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tfp.stats.count_integers

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

tfp.stats.count_integers(
    arr,
    weights=None,
    minlength=None,
    maxlength=None,
    axis=None,
    dtype=tf.int32,
    name=None
)

Defined in python/stats/quantiles.py.

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.

Args:

  • 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).

Returns:

A vector with the same dtype as weights or the given dtype. The bin values.