Python – tensorflow.math.divide_no_nan()
Last Updated :
24 Jun, 2020
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
import tensorflow as tf
a = tf.constant([ 6 , 8 , 12 , 15 ], dtype = tf.float64)
b = tf.constant([ 2 , 3 , 4 , 5 ], dtype = tf.float64)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.divide_no_nan(x = a, y = b)
print ( 'Result: ' , res)
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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
import tensorflow as tf
a = tf.constant([ 6 , 8 , 12 , 15 ], dtype = tf.float64)
b = tf.constant([ 2 , 3 , 4 , 0 ], dtype = tf.float64)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.divide_no_nan(x = a, y = b)
print ( 'Result: ' , res)
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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)
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