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# Python – tensorflow.math.igamma()

• Last Updated : 18 Jan, 2022

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

igamma() is used to Compute the lower regularized incomplete Gamma function P(a, x). P(a, x) is defined as:

where gamma(a, x) is the lower incomplete Gamma function and is defined as:

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

Parameters:

• x: It is a tensor. Allowed dtypes are float32, float64.
• y: It is a tensor of same dtype as x.
• name(optional): It defines the name of the operation

Returns: It returns a tensor of dtype as x.

Example 1:

## Python3

 # importing the library import tensorflow as tf   # Initializing the input tensor a = tf.constant([7, 8, 13, 11], dtype = tf.float64) b = tf.constant([2, 8, 14, 5],  dtype = tf.float64)   # Printing the input tensor print('a: ', a) print('b: ', b)   # Calculating the result res = tf.math.igamma(a, b)   # Printing the result print('Result: ', res)

Output:

a:  tf.Tensor([ 7.  8. 13. 11.], shape=(4, ), dtype=float64)
b:  tf.Tensor([ 2.  8. 14.  5.], shape=(4, ), dtype=float64)
Result:  tf.Tensor([0.00453381 0.54703919 0.64154158 0.01369527], shape=(4, ), dtype=float64)

Example 2:

## Python3

 # Importing the library import tensorflow as tf   # Initializing the input tensor a = tf.constant([2, 8, 14, 5], dtype = tf.float32) b = tf.constant([7, 8, 13, 11],  dtype = tf.float32)   # Printing the input tensor print('a: ', a) print('b: ', b)   # Calculating the result res = tf.math.igamma(a, b)   # Printing the result print('Result: ', res)

Output:

a:  tf.Tensor([ 2.  8. 14.  5.], shape=(4, ), dtype=float32)
b:  tf.Tensor([ 7.  8. 13. 11.], shape=(4, ), dtype=float32)
Result:  tf.Tensor([0.9927049  0.5470391  0.42695415 0.9848954 ], shape=(4, ), dtype=float32)

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