TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks.
fresnel_spence() method
fresnel_spence() is used to compute element wise Spence’s integral of x. It is defines as the integral of log(t) / (1 – t) from 1 to x, with the domain of definition all positive real numbers.
Sytnax: tensorflow.math.special.spence( 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.spence(a) # Printing the result print('Result: ', res) |
Output:
a: tf.Tensor( [[-5. -7.] [ 2. 0.]], shape=(2, 2), dtype=float64) Result: tf.Tensor( [[ nan nan] [-0.82246703 1.64493407]], 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.spence(a) # Printing the result print('Result: ', res) |
Output:
a: tf.Tensor([1. 2. 3. 4. 5.], shape=(5,), dtype=float64)
Result: tf.Tensor([ 0. -0.82246703 -1.43674637 -1.93937542 -2.3699398 ], shape=(5,), dtype=float64)
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