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.

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.unsorted_segment_max

mindspore.ops.unsorted_segment_max(x, segment_ids, num_segments)

Computes the maximum along segments of a tensor.

The following figure shows the calculation process of unsorted_segment_max:

$${\text{ output }}_i={\text{max}}_{j\dots }\text{ data }[j\dots ]$$

where $max$ over tuples $j...$ such that $segment\mathrm{\_}ids[j...]==i$.

Note

• If the segment_id i is absent in the segment_ids, then output[i] will be filled with the minimum value of the x's type.

• The segment_ids must be non-negative tensor.

Parameters

• x (Tensor) – The shape is $(x_1,x_2,...,x_R)$. With float16, float32 or int32 data type.

• segment_ids (Tensor) – TThe label indicates the segment to which each element belongs. Set the shape as $(x_1,x_2,...,x_N)$, where 0 < N <= R.

• num_segments (Union[int, Tensor], optional) – Set $z$ as num_segments, it can be an int or 0-D Tensor.

Returns

Tensor, the shape is $(z,x_{N+1},...,x_R)$.

Raises

TypeError – If num_segments is not an int.

Supported Platforms:

Ascend GPU CPU

Examples

>>> from mindspore import Tensor
>>> from mindspore import ops
>>> import numpy as np
>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [4, 2, 1]]).astype(np.float32))
>>> segment_ids = Tensor(np.array([0, 1, 1]).astype(np.int32))
>>> num_segments = 2
>>> output = ops.unsorted_segment_max(x, segment_ids, num_segments)
>>> print(output)
[[1. 2. 3.]
 [4. 5. 6.]]