Python | Tensorflow exp() method

Python – tensorflow.math.expm1()

Last Updated : 08 Jun, 2020

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

expm1() is used to compute element wise exp(x)-1.

Syntax: tensorflow.math.expm1( x, name)

Parameters:

x: It’s the input tensor. Allowed dtypes are bfloat16, half, float32, float64, complex64, complex128.

name(optional): It defines the 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([1, 2, 3, 4, 5], dtype = tf.float64) 
  
# Printing the input tensor 
print('Input: ', a) 
  
# Calculating result 
res = tf.math.expm1(x = a) 
  
# Printing the result 
print('Result: ', res) 

Output:

Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor([  1.71828183   6.3890561   19.08553692  53.59815003 147.4131591 ], shape=(5, ), dtype=float64)

Example 2: Visualization

Python3

# importing the library 
import tensorflow as tf 
import matplotlib.pyplot as plt 
  
# Initializing the input tensor 
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64) 
  
# Calculating result 
res = tf.math.expm1(x = a) 
  
# Plotting the graph 
plt.plot(a, res, color ='green') 
plt.title('tensorflow.math.expm1') 
plt.xlabel('Input') 
plt.ylabel('Result') 
plt.show() 

Output:

Python | Tensorflow exp() method

aman neekhara

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