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# Python | Tensorflow tan() method

• Last Updated : 07 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.tan()` [alias `tf.math.tan`] provides support for the tangent 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 tangent is computed.

Syntax: tf.tan(x, name=None) or tf.math.tan(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 tan function and``# storing the result in 'b'``b ``=` `tf.tan(a, name ``=``'tan'``)`` ` `# 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("tan:0", shape=(6, ), dtype=float32)
Output: [ 1.5574077 -0.5463025  0.264317   1.7098469  0.        -0.2202772]
```

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 1``a ``=` `np.linspace(``-``1``, ``1``, ``15``)`` ` `# Applying the tangent function and``# storing the result in 'b'``b ``=` `tf.tan(a, name ``=``'tan'``)`` ` `# 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.tan"``) ``    ``plt.xlabel(``"X"``) ``    ``plt.ylabel(``"Y"``) `` ` `    ``plt.show()`

Output:

```Input: [-1.         -0.85714286 -0.71428571 -0.57142857 -0.42857143 -0.28571429
-0.14285714  0.          0.14285714  0.28571429  0.42857143  0.57142857
0.71428571  0.85714286  1.        ]
Output: [-1.55740772 -1.15486601 -0.86700822 -0.64298589 -0.45689311 -0.29375136
-0.14383696  0.          0.14383696  0.29375136  0.45689311  0.64298589
0.86700822  1.15486601  1.55740772]
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