Function bincount_v1

tensorflow/python/ops/math_ops.py:3222–3250

Counts the number of occurrences of each value in an integer array. If `minlength` and `maxlength` are not given, returns a vector with length `tf.reduce_max(arr) + 1` if `arr` is non-empty, and length 0 otherwise. If `weights` are non-None, then index `i` of the output stores the sum of the

(arr,
                weights=None,
                minlength=None,
                maxlength=None,
                dtype=dtypes.int32)

@tf_export(v1=["math.bincount", "bincount"])
@deprecation.deprecated_endpoints("bincount")
def bincount_v1(arr,
                weights=None,
                minlength=None,
                maxlength=None,
                dtype=dtypes.int32):
  """Counts the number of occurrences of each value in an integer array.

  If `minlength` and `maxlength` are not given, returns a vector with length
  `tf.reduce_max(arr) + 1` if `arr` is non-empty, and length 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`.
    dtype: If `weights` is None, determines the type of the output bins.

  Returns:
    A vector with the same dtype as `weights` or the given `dtype`. The bin
    values.
  """
  return bincount(arr, weights, minlength, maxlength, dtype)


@tf_export("math.cumsum", "cumsum")