Python | Tensorflow sinh() method
Tensorflow is an open-source machine learning library developed by Google. One of its applications is to develop deep neural networks.
The module tensorflow.math
provides support for many basic mathematical operations. Function tf.sinh()
[alias tf.math.sinh
] provides support for the hyperbolic sine function in Tensorflow. It expects the input in radian form. The input type is tensor and if the input contains more than one element, element-wise hyperbolic sine is computed.
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:
Python3
# Importing the Tensorflow library import tensorflow as tf # A 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 sinh function and # storing the result in 'b' 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)) |
Output:
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: Visualization
Python3
# Importing the Tensorflow library import tensorflow as tf # Importing the NumPy library import numpy as np # Importing the matplotlib.pyplot function import matplotlib.pyplot as plt # A vector of size 15 with values from -5 to 5 a = np.linspace( - 5 , 5 , 15 ) # Applying the hyperbolic sine function and # storing the result in 'b' 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() |
Output:
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]
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