# Python – tensorflow.math.is_nan()

• Last Updated : 09 Jun, 2020

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

is_nan() returns true if element is NaN otherwise it returns false.

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

Parameters:

• x: It is a tensor. Allowed dtypes are bfloat16, half, float32, float64.
• name(optional): It defines the name of the operation

Returns: It returns a tensor of dtype bool.

Example 1:

## Python3

 `# importing the library ` `import` `tensorflow as tf ` `import` `numpy as np ` ` `  `# Initializing the input tensor ` `a ``=` `tf.constant([``7``, ``8``, ``13``, ``11``, np.inf], dtype ``=` `tf.float64) ` ` `  `# Printing the input tensor ` `print``(``'a: '``, a) ` ` `  `# Calculating the result ` `res ``=` `tf.math.is_nan(a) ` ` `  `# Printing the result ` `print``(``'Result: '``, res) `

Output:

```a:  tf.Tensor([ 7.  8. 13. 11. inf], shape=(5, ), dtype=float64)
Result:  tf.Tensor([False False False False  False], shape=(5, ), dtype=bool)

```

Example 2: This example uses numpy nan.

## Python3

 `# Importing the libraray ` `import` `tensorflow as tf ` `import` `numpy as np ` ` `  `# Initializing the input tensor ` `a ``=` `tf.constant([``7``, ``8``, ``13``, ``11``, np.nan], dtype ``=` `tf.float64) ` ` `  `# Printing the input tensor ` `print``(``'a: '``, a) ` ` `  `# Calculating the result ` `res ``=` `tf.math.is_nan(a) ` ` `  `# Printing the result ` `print``(``'Result: '``, res) `

Output:

```a:  tf.Tensor([ 7.  8. 13. 11. nan], shape=(5, ), dtype=float64)
Result:  tf.Tensor([False False False False True], shape=(5, ), dtype=bool)```

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