TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
erfinv() is used to compute element wise inverse error function.
Syntax: tensorflow.math.erfinv( 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 inverse error res = tf.math.erfinv(x = a) # Printing the result print ( 'Result: ' , res) |
Output:
Input: tf.Tensor([0.1 0.2 0.3 0.4 0.5], shape=(5, ), dtype=float64) Result: tf.Tensor([0.08885599 0.17914345 0.27246271 0.37080716 0.47693628], 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 inverse error res = tf.math.erfinv(x = a) # Plotting the graph plt.plot(a, res, color = 'green' ) plt.title( 'tensorflow.math.erfinv' ) plt.xlabel( 'Input' ) plt.ylabel( 'Result' ) plt.show() |
Output: