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.Tensor.gather_nd

Tensor.gather_nd(indices)

Gathers slices from a input tensor by indices. Using given indices to gather slices from a input tensor with a specified shape. input tensor’s shape is $(N,\ast )$ where $\ast$ means any number of additional dimensions. For convenience define it as input_x, the variable input_x refers to input tensor. indices is an K-dimensional integer tensor. Suppose that it is a (K-1)-dimensional tensor and each element of it defines a slice of input tensor:

$$output[(i_0,...,i_{K-2})]=input\mathrm{\_}x[indices[(i_0,...,i_{K-2})]]$$

The last dimension of indices can not more than the rank of input tensor: $indices.shape[-1]<=input\mathrm{\_}x.rank$.

Parameters

indices (Tensor) – The index tensor that gets the collected elements, with int32 or int64 data type.

Returns

Tensor, has the same type as input tensor and the shape is $indices\mathrm{\_}shape[:-1]+input\mathrm{\_}x\mathrm{\_}shape[indices\mathrm{\_}shape[-1]:]$.

Raises

ValueError – If length of shape of input tensor is less than the last dimension of indices.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)
>>> indices = Tensor(np.array([[0, 0], [1, 1]]), mindspore.int32)
>>> output = input_x.gather_nd(indices)
>>> print(output)
[-0.1  0.5]