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/TensorFlow Python

# tf.count_nonzero

```tf.count_nonzero(
input_tensor,
axis=None,
keepdims=None,
dtype=tf.int64,
name=None,
reduction_indices=None,
keep_dims=None
)
```

Defined in `tensorflow/python/ops/math_ops.py`.

See the guide: Math > Reduction

Computes number of nonzero elements across dimensions of a tensor. (deprecated arguments)

SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead

Reduces `input_tensor` along the dimensions given in `axis`. Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in `axis`. If `keepdims` is true, the reduced dimensions are retained with length 1.

If `axis` has no entries, all dimensions are reduced, and a tensor with a single element is returned.

NOTE Floating point comparison to zero is done by exact floating point equality check. Small values are not rounded to zero for purposes of the nonzero check.

For example:

```x = tf.constant([[0, 1, 0], [1, 1, 0]])
tf.count_nonzero(x)  # 3
tf.count_nonzero(x, 0)  # [1, 2, 0]
tf.count_nonzero(x, 1)  # [1, 2]
tf.count_nonzero(x, 1, keepdims=True)  # [, ]
tf.count_nonzero(x, [0, 1])  # 3
```

#### Args:

• `input_tensor`: The tensor to reduce. Should be of numeric type, or `bool`.
• `axis`: The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))`.
• `keepdims`: If true, retains reduced dimensions with length 1.
• `dtype`: The output dtype; defaults to `tf.int64`.
• `name`: A name for the operation (optional).
• `reduction_indices`: The old (deprecated) name for axis.
• `keep_dims`: Deprecated alias for `keepdims`.

#### Returns:

The reduced tensor (number of nonzero values).

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/count_nonzero