Python – tensorflow.math.divide_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.

divide_no_nan() is used to compute element wise safe division of x by y i.e it returns 0 if y is zero

Syntax: tensorflow.math.divide_no_nan( x, y, name)

Parameters:

x: It is a tensor.

y: It is a tensor.

name(optional): It defines the name of the operation

Returns: It returns a tensor.

Example 1:

Python3

# importing the library 
import tensorflow as tf 
  
# Initializing the input tensor 
a = tf.constant([6, 8, 12, 15], dtype = tf.float64) 
b = tf.constant([2, 3, 4, 5],  dtype = tf.float64) 
  
# Printing the input tensor 
print('a: ', a) 
print('b: ', b) 
  
# Calculating safe division 
res = tf.math.divide_no_nan(x = a, y = b) 
  
# Printing the result 
print('Result: ', res) 

Output:

a:  tf.Tensor([ 6.  8. 12. 15.], shape=(4, ), dtype=float64)
b:  tf.Tensor([2. 3. 4. 5.], shape=(4, ), dtype=float64)
Result:  tf.Tensor([3.         2.66666667 3.         3.        ], shape=(4, ), dtype=float64)

Example 2: In this example one of the value in second tensor is taken 0.

Python3

# importing the library 
import tensorflow as tf 
  
# Initializing the input tensor 
a = tf.constant([6, 8, 12, 15], dtype = tf.float64) 
b = tf.constant([2, 3, 4, 0],  dtype = tf.float64) 
  
# Printing the input tensor 
print('a: ', a) 
print('b: ', b) 
  
# Calculating safe division 
res = tf.math.divide_no_nan(x = a, y = b) 
  
# Printing the result 
print('Result: ', res) 

Output:

a:  tf.Tensor([ 6.  8. 12. 15.], shape=(4, ), dtype=float64)
b:  tf.Tensor([2. 3. 4. 0.], shape=(4, ), dtype=float64)
Result:  tf.Tensor([3.         2.66666667 3.                0], shape=(4, ), dtype=float64)