TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
polygamma() is used to compute polygamma function. Polygamma function is defined as:
This function is defined for only non-negative integer orders i.e. value of a should be non-negative.
Syntax: tensorflow.math.polygamma( a, x, name)
Parameters:
- a: It’s a tensor of non-negative values. Allowed dtypes are float32, float64.
- x: It’s a tensor of same dtype as a.
- name(optional): It defines the name for the operation.
Returns:
It returns a tensor of same dtype as a.
Example 1:
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([1, 2, 3], dtype = tf.float64)x = tf.constant([7, 9, 13], dtype = tf.float64)# Printing the input tensorprint('a: ', a)print('x: ', x)# Calculating resultres = tf.math.polygamma(a, x)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([1. 2. 3.], shape=(3, ), dtype=float64) x: tf.Tensor([ 7. 9. 13.], shape=(3, ), dtype=float64) Result: tf.Tensor([ 0.15354518 -0.01379332 0.00102074], shape=(3, ), dtype=float64)
Example 2: For negative value of a returned output is nan.
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([-1, 2, 3], dtype = tf.float64)x = tf.constant([7, 9, 13], dtype = tf.float64)# Printing the input tensorprint('a: ', a)print('x: ', x)# Calculating Resultres = tf.math.polygamma(a, x)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([-1. 2. 3.], shape=(3, ), dtype=float64) x: tf.Tensor([ 7. 9. 13.], shape=(3, ), dtype=float64) Result: tf.Tensor([ nan -0.01379332 0.00102074], shape=(3, ), dtype=float64)
