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  2. Python | Tensorflow method ()

Python | Tensorflow method ()



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

Syntax : tf.cosh (x, name = None) or tf.math.cosh (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 Kosh function and
# saving the result to & # 39; b & # 39;

b = tf.cosh (a, name = `cosh` )

 
# 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_2: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4 -2.1 0. -6.5] Return type: Tensor ("cosh_1: 0", shape = (6,), dtype = float32) Output: [1.5430806 1.127626 14.998738 4.144313 1. 332.5716]

Code # 2: Rendering

# Tensorflow library import

import tensorflow as tf

 
# Import NumPy library

import numpy as np

  
# Import of the matplotlib.pylot function

import matplotlib.pyplot as plt

 
# Vector size 15 with values ​​from -1 to 1

a = np.linspace ( - 1 , 1 , 15 )

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

b = tf.cosh (a, name = `cosh` )

  
# 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.cosh" ) 

plt.xlabel ( " X " ) 

plt.ylabel ( < code class = "string"> "Y" ) 

 

plt.show ()

Output:

 Input: [-1. -0.85714286 -0.71428571 -0.57142857 -0.42857143 -0.28571429 -0.14285714 0. 0.14285714 0.28571429 0.42857143 0.57142857 0.71428571 0.85714286 1.] Output: [1.54308063 1.39039564 1.26613436 1.16775654 1.09325103 1.04109475 1.01022145 1. 1.01022145 1.04109475 1.09325103 1.16775654 1.26613436 1.39039564 1.54308063]