Document feedback

Question document fragment

When a question document fragment contains a formula, it is displayed as a space.

Submission type

issue

It's a little complicated...

I'd like to ask someone.

PR

Just a small problem.

I can fix it online!

Please select the submission type

Problem type

Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

- Low writing fluency that does not affect understanding.

- Incorrect version numbers, including software package names and version numbers on the UI.

Usability

- Usability:

- Incorrect or missing key steps.

- Missing main function descriptions, keyword explanation, necessary prerequisites, or precautions.

- Ambiguous descriptions, unclear reference, or contradictory context.

- Unclear logic, such as missing classifications, items, and steps.

Correctness

- Correctness:

- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

- Content Compliance:

- Contents that may violate applicable laws and regulations or geo-cultural context-sensitive words and expressions.

- Copyright infringement.

Please select the type of question

Problem description

Describe the bug so that we can quickly locate the problem.

Submit

Document feedback

mindspore.ops.CumSum

class mindspore.ops.CumSum(exclusive=False, reverse=False)

Computes the cumulative sum of input tensor along axis.

$$y_i=x_1+x_2+x_3+...+x_i$$

Parameters

• exclusive (bool, optional) – By default, this op performs an inclusive cumsum, which means that the first element of the input is identical to the first element of the output. Default: False .

• reverse (bool, optional) – If True , perform inverse cumulative sum. Default: False .

Inputs:

• input (Tensor) - The input Tensor with shape $(N,\ast )$ where $\ast$ means any number of additional dimensions.

• axis (int) - The axis to accumulate the tensor's value. Only constant value is allowed. Must be in the range [-rank(input), rank(input)).

Outputs:

Tensor, the shape of the output tensor is consistent with the input tensor's.

Raises

• TypeError – If exclusive or reverse is not a bool.

• TypeError – If axis is not an int.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[3, 4, 6, 10], [1, 6, 7, 9], [4, 3, 8, 7], [1, 3, 7, 9]]).astype(np.float32))
>>> cumsum = ops.CumSum()
>>> # case 1: along the axis 0
>>> y = cumsum(x, 0)
>>> print(y)
[[ 3.  4.  6. 10.]
 [ 4. 10. 13. 19.]
 [ 8. 13. 21. 26.]
 [ 9. 16. 28. 35.]]
>>> # case 2: along the axis 1
>>> y = cumsum(x, 1)
>>> print(y)
[[ 3.  7. 13. 23.]
 [ 1.  7. 14. 23.]
 [ 4.  7. 15. 22.]
 [ 1.  4. 11. 20.]]
>>> # Next demonstrate exclusive and reverse, along axis 1
>>> # case 3: exclusive = True
>>> cumsum = ops.CumSum(exclusive=True)
>>> y = cumsum(x, 1)
>>> print(y)
[[ 0.  3.  7. 13.]
 [ 0.  1.  7. 14.]
 [ 0.  4.  7. 15.]
 [ 0.  1.  4. 11.]]
>>> # case 4: reverse = True
>>> cumsum = ops.CumSum(reverse=True)
>>> y = cumsum(x, 1)
>>> print(y)
[[23. 20. 16. 10.]
 [23. 22. 16.  9.]
 [22. 18. 15.  7.]
 [20. 19. 16.  9.]]