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GB/T 46345-2025Artificial intelligence - Interface of deep learning compiler (English PDF)

人工智能　深度学习编译器接口

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Issued by

SAMR; SAC

Level / Type

National · Recommended

Issue date

October 5, 2025

Implementation date

October 5, 2025

Scope

GB/T 46345-2025 is the English-translated version of 人工智能　深度学习编译器接口.

GB/T 46345-2025 is the Chinese standard "Artificial intelligence - Interface of deep learning compiler". Its scope clause reads: This document specifies the graph generation module interface, graph transformation module interface, graph scheduling module interface, and domain-specific syntax of the deep learning compiler.

The requirements for the functions and input/output parameters of the language interface and operator generator interface are described, along with the corresponding testing methods.

This document applies to the design and implementation of deep learning compilers, and also provides a reference for the integration and application of deep learning compilers. Its clauses include terms and definitions.

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Document preview — GB/T 46345-2025

National Standard of the People's Republic of China

ICS: 35.240
Classification: L 70

Issued by: State Administration for Market Regulation; Standardization Administration of the PRC

Preface
1.Scope
2 Normative References
3.Terms and Definitions
4.Abbreviations
5.Overview
5.1 Technical Architecture
5.2 Technical Process
5.3 Interface Testing
6.Diagram generation module interface
6.1 Overview
6.2 Loading the computational graph
6.3 Calculation Graph Editing
7.Image conversion module interface 6.
7.1 Overview
7.2 Graph Optimization
7.3 Diagram Splitting
7.4 Descending Figure
8.Diagram scheduling module interface
8.1 Overview
8.2 Resource Management
8.3 Subgraph Scheduling
9 Domain-Specific Language Interfaces
10 Operator Generator Interface
Appendix A (Normative) Interface Testing Methods
Appendix B (Normative) Calculation Graph Editing Interface
Appendix C (Normative) DSL Basic Operation Interface
References

1 Scope

This document specifies the graph generation module interface, graph transformation module interface, graph scheduling module interface, and domain-specific syntax of the deep learning compiler.

The requirements for the functions and input/output parameters of the language interface and operator generator interface are described, along with the corresponding testing methods.

This document applies to the design and implementation of deep learning compilers, and also provides a reference for the integration and application of deep learning compilers.

2 Normative references

The contents of the following documents, through normative references within the text, constitute essential provisions of this document. Dated citations are not included.

For references to documents, only the version corresponding to that date applies to this document; for undated references, the latest version (including all amendments) applies.

This document.

GB/T 41867-2022 Terminology for Information Technology and Artificial Intelligence

3 Terms and Definitions

The terms and definitions defined in GB/T 41867-2022, as well as the following terms and definitions, apply to this document.

3.1 Deep learning

A method for creating rich hierarchical representations by training neural networks with many hidden layers.

Note. Deep learning is a subset of machine learning.

[Source. GB/T 41867-2022, 3.2.27]

3.2 Deep learning compiler

Tools for optimizing and compiling source code for deep learning models and domain-specific languages.

Note. Deep learning compilers convert deep learning models or domain-specific language source code into executable code for AI acceleration chips, enabling efficient...

Training and reasoning.

3.3

Integrated circuit components with a computing microarchitecture adapted to artificial intelligence algorithms, capable of performing computational processing for artificial intelligence applications.

[Source. GB/T 41867-2022, 3.1.5]

3.4

A form of encoding used by deep learning compilers in the process of converting source code into executable code.

Note. Intermediate representations are used during the conversion process to show the structure and semantic information of the program, so as to facilitate further optimization and code generation.

GB/T 47474 | GB/T 43195 | GB/T 43268 | GB/T 46347 | GB/T 46346 | […]

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This preview omits tables, figures, formulas and parts of the technical clauses. The complete document — 28 pages — is available in the English PDF.

Referenced standards

Normative references

GB/T 41867-2022Information technology—Artificial intelligence—Terminology

Editions of GB/T 46345

Edition	Title	Revision	Status
GB/T 46345-2025	Artificial intelligence - Interface of deep learning compiler	current edition	Current

This page sells the current edition, GB/T 46345-2025. Earlier editions are listed for reference only.

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