Python – tensorflow.math.erfc()

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

erfc() is used to compute element wise complementary Gauss error function.

Syntax: tensorflow.math.erfc(   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 complementary Gauss error
res = tf.math.erfc(x = a)

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

Output:

Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor(
[1.57299207e-01 4.67773498e-03 2.20904970e-05 1.54172579e-08
 1.53745979e-12], 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 complementary Gauss error
res = tf.math.erfc(x = a)

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

Output: