# Python – tensorflow.math.sqrt()

• Last Updated : 16 Jun, 2020

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

sqrt() is used to compute element wise square root.

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

Parameters:

• x: It’s a tensor. Allowed dtypes are bfloat16, half, float32, float64, complex64, complex128.
• name(optional): It defines the name for the operation.

Returns: It returns a tensor.

Example 1:

## Python3

 `# importing the library``import` `tensorflow as tf`` ` `# Initializing the input tensor``a ``=` `tf.constant([ ``5``, ``7``, ``9``, ``15``], dtype ``=` `tf.float64)`` ` `# Printing the input tensor``print``(``'a: '``, a)`` ` `# Calculating result``res ``=` `tf.math.sqrt(a)`` ` `# Printing the result``print``(``'Result: '``, res)`

Output:

```a:  tf.Tensor([ 5.  7.  9. 15.], shape=(4, ), dtype=float64)
Result:  tf.Tensor([2.23606798 2.64575131 3.         3.87298335], shape=(4, ), dtype=float64)

```

Example 2: Visualization

## Python3

 `# import tensorflow as tf``import` `matplotlib.pyplot as plt`` ` `# Initializing the input tensor``a ``=` `tf.constant([ ``5``, ``7``, ``9``, ``15``], dtype ``=` `tf.float64)`` ` `# Calculating tangent``res ``=` `tf.math.sqrt(a)`` ` `# Plotting the graph``plt.plot(a, res, color ``=``'green'``)``plt.title(``'tensorflow.math.sqrt'``)``plt.xlabel(``'Input'``)``plt.ylabel(``'Result'``)``plt.show()`

Output:

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