Python – tensorflow.math.zeta()
Last Updated :
06 Aug, 2021
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
zeta() is used to compute the Hurwitz zeta function. It is defined as:
Syntax: tensorflow.math.zeta( x, q, name)
Parameter:
- x: It’s a Tensor. Allowed dtypes are float32 and float64.
- q: It’s a Tensor of same dtype as x.
- name(optional): It defines the name for the operation.
Returns:
It returns a Tensor of same dtype as x.
Example 1:
Python3
import tensorflow as tf
a = tf.constant([ - 5 , - 7 , 2 , 0 , 7 ], dtype = tf.float64)
b = tf.constant([ 1 , 3 , 9 , 4 , 7 ], dtype = tf.float64)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.zeta(a, b)
print ( 'Result: ' , res)
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Output:
a: tf.Tensor([-5. -7. 2. 0. 7.], shape=(5, ), dtype=float64)
b: tf.Tensor([1. 3. 9. 4. 7.], shape=(5, ), dtype=float64)
Result: tf.Tensor(
[ nan nan 1.17512015e-01 nan
2.12260976e-06], shape=(5, ), dtype=float64)
Example 2:
Python3
import tensorflow as tf
a = tf.constant([ [ - 5 , - 7 ], [ 2 , 0 ]], dtype = tf.float64)
b = tf.constant([ [ 1 , 3 ], [ 9 , 4 ]], dtype = tf.float64)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.zeta(a, b)
print ( 'Result: ' , res)
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Output:
a: tf.Tensor(
[[-5. -7.]
[ 2. 0.]], shape=(2, 2), dtype=float64)
b: tf.Tensor(
[[1. 3.]
[9. 4.]], shape=(2, 2), dtype=float64)
Result: tf.Tensor(
[[ nan nan]
[0.11751201 nan]], shape=(2, 2), dtype=float64)
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