1557results about "Program code adaption" patented technology

A system for creating functionality modules for deployment in a workflow for use in visual programming including a configuration server with a processing element operable to implement the functionality modules and workflow, at least one large language model, a customizable functionality module in a workflow including at least one interface defining one or more customizable properties, and wherein the workflow executes a first operational environment different from a second operational environment executed by the large language models.

The present application discloses an intelligent inspection system and method for a power distribution network. The intelligent inspection system for the power distribution network comprises: acquiring an inspection analysis model; converting a model parameter into a specific tensor form, to determine whether a network structure of the inspection analysis model matches a network structure supported by a target porting platform; if the two network structures match, on the basis of the network structure supported by the target porting platform, converting the tensor form of the inspection analysis model into a target tensor, and rewriting an inconsistent portion in an operator structure of the inspection analysis model, to complete recompiling of the inspection analysis model; if the two network structures do not match, performing tensor regeneration for a non-matching model parameter type of the inspection analysis model, and performing regeneration for a non-matching operator structure of the inspection analysis model, to complete recompiling of the inspection analysis model; and pushing the recompiled inspection analysis model to the target porting platform, causing the target porting platform to perform inspection analysis on the basis of an inspection task.

The invention discloses an operator migration method and device between hardware platforms and a migration model construction method. The migration method comprises the following steps: obtaining an operator code and a function label of an operator to be migrated; when the existing operator information of the target hardware platform does not contain the function label, obtaining first information of the target hardware platform and second information of the source hardware platform; training a large language model based on the first information and the second information, and taking the trained large language model as an operator automatic migration development model; generating an initial operator matched with the precision requirement of the target hardware platform based on the operator automatic migration development model and the operator code; analyzing the initial operator to obtain an operator precision difference; taking an initial operator corresponding to the operator precision difference passing verification as a target operator; and storing the target operator to a corresponding level of the target hardware platform. According to the method, automatic non-inductive migration of the model operator on different hardware platforms can be realized, and efficient and seamless adaptation with different platforms is realized.

This disclosure relates to method and system for facilitating legacy code transformation. The method includes receiving legacy code data and natural language document from one or more data sources. Each of the one or more data sources is one of an external data source or an internal data source. Further, the method includes generating a first natural language output based on the legacy code data through a first LLM, and a second natural language output based on the natural language document through a second LLM. Further, the method includes fine-tuning one of the first LLM or the second LLM based on the first natural language output and the second natural language output, through a third LLM. Further, the method includes generating a natural language specification document corresponding to the legacy code data based on the first natural language output and the second natural language output through the third LLM.

The invention provides a cross-frame code migration method and system, electronic equipment and a storage medium, and the code migration method comprises the steps: carrying out the frame-level conversion of a first frame code, and generating a target engineering skeleton adaptive to a second frame protocol; analyzing the construction configuration and the entry file, determining an entry point and a compiling rule of code migration, analyzing the first frame code through an abstract syntax tree, and generating a target code range list needing to be migrated; and according to the target code range list and the dependency item list, applying a preset conversion rule to the first framework code, and generating a second framework code adaptive to a second framework protocol. Through automatic framework-level conversion and dynamic rule adaptation, rapid migration from the first framework code to the second framework code is realized, a multi-terminal code library is unified, the manpower development cost is reduced, synchronous operation of business iteration and migration is supported, and the development efficiency is improved.

The invention relates to the technical field of integrated circuits, in particular to a processing system of a single-precision configurable matrix operation unit based on RISC-V instruction expansion, which comprises an RISC-V processor used for executing a software program and identifying a user-defined expansion instruction, and the RISC-V processor is connected with the single-precision configurable matrix operation unit through a user-defined coprocessor interface; the single-precision configurable matrix operation unit comprises an instruction response and decoding module and an instruction retirement and write-back module, and the instruction response and decoding module is used for receiving an instruction function code, source operation data and a destination register number and decoding the instruction function code; after decoding is completed, different execution units are selected according to a decoding result to send corresponding control signals; and after the execution unit completes the corresponding task, the instruction retirement and write-back module returns an execution result and a completion signal to the RISC-V processor, so that execution of a self-defined extension instruction is completed. According to the system, the matrix operation speed can be accelerated through bottom hardware under limited hardware resource consumption.

The invention provides a cross-hardware platform AI algorithm model automatic matching migration method and system based on low-code development, and the method comprises the steps: firstly receiving an AI algorithm model uploaded by a user, obtaining the information of a target hardware platform needing to be migrated, carrying out the optimization adjustment of the AI algorithm model according to the obtained information of the target hardware platform, and carrying out the automatic matching migration of the AI algorithm model. The optimization and adjustment process comprises the following steps: analyzing the AI algorithm model, selecting a corresponding model type according to the function of the algorithm model, carrying out parameter quantification, model conversion, model deployment and evaluation on the AI algorithm model according to the model type, classifying and downloading the converted model, and carrying out optimization and adjustment on the model. An optimized AI algorithm model is obtained; and finally, deploying the obtained AI algorithm model to a target hardware platform. According to the method, the defects of a traditional matching method can be overcome, the model performance and universality are improved, and a unified adaptive solution is provided for different hardware platforms.

Example implementations include a method, apparatus, and computer-readable medium configured for implementing a workflow using a large language model (LLM). A workflow automation application sends a first prompt to a large language model (LLM) to transform a first input data source in a first format to a second format. The workflow automation application sends a second prompt to the LLM to define multiple steps of a workflow starting on the data source in the second format. The workflow automation application sends a third prompt to the LLM to define execution of business logic for each step of the workflow. The workflow automation application receives, from the LLM, output data indicating that each step of the workflow has been executed.

The invention relates to the technical field of computing power resource sharing in a data center application environment, and discloses an enterprise computing power layout and intelligent decision mobile application system and an implementation method thereof. And real-time monitoring and dynamic scheduling of internal or cloud computing resources of an enterprise are realized. Historical data and real-time load are processed by using machine learning and an optimization algorithm, an optimal scheduling scheme is generated, and an alarm is automatically triggered when abnormality is detected, so that efficient utilization of enterprise resources is ensured. The method has the advantages of being high in real-time performance, intelligent, flexible in expansion, safe, reliable and the like, and the operation and maintenance efficiency and decision response speed of enterprises can be remarkably improved.

The invention discloses a Direct3D rendering model compatible method based on a dynamic template pool, which comprises the following steps: establishing three types of mapping tables between D3D and Vulkan when compiling DXVK, constructing resource metadata, and creating a core, extended and temporary three-level template pool according to the mapping tables after starting; when the D3D application creates resources, metadata is initialized, parameters are verified, physical memories are allocated and grouped, resource groups are pre-verified, a batch binding command is generated, memory binding is completed, and the metadata is updated; when a resource view is created, a template is matched from a template pool, a handle is generated after instantiation, a resource handle is associated, and a descriptor is bound; when a rendering state is set and a rendering instruction is executed, the rendering state and the rendering instruction are respectively converted into a Vulkan related state and a Vulkan related instruction through a mapping table, a handle is bound after a PSO cache is inquired, a command buffer area is submitted to a GPU queue to execute drawing, and compatible operation of the D3D application on a platform supporting a Vulkan operating system is realized under the condition that the GPU does not support VKKHRmaintence5 and VKKHRmaintence6 extension.

According to the cross-platform kernel adaptation method provided by the embodiment of the invention, by accurately understanding kernel interface semantics, establishing a flexible parameter conversion mechanism and ensuring stable operation of a system through an efficient scheduling strategy, and by introducing deep learning and natural language processing technologies, the accuracy of interface matching is improved, better cross-platform compatibility is realized, and the performance of the system is improved. Meanwhile, monitoring and exception handling during operation are enhanced, and the reliability and safety of the system are improved.

The invention provides a software package source code optimization method of a cross-instruction-set architecture. The method comprises the following steps: step 1, retrieving and collecting various architecture migration optimization cases; step 2, the verified optimization cases are accumulated through the optimization library; 3, collecting a software package source code with a poor migration effect in a project, and providing the software package source code to a big language model to generate an optimization suggestion of migration between an original architecture and a target architecture; 4, inputting the to-be-optimized software package source code and the optimization suggestion into the large language model to generate a candidate optimization code; 5, further evaluating and screening the candidate optimization codes; step 6, retrieving in the optimization library based on the semantic features of the current code to obtain an excellent instance; step 7, performing optimization again by using a large language model; and step 8, evaluating a construction speed increase rate and function consistency. According to the scheme, a double-stage task decomposition strategy is adopted, the semantic drift risk is effectively reduced, and the accuracy of instruction-level conflict repair is improved.

The invention relates to the technical field of computer software engineering and cross-platform development, in particular to a system for assisting in transplanting Android language to ArkTS (ArkTS) of the swan Mongolia, which comprises a code input module for acquiring Java and Kotlin double-language source codes, an analysis module for analyzing codes by using an improved grammar analysis algorithm, and a storage module for storing the codes. The translation module constructs an abstract syntax tree based on an analysis result and generates an attribute description array, and the generation module generates an ArkTS interface code according to the attribute description array; the distributed computing architecture realizes efficient task scheduling and processing, and the post-processing optimization module guarantees the code quality. Through multi-module cooperation, the probability-rule fusion algorithm, the type dynamic mapping and other technologies, code transplantation can be rapidly and accurately completed, the large project transplantation period is shortened from several weeks to several days, the manual correction cost is reduced, the code conversion accuracy and the system stability are improved, and the development of the wide-gap application ecology is powerfully promoted.

The invention relates to the technical field of electric digital data processing, and provides a secondary development code cross-product transplantation method and device, computer equipment and a medium. The method comprises the steps of loading a source project, screening a to-be-transplanted source code file, identifying an original API type, determining a mapping relation between the original API type and a target API type, and generating an adaptation layer code framework according to the mapping relation; copying the to-be-transplanted source code file into the target project; on the premise of keeping the project hierarchical structure of the source project, replacing the calling node of the original API type with the calling node of the adapter type, and replacing the namespace reference with the corresponding namespace in the target project to obtain a migrated source code file; and obtaining a secondary development project of the target project based on the second product API according to the adaptation layer code framework and the migrated source code file. According to the method and the device, the transplantation efficiency and accuracy of the transplantation of the cross-product secondary development codes are improved.

The invention discloses a multi-dimensional evaluation method for credential environment migration, and particularly relates to the field of evaluation. According to the method, an evaluation index system covering infrastructure, an application system, data resources and security compliance is constructed, and comprehensive scanning is realized through instruction set detection, binary analysis and equal security compliance inspection; dynamically calculating the weight by adopting an AHP-entropy weight hybrid model, and triggering weight rebalance based on the volatility; through combination of static scanning and a dynamic probe, the compatibility, performance and safety differences are quantitatively analyzed; and finally, generating a visual risk assessment report, integrating data of each stage to calculate a compatibility score, a performance loss rate and a security level, providing instruction level difference comparison, a performance flame graph and a vulnerability attack path interaction view, and outputting a migration suggestion comprising a priority reconstruction list, an NEON instruction optimization scheme and a staged reinforcement plan.

The present invention provides a software design method for intelligent vehicle-mounted terminal based on a microservice architecture, and belongs to the technical field of intelligent networked vehicles. Software system development is realized based on the framework of distributed microservices. In terms of software architecture, the single application integrated by the original intelligent vehicle-mounted terminal is divided into a group of small services, and the services are coordinated and cooperated with each other to provide ultimate value for the application layer and the terminal. Each service runs in its own independent process, and services communicate with each other using a lightweight communication mechanism. Each service is built around a specific business and can be independently deployed to a production environment, a production-like environment, etc. The distributed scenario development method based on the microservice architecture enables different service modules to be freely combined to form application scenarios, which is convenient for independent deployment, distributed management and code decoupling, and the applications can be updated and expanded independently, reducing the coupling of hardware platforms and improving software portability.

The invention provides a Java-to-ArkTS code conversion method and system based on a large model, and belongs to the field of computers.The Java-to-ArkTS code conversion method comprises the steps that S1, a Java project to be converted is comprehensively analyzed, the dependency relationship and semantic information between files are extracted, and a code knowledge graph is constructed; s2, determining a code conversion sequence based on the code knowledge graph, extracting context information and multi-modal semantic information of a to-be-converted code, and completing conversion from Java to TS codes in combination with a multi-agent cooperation mechanism; and S3, comparing and analyzing the TS code with an official ArkTS coding specification, identifying a violation code, and correcting and verifying the violation code through a plurality of intelligent agents to generate an ArkTS code which accords with the ArkTS grammar specification and is consistent in semantics. According to the method, the automatic migration from the Java project to the ArkTS project can be effectively supported, the project migration efficiency and the code quality are improved, and the manual intervention cost is reduced.

A system includes an application generating website building system (AGWBS) for converting a website to an application (app) which operates on a mobile device. The AGWBS includes at least one database storing at least one layout option for the app and BI (business information) for the website, where the BI includes at least use of settings and features by a designer of the website and of apps of the AGWBS from previous editing sessions and an app-editor to determine an editing mode for a designer of the app according to at least the use of settings and features and to provide at least one layout option from the at least one database for the app according to the editing mode and to receive modification to a designer selected layout.

The invention belongs to the technical field of software engineering, and particularly relates to a large language model automatic vulnerability patch migration method based on grammar and semantic enhancement. The method comprises the following steps: extracting semantic and grammatical signatures related to vulnerabilities from a patch function of an original branch, wherein the semantic and grammatical signatures comprise a signature before repair and a signature after repair; extracting a corresponding vulnerability function signature from the vulnerability function of the target vulnerability branch; generating a patch migration prompt by using the signature information; using an original-target patch function to finely adjust the data set and the large language model; generating an initial repair function through the fine-tuned large language model; detecting semantic anomaly, placeholder anomaly and grammar anomaly by adopting a heuristic check method; and iteratively optimizing the repair function according to a check result until conditions are met, and outputting a final repair function. The method can effectively improve the success rate of migration of the vulnerability patches among different code branches, reduce manual intervention and reduce security risks.

The invention relates to the technical field of software and hardware compatibility testing, in particular to a domestic software and hardware compatibility intelligent evaluation system and method, and the system comprises a compatibility analysis engine, a compatibility detection task execution engine, a software behavior analysis module, a fault positioning module, a knowledge graph module, a performance optimization suggestion module and a visual interface. The software behavior analysis module constructs a high-dimensional feature space of a software running state through deep learning, and extracts abnormal features based on a topological space mapping technology; the fault positioning module constructs a dynamic causal network based on a probability graph model, and identifies a root node through a chaos sensitivity analysis algorithm; the knowledge graph module constructs a software and hardware dependency relationship model and provides priori knowledge for fault location; and the performance optimization suggestion module generates an optimization scheme based on the root positioning result, so that the functions of automatically executing a compatibility test, accurately positioning the root of the compatibility problem and providing targeted optimization suggestions are realized, and the adaptation efficiency of domestic software and hardware is greatly improved.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and providing transformed code snippets using a large language model. In particular, the disclosed systems can determine a code snippet from a code, for instance, based on user selection of the code snippet. The disclosed system can analyze the code and / or the code snippet to generate a prompt comprising context. The context contains information about the functionality of the code. The disclosed systems further use a large language model to analyze the code snippet and the prompt comprising the context and generate transformed code. The disclosed systems may provide the transformed code snippet to one or more devices.

Techniques for complex code modification via chain of thought prompting are described. A modification service obtains code to be modified according to a modification goal, and can decompose the modification goal, via use of a database or a machine learning model, to identify a set of modification steps. The set of modification steps may be organized according to a chain of thoughts, tree of thoughts, or graph of thoughts. The modification service can execute the set of modification steps via use of a machine learning model to yield modified code, which can be returned to a user.

The invention provides an algorithm plug-in collaborative development method and system based on multi-version control, and relates to the technical field of software development, and the method comprises the following steps: creating a development task and distributing the development task to a plurality of development nodes, constructing a dependency graph and analyzing version conflicts, performing code review, and deploying and testing in test environments of different version underlying frameworks. The compatibility score is calculated through the support vector machine, the release version is determined, and the release information is synchronized, so that collaborative development of multiple development nodes is realized, dependency conflicts are recognized in advance, and the compatibility of the algorithm plug-in under a multi-version framework is ensured.

The invention belongs to the technical field of artificial intelligence and localization basic platforms, and discloses a local large language model operation framework transplantation and adaptation method based on a domestic DCU environment. According to the method provided by the invention, DCU-based local operation framework adaptation is realized, and the hardware selection range of a mainstream large language model operation framework is greatly expanded; through the model quantification and compression technology, the hardware of the local deployment large language model can be quickly applied to the field of natural language processing, and the competitiveness of the domestic hardware in the large language model application is improved.

The invention discloses an architecture system applied to embedded system development, and relates to the field of embedded system development, and the architecture system comprises an application layer which is used for executing business logic in an embedded system and managing the configuration of the embedded system, and the application layer is developed by adopting a Lua script; the hardware abstraction layer provides a unified hardware access interface; and the virtualization interface layer is used for providing a uniform interface for the application layer, so that the application layer can access the hardware resources of the hardware abstraction layer and call the system service in the embedded system. According to the method and the device, the problem that cross-platform transplantation is difficult due to the fact that a C language direct programming mode is adopted in an embedded system in the related technology is solved.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The embodiment of the invention provides a model conversion method, a related device and a medium. According to the method, a model conversion mirror image is deployed to a node where a target chip is located, and an original model is converted into a target model corresponding to the target chip through the model conversion mirror image. And then the original model before conversion and the target model after conversion are verified through the original model verification mirror image and the target model verification mirror image respectively, a conversion deviation value capable of judging the model conversion effect is obtained according to the first verification result and the second verification result, and automatic verification of the target model after conversion is achieved. And based on the verification result (conversion deviation value), constructing a mirror image for the target model meeting the requirement, and storing the mirror image in a mirror image warehouse for subsequent calling. The embodiment of the invention aims to ensure the availability of the converted model. The embodiment of the invention can be applied to scenes of computer vision, natural language processing, voice recognition, automatic driving, edge calculation and the like.

The invention relates to the technical field of deep learning, in particular to a PyTorch framework-based compatibility expansion system, which comprises a cross-framework model converter, a heterogeneous hardware abstraction layer, a hybrid computational graph execution engine, an intelligent distributed trainer and a self-adaptive optimizer, the cross-frame model converter converts input model formats of different frames into PyTorch executable formats, the heterogeneous hardware abstraction layer supports rear ends of various hardware and automatically selects an optimal calculation path, and the hybrid calculation graph execution engine fuses dynamic graph flexibility and static subgraph optimization and supports dynamic control function execution flow. An intelligent distributed trainer automatically selects a parallel scheme and is compatible with multi-protocol communication, a self-adaptive optimizer performs dynamic optimization based on hardware characteristics and a PyTorch tensor, a cross-frame model converter supports model conversion of multiple deep learning frames, the cost of migration among different frames by a user is reduced, and the universality of the PyTorch frame is improved.

The invention discloses an automatic generation method and system for an intelligent adaptation layer based on API change. The method comprises the steps that API change detection is conducted according to new and old version API interface definitions, adaptation codes are generated according to an API change detection result and compiled into a compatible adaptation layer library, and the compatible adaptation layer library is packaged into an installation package; in the installation stage, the new version target library and the compatible adaptation layer library are installed in a target directory; and loading the compatible adaptation layer library prior to the new-version target library in the running stage, taking over and processing the old-version API interface through the compatible adaptation layer library, and transferring the new-version API interface in the new-version target library. The invention aims to solve the compatibility problem caused by the API change of the software library, realize the automatic generation of the intelligent adaptation layer to ensure the seamless compatibility of the application program with different version libraries under the RPM and other software package management systems, and reduce the maintenance workload for solving the incompatibility problem caused by the API change.

The invention relates to the technical field of chip development, and discloses a transplanting method and device of a swan gap system, a storage medium and computer equipment, and the method comprises the steps: constructing a swan gap system to be transplanted based on a target chip, obtaining a corresponding source code, and then configuring a compiling configuration file in the source code, the compiling subsystem is used for establishing a compiling environment based on configuration information in the compiling configuration file, performing transplantation adaptation on a kernel layer in the compiling environment to generate a kernel mirror image, configuring the starting recovery subsystem, generating a root file system mirror image based on the file system configuration file, and starting the starting recovery subsystem. And finally burning the kernel mirror image and the root file system mirror image to a target chip, and performing function verification and test on the target chip. According to the method disclosed by the present invention, the swan-gap system transplantation including kernel layer transplantation, subsystem adaptation and root file system customization is designed and realized, so that the swan-gap system is successfully adapted to the target chip, and the accelerator equipment carrying the target chip can stably and reliably operate.