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Python – tensorflow.math.reciprocal_no_nan()

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TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning  neural networks. reciprocal_no_nan() is used to find element wise safe reciprocal of x i.e. if x is 0 it’s reciprocal is also 0.

Syntax: tf.math.reciprocal_no_nan(x, name)

Parameter:

  • x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, int32, int64, complex64, complex128.
  • name(optional): It defines the name for the operation.

Returns: It returns a tensor of dtype same as x.

Example 1: This example uses real tensor.

Python3




# Importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([0, 2, -3, -4], dtype = tf.float64)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reciprocal_no_nan(a)
 
# Printing the result
print('Result: ', res)


Output:

Input:  tf.Tensor([ 0.  2. -3. -4.], shape=(4, ), dtype=float64)
Result:  tf.Tensor([ 0.          0.5        -0.33333333 -0.25      ], shape=(4, ), dtype=float64)

Example 2: This example uses complex tensor.

Python3




# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([0 + 0j, 2-5j, -3 + 7j, -4-8j], dtype = tf.complex128)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reciprocal_no_nan( a)
 
# Printing the result
print('Result: ', res)


Output:

Input:  tf.Tensor([ 0.+0.j  2.-5.j -3.+7.j -4.-8.j], shape=(4, ), dtype=complex128)
Result:  tf.Tensor(
[ 0.        +0.j          0.06896552+0.17241379j -0.05172414-0.12068966j
 -0.05      +0.1j       ], shape=(4, ), dtype=complex128)


Last Updated : 15 Mar, 2023
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