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 defines as exp(-x**2) times the integral of exp(t**2) from 0 to x, with the domain of definition all real numbers.
Sytnax: 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)
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