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# Python | Tensorflow acosh() method

• Last Updated : 10 Dec, 2018

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:

 `# 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

 `# Importing the Tensorflow library``import` `tensorflow as tf``  ` `# Importing the NumPy library``import` `numpy as np``  ` `# Importing the matplotlib.pylot 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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