tfp.experimental.substrates.numpy.stats.count_integers

Counts the number of occurrences of each value in an integer array arr.

Works like 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].

If minlength and maxlength are not given, K = tf.reduce_max(arr) + 1 if arr is non-empty, and 0 otherwise. If weights are non-None, then index i of the output stores the sum of the value in weights at each index where the corresponding value in arr is i.

arr An int32 Tensor of 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 arr that are equal or greater than maxlength, ensuring that the output has length at most maxlength.
axis A 0-D or 1-D int32 Tensor (with static values) designating dimensions in arr to reduce over. Default value: None, meaning reduce over all dimensions.
dtype If weights is 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 values.