Python | Tensorflow sinh () method

Michael Zippo 18.07.2021

The tensorflow.math module provides support for many basic mathematical operations. The tf.sinh () [alias tf.math.sinh ] function provides support for the hyperbolic sine function in Tensorflow. Input in radians is expected. Input type — tensor, and if the input contains more than one element, the element-wise hyperbolic sine is calculated.

Syntax : tf.sinh (x, name = None) or tf.math.sinh (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) 
   
  # Usage sinh functions and  
  # save result to & # 39; b & # 39;  
   b   =   tf.sinh (a, name   =   ’sinh’  )  
   
  # Initiating a Tensorflow session  
  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_3: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4 -2.1 0. -6.5] Return type: Tensor ("sinh: 0", shape = (6,), dtype = float32) Output: [1.1752012 -0.5210953 14.965365 -4.0218563 0. -332.57004]

Code # 2: Rendering

# Import Tensorflow library

import tensorflow as tf

# Import NumPy library

import numpy as np

# Importing the matplotlib.pylot function

import matplotlib.pyplot as plt

# Vector size 15 with values from -5 to 5

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

# Applying the hyperbolic sine function and
# save the result to & # 39; b & # 39;

b = tf.sinh (a, name = ’ sinh’ )

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

print ( ’Input:’ , a)

     print   (  ’Output:’  , sess.run (b)) 
   plt.plot (a, sess.run (b), color   =   ’red’  , marker   =   "o"  ) 
   plt. title (  "tensorflow.sinh"  ) 
   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: [-74.20321058 -36.32033021 -17.76962587 -8.67713772 -4.20321865 -1.96654142 -0.77659271 0. 0.77659271 1.96654142 4.20321865 8.67713772 17.76962587 36.32033021 74.20321058]