Python - tensorflow.math.digamma()

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:

# importing the library
import tensorflow as tf

# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)

# Printing the input tensor
print('Input: ', a)

# Calculating digamma
res = tf.math.digamma(x = a)

# Printing the result
print('Result: ', res)

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

# importing the library
import tensorflow as tf
import matplotlib.pyplot as plt

# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)

# Calculating digamma
res = tf.math.digamma(x = a)

# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.digamma')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()

Output: