  # Python | Tensorflow mutual flows method ()

NumPy | Python Methods and Functions

The `tensorflow.math ` module provides support for many basic mathematical operations. The ` tf.reciprocal () ` [alias ` tf.math.reciprocal `] provides support for calculating the reciprocal input amount in Tensorflow. Expected to be input as complex numbers in the form , floating point numbers and integers. Input type — tensor, and if the input contains more than one element, the inverse element is calculated, ,

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 `   ` # Constant vector of size 6 ` a ` = ` ` tf.constant ([` ` - ` ` 0.5 ` `, ` ` - ` ` 0.1 ` `, ` ` 0 ` `, ` ` 0.1 ` `, ` ` 0.5 ` `, ` ` 2 ` `], dtype ` ` = ` ` tf.float32) `   ` # Reverse function and ` ` # save result to & # 39; b & # 39; ` ` 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: Tens or ("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 inverse values ​​approach infinity when input approaching zero.

Code # 2: Rendering

 ` # Import Tensorflow library ` ` import ` ` tensorflow as tf `   ` # Importing the NumPy library ` ` import ` ` numpy as np ` ` `  ` # Import matplotlib.pylot `` import matplotlib.pyplot as plt    # Two vectors sized 20 with values ​​from 0 to 10 a = np.linspace ( 0 , 10 , 20 )    # Apply inverse function and # save result to & # 39; b & # 39; 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 0.475 0.38 0.63333333 0.31666667 0.27142857 0.21111111 0.19 0.2375 0.17272727 0.15833333 0.14615385 0.13571429 0.12666667 0.11176471 0.10555556 0.11875 0.1] 