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
# 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
Python3
# 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:
