tensorflow.math.special.dawsn() function in Python

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

dawsn() function

dawsn() is used to compute element wise Dawson’s integral of x. It is defined as exp(-x**2) times the integral of exp(t**2) from 0 to x, with the domain of definition all real numbers.

Syntax: tensorflow.math.special.dawsn( x, name)

Parameter:

• x: It’s a Tensor or Sparse Tensor. Allowed dtypes are float32 and float64.
• name(optional): It defines 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([ [-5, -7],[ 2, 0]], dtype=tf.float64)

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

# Calculating result
res = tf.math.special.dawsn(a)

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

Output:

a:  tf.Tensor(
[[-5. -7.]
 [ 2.  0.]], shape=(2, 2), dtype=float64)
Result:  tf.Tensor(
[[-0.10213407 -0.07218097]
 [ 0.30134039  0.        ]], shape=(2, 2), dtype=float64)

Example 2:

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('a: ', a)

# Calculating result
res = tf.math.special.dawsn(a)

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

Output:

a:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5,), dtype=float64) 
Result:  tf.Tensor([0.53807951 0.30134039 0.17827103 0.129348   0.10213407], shape=(5,), dtype=float64)