# Python | Tensorflow acosh() method

• Last Updated : 10 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.acosh() [alias tf.math.acosh] provides support for the inverse hyperbolic cosine function in Tensorflow. It expects the input in the range [1, ∞) and returns nan for any input outside this range. The input type is tensor and if the input contains more than one element, element-wise inverse hyperbolic cosine is computed.

Syntax: tf.acosh(x, name=None) or tf.math.acosh(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 acosh function and``# storing the result in 'b'``b ``=` `tf.acosh(a, name ``=``'acosh'``)`` ` `# 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:0", shape=(6, ), dtype=float32)
Input: [ 1.   0.5  3.4 -2.1  0.   6.5]
Return type: Tensor("acosh:0", shape=(6, ), dtype=float32)
Output: [0.            nan 1.894559      nan      nan 2.558979]```

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 1 to 10``a ``=` `np.linspace(``1``, ``10``, ``15``)`` ` `# Applying the inverse hyperbolic cosine``# function and storing the result in 'b'``b ``=` `tf.acosh(a, name ``=``'acosh'``)`` ` `# 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.acosh"``)``    ``plt.xlabel(``"X"``)``    ``plt.ylabel(``"Y"``)`` ` `    ``plt.show()`

Output:

```Input: [ 1.          1.64285714  2.28571429  2.92857143  3.57142857  4.21428571
4.85714286  5.5         6.14285714  6.78571429  7.42857143  8.07142857
8.71428571  9.35714286 10.        ]
Output: [0.         1.08055227 1.46812101 1.73714862 1.94591015 2.11724401
2.26282815 2.38952643 2.50174512 2.60249262 2.69391933 2.77761797
2.85480239 2.92641956 2.99322285]```

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