 # Python | Tensorflow sinh () method

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:

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``` # 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] `