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# Python – tensorflow.math.count_nonzero()

• Last Updated : 21 Jul, 2021

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

count_nonzero() is used to count the number of non zero elements in a Tensor.

Syntax: tf.math.count_nonzero(  input, axis, keepdim, dtype, name)

Parameters:

• input: It’s a Tensor that need to be reduced.
• axis(optional): It defines the axis along which input need to be reduced. Allowed range for this is  [-rank(input), rank(input)). If no value is given then default is none i.e. input will be reduced along all axis.
• keepdim(optional): If it is true, it will retain the reduced dimensions with length 1.
• dtype(optional): It defines the output dtype. Default if int32.
• name(optional): It defines the name for the operation.

Returns:

It returns a tensor that contains the number of non-zero values.

Example 1:

## Python3

 `# importing the library``import` `tensorflow as tf` `# initializing the input``a ``=` `tf.constant([``1``,``0``,``2``,``5``,``0``], dtype ``=` `tf.int32)  ``# 3 non-zero` `# Printing the input``print``(``"Input: "``,a)` `# Counting non-zero``res  ``=` `tf.math.count_nonzero(a)` `# Printing the result``print``(``"No of non-zero elements: "``,res)`

Output:

```Input:  tf.Tensor([1 0 2 5 0], shape=(5,), dtype=int32)
No of non-zero elements:  tf.Tensor(3, shape=(), dtype=int64)```

Example 2: When input tensor is of type string, “” is considered as empty string. ” ” is non zero.

## Python3

 `# importing the library``import` `tensorflow as tf` `# initializing the input``a ``=` `tf.constant(["``","` `","``a``","``b"])  ``# 3 non-zero` `# Printing the input``print``(``"Input: "``,a)` `# Counting non-zero``res  ``=` `tf.math.count_nonzero(a)` `# Printing the result``print``(``"No of non-zero elements: "``,res)`

Output:

```Input:  tf.Tensor([b'' b' ' b'a' b'b'], shape=(4,), dtype=string)
No of non-zero elements:  tf.Tensor(3, shape=(), dtype=int64)```

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