tf.compat.v1.count_nonzero

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

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.math.count_nonzero

tf.compat.v1.count_nonzero(
    input_tensor=None,
    axis=None,
    keepdims=None,
    dtype=tf.dtypes.int64,
    name=None,
    reduction_indices=None,
    keep_dims=None,
    input=None
)

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

Note: Strings are compared against zero-length empty string "". Any string with a size greater than zero is already considered as nonzero.

For example:

x = tf.constant(["", "a", "  ", "b", ""])
tf.math.count_nonzero(x) # 3, with "a", "  ", and "b" as nonzero strings.

Args
input_tensor	The tensor to reduce. Should be of numeric type, bool, or string.
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.
input	Overrides input_tensor. For compatibility.

Returns
The reduced tensor (number of nonzero values).