TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. bessel_i0e() is function present in tensorflow math module. This function is used to find element wise exponentially scaled modified 0 order Bessel function.
bessel_i0e(x) = exp(-abs(x)) bessel_i0(x) bessel_i0e(x) is faster and numerically stabler than bessel_i0(x).
Syntax: tensorflow.math.bessel_i0e( x, name)
Parameters:
- x: It’s a tensor and the allowed dtypes for this tensor are bfloat16, half, float32, float64.
- name: It is an optional argument which is used to give operation name.
Returns: It returns a tensor or sparse tensor depending upon x of same dtype as x.
Example 1:
Python3
# importing the library import tensorflow as tf
# initializing the input a = tf.constant([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64)
# printing the input print ( 'a: ' ,a)
# evaluating the result r = tf.math.bessel_i0e(a)
# printing the result print ( "Result: " ,r)
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Output:
a: tf.Tensor([1. 2. 3. 4. 5.], shape=(5,), dtype=float64) Result: tf.Tensor([0.46575961 0.30850832 0.24300035 0.20700192 0.18354081], shape=(5,), dtype=float64)
Example 2: Visualization
Python3
# importing the library import tensorflow as tf
import matplotlib.pyplot as plt
# initializing the input a = tf.constant([ 1 , 2 , 3 , 4 , 5 ], dtype = tf.float64)
# evaluating the result r = tf.math.bessel_i0e(a)
#plotting the graph plt.plot(a, r, color = 'green' , marker = "o" )
plt.title( "tensorflow.math.bessel_i0e" )
plt.xlabel( "Input" )
plt.ylabel( "Result" )
plt.show() |
Output:
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