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Custom Operators
=================

.. image:: https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.7.2/resource/_static/logo_source_en.svg
    :target: https://gitee.com/mindspore/docs/blob/r2.7.2/tutorials/source_en/custom_program/op_custom.rst
    :alt: View Source On Gitee

.. toctree::
   :maxdepth: 1
   :hidden:

operation/op_custom_prim
   operation/op_custom_ascendc
   operation/op_custom_aot
   operation/op_custom_adv
   operation/op_customopbuilder
   operation/cpp_api_for_custom_ops
   operation/op_customopbuilder_atb
   operation/op_customopbuilder_asdsip
   operation/op_customopbuilder_aclnn

When built-in operators cannot meet requirements during network development, you can use MindSpore's custom operator functionality to integrate your operators. Currently, MindSpore provides two approaches for integrating custom operators:

- `Custom Primitive-Based Custom Operators <https://www.mindspore.cn/tutorials/en/r2.7.2/custom_program/operation/op_custom_prim.html>`_
- `CustomOpBuilder-Based Custom Operators <https://www.mindspore.cn/tutorials/en/r2.7.2/custom_program/operation/op_customopbuilder.html>`_

.. list-table::
   :widths: 20 40 40
   :header-rows: 1

* - Interface Comparison
     - `Custom Primitive <https://www.mindspore.cn/tutorials/en/r2.7.2/custom_program/operation/op_custom_prim.html>`_
     - `CustomOpBuilder <https://www.mindspore.cn/tutorials/en/r2.7.2/custom_program/operation/op_customopbuilder.html>`_
   * - Supported Modes
     - Graph Mode and PyNative Mode
     - PyNative Mode
   * - Interface Functions
     - Provides a unified Custom Primitive that calls user interfaces at various stages of operator execution.
     - Compiles and loads custom operator modules online, which can be directly applied to networks.
   * - Advantages
     - Supports both Graph and PyNative mode , with operator scheduling and execution processes consistent with built-in operators, ensuring high performance.
     - Enables operator development based on C++ tensors, offering a more intuitive custom execution process.
   * - Disadvantages
     - Has more interface restrictions, and the operator execution process is not visible to users.
     - Involves multiple interfaces for operator development; currently lacks a concise and efficient C++ API, making the development of high-performance operators challenging.
   * - Feature Level
     - STABLE
     - BETA

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authored 2025-12-10 10:21 +08:00 . modify links 2.7.2

Custom Operators

View Source On Gitee

.. toctree::
   :maxdepth: 1
   :hidden:

   operation/op_custom_prim
   operation/op_custom_ascendc
   operation/op_custom_aot
   operation/op_custom_adv
   operation/op_customopbuilder
   operation/cpp_api_for_custom_ops
   operation/op_customopbuilder_atb
   operation/op_customopbuilder_asdsip
   operation/op_customopbuilder_aclnn

When built-in operators cannot meet requirements during network development, you can use MindSpore's custom operator functionality to integrate your operators. Currently, MindSpore provides two approaches for integrating custom operators:

Interface Comparison	Custom Primitive	CustomOpBuilder
Supported Modes	Graph Mode and PyNative Mode	PyNative Mode
Interface Functions	Provides a unified Custom Primitive that calls user interfaces at various stages of operator execution.	Compiles and loads custom operator modules online, which can be directly applied to networks.
Advantages	Supports both Graph and PyNative mode , with operator scheduling and execution processes consistent with built-in operators, ensuring high performance.	Enables operator development based on C++ tensors, offering a more intuitive custom execution process.
Disadvantages	Has more interface restrictions, and the operator execution process is not visible to users.	Involves multiple interfaces for operator development; currently lacks a concise and efficient C++ API, making the development of high-performance operators challenging.
Feature Level	STABLE	BETA

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