# Python | Tensorflow reciprocal() method

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.reciprocal()` [alias `tf.math.reciprocal`] provides support to calculate the reciprocal of input in Tensorflow. It expects the input in form of complex numbers as , floating point numbers and integers. The input type is tensor and if the input contains more than one element, an element-wise reciprocal is computed, .

Syntax: tf.reciprocal(x, name=None) or tf.math.reciprocal(x, name=None)

Parameters:
x: A Tensor of type bfloat16, half, float32, float64, int32, int64, complex64 or complex128.
name (optional): The name for the operation.

Return type: A Tensor with the same size and type as that of x.

Code #1:

 `# Importing the Tensorflow library ` `import` `tensorflow as tf ` ` `  `# A constant vector of size 6 ` `a ``=` `tf.constant([``-``0.5``, ``-``0.1``, ``0``, ``0.1``, ``0.5``, ``2``], dtype ``=` `tf.float32) ` ` `  `# Applying the reciprocal function and ` `# storing the result in 'b' ` `b ``=` `tf.reciprocal(a, name ``=``'reciprocal'``) ` ` `  `# 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: [-0.5 -0.1  0.   0.1  0.5  2. ]
Return type: Tensor("reciprocal:0", shape=(6, ), dtype=float32)
Output: [ -2.  -10.    inf  10.    2.    0.5]
```

denotes that the reciprocal approaches to infinity as the input approaches to zero.

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 ` ` `  `# Two vector each of size 20 with values from 0 to 10 ` `a ``=` `np.linspace(``0``, ``10``, ``20``) ` ` `  `# Applying the reciprocal function and ` `# storing the result in 'b' ` `b ``=` `tf.reciprocal(a, name ``=``'reciprocal'``) ` ` `  `# 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.reciprocal"``)  ` `    ``plt.xlabel(``"X"``)  ` `    ``plt.ylabel(``"Y"``)  ` `    ``plt.grid() ` ` `  `    ``plt.show() `

Output:

```Input: [ 0.          0.52631579  1.05263158  1.57894737  2.10526316  2.63157895
3.15789474  3.68421053  4.21052632  4.73684211  5.26315789  5.78947368
6.31578947  6.84210526  7.36842105  7.89473684  8.42105263  8.94736842
9.47368421 10.        ]
Output: [       inf 1.9        0.95       0.63333333 0.475      0.38
0.31666667 0.27142857 0.2375     0.21111111 0.19       0.17272727
0.15833333 0.14615385 0.13571429 0.12666667 0.11875    0.11176471
0.10555556 0.1       ]
```

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