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.. _op_ai_onnx_CumSum-11:

CumSum - version 11
===================

This page documents version **11** of operator **CumSum**. See :doc:`CumSum` for the latest version (since version 14).

- **Domain**: ``ai.onnx``
- **Since version**: 11

Performs cumulative sum of the input elements along the given axis.
By default, it will do the sum inclusively meaning the first element is copied as is.
Through an ``exclusive`` attribute, this behavior can change to exclude the first element.
It can also perform summation in the opposite direction of the axis. For that, set ``reverse`` attribute to 1.

Example:

.. code-block::

    input_x = [1, 2, 3]
    axis=0
    output = [1, 3, 6]
    exclusive=1
    output = [0, 1, 3]
    exclusive=0
    reverse=1
    output = [6, 5, 3]
    exclusive=1
    reverse=1
    output = [5, 3, 0]


**Inputs**

- **x** (*T*): An input tensor that is to be processed.
- **axis** (*T2*): A 0-D tensor. Must be in the range [-rank(x), rank(x)-1]. Negative value means counting dimensions from the back.

**Outputs**

- **y** (*T*): Output tensor of the same type as 'x' with cumulative sums of the x's elements

**Attributes**

- **exclusive** (*int*): If set to 1 will return exclusive sum in which the top element is not included. In other terms, if set to 1, the j-th output element would be the sum of the first (j-1) elements. Otherwise, it would be the sum of the first j elements.
- **reverse** (*int*): If set to 1 will perform the sums in reverse direction.

**Type Constraints**

- **T**: Input can be of any tensor type.
  Allowed types: tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64).
- **T2**: axis tensor can be int32 or int64 only
  Allowed types: tensor(int32), tensor(int64).