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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.

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Problem description

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

mindspore.scipy

Warning

These are experimental APIs that are subject to change or deletion. Only support Linux.

Scipy-like interfaces in mindspore.

mindspore.scipy.linalg

Linear algebra submodule

API Name

Description

Supported Platforms

mindspore.scipy.linalg.block_diag

Create a block diagonal matrix from provided arrays.

GPU CPU

mindspore.scipy.linalg.cho_factor

Compute the cholesky decomposition of a matrix, to use in mindspore.scipy.linalg.cho_solve().

GPU CPU

mindspore.scipy.linalg.cho_solve

Given the cholesky factorization of A, solve the linear equation.

GPU CPU

mindspore.scipy.linalg.cholesky

Compute the cholesky decomposition of a matrix.

GPU CPU

mindspore.scipy.linalg.eigh

Solve a standard or generalized eigenvalue problem for a complex Hermitian or real symmetric matrix.

GPU CPU

mindspore.scipy.linalg.inv

Compute the inverse of a matrix.

GPU CPU

mindspore.scipy.linalg.lstsq

Computes a solution to the least squares problem of a system of linear equations AX=B.

Ascend CPU

mindspore.scipy.linalg.lu

Compute pivoted LU decomposition of a general matrix.

GPU CPU

mindspore.scipy.linalg.lu_factor

Compute pivoted LU decomposition of a square matrix, and its outputs can be directly used as the inputs of lu_solve.

GPU CPU

mindspore.scipy.linalg.solve_triangular

Solve the linear system ax=b for x, Assuming a is a triangular matrix.

Ascend CPU

mindspore.scipy.optimize

Optimize submodule

API Name

Description

Supported Platforms

mindspore.scipy.optimize.line_search

Inexact line search that satisfies strong Wolfe conditions.

GPU CPU

mindspore.scipy.optimize.linear_sum_assignment

Solve the linear sum assignment problem.

Ascend CPU

mindspore.scipy.optimize.minimize

Minimization of scalar function of one or more variables.

GPU CPU