# Python | Tensorflow sinh() method

• Last Updated : 09 Nov, 2021

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.

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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]``` My Personal Notes arrow_drop_up