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Counts the number of occurrences of each value in an integer array
tfp.experimental.substrates.numpy.stats.count_integers( arr, weights=None, minlength=None, maxlength=None, axis=None, dtype=tf.int32, name=None )
tf.math.bincount, but provides an
axis kwarg that specifies
dimensions to reduce over. With
~axis = [i for i in range(arr.ndim) if i not in axis],
this function returns a
Tensor of shape
[K] + arr.shape[~axis].
maxlength are not given,
K = tf.reduce_max(arr) + 1
arr is non-empty, and 0 otherwise.
weights are non-None, then index
i of the output stores the sum of the
weights at each index where the corresponding value in
Tensorof non-negative values.
weights: If non-None, must be the same shape as arr. For each value in
arr, the bin will be incremented by the corresponding weight instead of 1.
minlength: If given, ensures the output has length at least
minlength, padding with zeros at the end if necessary.
maxlength: If given, skips values in
arrthat are equal or greater than
maxlength, ensuring that the output has length at most
Tensor(with static values) designating dimensions in
arrto reduce over.
None, meaning reduce over all dimensions.
weightsis None, determines the type of the output bins.
name: A name scope for the associated operations (optional).
A vector with the same dtype as
weights or the given
dtype. The bin