# 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:

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