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.. toctree:: :maxdepth: 1 :hidden: operation/op_custom_prim operation/op_custom_ascendc operation/op_custom_aot operation/op_custom_julia operation/op_custom_adv operation/op_customopbuilder operation/op_customopbuilder_function
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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