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

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

# Library import Tensorflow import tensorflow as tf   # Constant vector of size 6 a = tf.constant ([ 1.0 , - 0.5 , 3.4 , 22.1 , 0.0 , - 6.5 ], dtype = tf.float32)   # Using the asinh function and # save the result to & # 39; b & # 39; b = tf.asinh (a, name = `asinh` )    # 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))

Output :

 Input type: Tensor ("Const_1: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4 22.1 0. -6.5] Return type: Tensor ("asinh: 0", shape = (6,) , dtype = float32) Output: [0.8813736 -0.48121184 1.9378793 3.7892363 0. -2.5708146] 

Code # 2: Rendering

# Tensorflow library import import tensorflow as tf   # Import NumPy library import numpy as np   # Import matplotlib.pylot function import matplotlib.pyplot as plt   # Vector size 15 with values ​​from -10 to 10 a = np.linspace ( - 10 , 10 , 15 )   # Apply inverse hyperbolic sine # function and save the result to & # 39; b & # 39; b = tf.asinh (a, name = ` asinh ` )    # 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.asinh" )  plt.xlabel ( " X " )  plt.ylabel ( "Y" )    plt.show ()

Exit:

 Input: [-10. -8.57142857 -7.14285714 -5.71428571 -4.28571429 -2.85714286 -1.42857143 0. 1.42857143 2.85714286 4.28571429 5.71428571 7.14285714 8.57142857 10.] Output: [-2.99822295 -2.84496713 -2.66412441 -2.44368627 -2.16177575 -1.77227614 -1.15447739 0. 1.15447739 1.77227614 2.16177575 2.44368627 2.66412441 2.84496713 2.99822295]