. It expects input in radians, and output is in the range [-1, 1]. Input type — tensor, and if the input contains more than one element, the element-wise cosine is calculated.

Syntax : tf.cos (x, name = None) or tf.math.cos ( x, name = None)

Parameters :
x : A tensor of any of the following types: float16, float32, float64, complex64, or complex128.
name (optional): The name for the operation.

Return type : A tensor with the same type as that of x.

Code # 1:

       # Tensorflow library import  
   import   tensorflow as tf 
    
  # Constant vector of size 6  
   a   =   tf.constant ([  1.0  ,   -   0.5  ,   3.4  ,   -   2.1  ,   0.0  ,   -   6.5  ], dtype   =   tf.float32) 
   
  # Applying the sin function and  
  # saving the result to & # 39; b & # 39;  
   b   =   tf.cos (a, name   =   ’cos’  ) 
   
  # Initiated Tensorflow session host  
  with tf.Session () as sess: 
   print   (  ’Input type:’  , a) 
     print   (  ’Input:’  , sess.run (a)) 
   print   (  ’Return type: ’ , b) 
     print   (  ’Output:’  , sess.run (b))

Exit:

 Input type: Tensor ("Const_2: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4000001 -2.0999999 0. -6.5] Return type: Tensor ("cos: 0", shape = (6,), dtype = float32) Output: [0.54030228 0.87758255 -0.96679819 -0.50484604 1. 0.97658765]

Code # 2: Rendering

# Import Tensorflow library

import tensorflow as tf

# Importing the NumPy library

import numpy as np

# Import matplotlib.pylot function

import matplotlib.pyplot as plt

# Vector size 15 with values from -5 to 5

a = np.linspace ( - 5 , 5 , 15 )

# Using the sigmoid function and
# saving the result to & # 39; b & # 39;

b = tf.cos (a, name = ’cos’ )

# Initiating a Tensorflow session
with tf.Session () as sess:

print ( ’Inpu t: ’ , a)

print ( ’Output:’ , sess.run (b))

plt.plot (a, sess.run (b), color = ’red’ , marker = "o" )

plt.title ( "tensorflow.cos" )

plt.xlabel ( "X" )

plt.ylabel ( "Y" )

plt.show ()

Exit:

 Input: [-5. -4.28571429 -3.57142857 -2.85714286 -2.14285714 -1.42857143 -0.71428571 0. 0.71428571 1.42857143 2.14285714 2.85714286 3.57142857 4.28571429 5.] Output: [0.28366219 -0.41384591 -0.90903414 -0.9598162 -0.5413659 0.1417459 0.75556135 1. 0.75556135 0.1417459 -0.5413659 -0.9598162 -0.90903414 -0.41384591 0.28366219 ]