TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks. nextafter() is used to find element wisenext representable value of x1 in the direction of x2.
Syntax: tf.math.nextafter(x1, x2, name)
Parameter:
- x1: It’s the input tensor. Allowed dtype for this tensor are float64, float32.
- x2: It’s the input tensor of same dtype as x1.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor of dtype as x1.
Example 1:
Python3
# Importing the libraryimport tensorflow as tf# Initializing the input tensorx1 = tf.constant([1, 2, -3, -4], dtype = tf.float64)x2 = tf.constant([5, -7, 3, -8], dtype = tf.float64)# Printing the input tensorprint('x1: ', x1)print('x2: ', x2)# Calculating resultres = tf.math.nextafter(x1, x2)# Printing the resultprint('Result: ', res) |
Output:
x1: tf.Tensor([ 1. 2. -3. -4.], shape=(4, ), dtype=float64) x2: tf.Tensor([ 5. -7. 3. -8.], shape=(4, ), dtype=float64) Result: tf.Tensor([ 1. 2. -3. -4.], shape=(4, ), dtype=float64)
Example 2: This example uses different dtype for x1 and x2. It will raise InvalidArgumentError.
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensorx1 = tf.constant([1, 2, -3, -4], dtype = tf.float64)x2 = tf.constant([5, -7, 3, -8], dtype = tf.float32)# Printing the input tensorprint('x1: ', x1)print('x2: ', x2)# Calculating resultres = tf.math.nextafter(x1, x2)# Printing the resultprint('Result: ', res) |
Output:
x1: tf.Tensor([ 1. 2. -3. -4.], shape=(4, ), dtype=float64)
x2: tf.Tensor([ 5. -7. 3. -8.], shape=(4, ), dtype=float32)
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
in ()
8
9 # Calculating result
---> 10 res = tf.math.nextafter(x1, x2)
11
12 # Printing the result
2 frames
/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: cannot compute NextAfter as input #1(zero-based) was expected to be a double tensor but is a float tensor [Op:NextAfter]
