tf.compat.v1.count_nonzero  |  TensorFlow v2.16.1 (original) (raw)

tf.compat.v1.count_nonzero

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

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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.

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

For example:

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