Python – tensorflow.math.digamma()
Last Updated :
08 Jun, 2020
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
digamma() is used to compute element wise derivative of Lgamma i.e. log of absolute value of Gamma(x).
Syntax: tensorflow.math.digamma( x, name)
Parameters:
- x: It’s the input tensor. Allowed dtypes are bfloat16, half, float32, float64.
- 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([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64)
print ( 'Input: ' , a)
res = tf.math.digamma(x = a)
print ( 'Result: ' , res)
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Output:
Input: tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result: tf.Tensor([-0.57721566 0.42278434 0.92278434 1.25611767 1.50611767], shape=(5, ), dtype=float64)
Example 2: Visualization
Python3
import tensorflow as tf
import matplotlib.pyplot as plt
a = tf.constant([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64)
res = tf.math.digamma(x = a)
plt.plot(a, res, color = 'green' )
plt.title( 'tensorflow.math.digamma' )
plt.xlabel( 'Input' )
plt.ylabel( 'Result' )
plt.show()
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Output:
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