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 libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([ [-5, -7],[ 2, 0]], dtype=tf.float64)# Printing the input tensorprint('a: ', a)# Calculating resultres = tf.math.special.dawsn(a)# Printing the resultprint('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 libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([1, 2, 3, 4, 5], dtype=tf.float64)# Printing the input tensorprint('a: ', a)# Calculating resultres = tf.math.special.dawsn(a)# Printing the resultprint('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)
