25 results about "YAML" patented technology

The application provides a method for optimizing a target detection network, comprising the following steps: S1, modifying a network file yolov7-tiny.yaml; S2, training a model; and S3, comparing the precisions before and after modification and showing the effect. Through the method, the calculation amount can be greatly reduced while the precision is maintained.

The invention discloses a resource configuration synchronization method, a cloud edge cooperation system, a medium and a product. The resource configuration synchronization method applied to a center side comprises the following steps: acquiring a to-be-synchronized resource configuration item and a configuration item parameter value corresponding to the resource configuration item; calling a configuration change interface of an edge cluster according to the resource configuration item and the configuration item parameter value, so that the edge cluster updates an original configuration item parameter value corresponding to the resource configuration item in an edge configuration table according to the configuration item parameter value; and calling a configuration redeployment interface of the edge cluster to enable the edge cluster to generate a yaml file according to the yaml template and the updated edge configuration table, and performing application deployment on the yaml file, thereby solving the problem that the synchronous update of the cloud edge collaboration system needs manual maintenance, and improving the operation and maintenance efficiency and stability of the cloud edge collaboration system.

This application provides a method and apparatus for generating random instruction test cases, relating to the field of automated testing technology. First, target instructions or instruction sequences are encapsulated into C inline functions using inline assembly or macro definition, forming a unified function library. Next, a function parameter constraint system is constructed, defining parameter types, address ranges, instruction combination methods, and value range constraints for each encapsulated C inline function. Then, a multi-level nested structure is built based on the C inline functions to organize the instructions, where each level node is associated with a corresponding C inline function name and constraints. Finally, based on a YAML configuration file, the target C inline functions are determined from the multi-level nested structure and combined to generate random instruction test cases. The YAML configuration file includes at least the number of iterations, a random seed, a random strength factor, and test content configuration. The solution provided in this application has the advantages of improved verification efficiency and applicability to different scenarios.

The invention discloses a software test report generation method and device, a storage medium and computer equipment, and the method comprises the steps: responding to a test report generation instruction of target software for a target scene, and obtaining test index data of different data sources through a unified multi-data source adaptation layer interface, the different data sources comprise a Prometheus time sequence data source, a Grafana visual data source and a YAML test case data source; obtaining a test report generation template corresponding to the target scene, and determining an index association rule and a rendering type in the test report generation template; performing association analysis on the test index data of the different data sources on the basis of an index association rule, determining test conclusion data of the target software on the basis of an association analysis result, and rendering the test index data in the Grafana visual data source on the basis of a rendering type to obtain a rendered picture; and embedding the test index data, the test conclusion data and the rendering picture into a test report generation template to obtain a test report corresponding to the target software.

The invention discloses a high-performance visual interface configuration service design method based on a yaml format, a visual large-screen interface is provided through database configuration without code writing, and the method comprises the following steps: interface configuration rules: one configuration represents one interface; the data acquisition engine acquires original data according to configuration; the data processing engine processes the original data according to the configuration to generate target chart data; and performing visual display, wherein the web page end displays a corresponding chart according to an interface response result. According to the method, data acquisition and data processing are decoupled, and the data processing flow is completed by the back-end service, so that the network data transmission quantity is greatly reduced, the data processing tasks of the web front-end equipment are reduced, and the rendering speed of the visualized large-screen chart is improved.

The application provides a configuration-driven DL4NLP model automatic training and deployment method, which comprises the following steps: parsing a YAML configuration file and verifying parameters to generate a unified process configuration; automatically loading data and performing preprocessing according to the configuration to generate a model input tensor; instantiating model components through a component factory and assembling the model components into a complete network model; automatically configuring a training environment to train and evaluate the model to obtain an optimal model; exporting the model into a TorchScript format binary file; and automatically generating a standardized deployment package based on a template engine. The application abstracts the whole process of model development and deployment into a configuration-driven standardized pipeline by parsing the YAML configuration file, automatically performs data loading and preprocessing, model component instantiation and assembly, training optimization and deployment package generation, and solves the problems of low development efficiency, long cycle and technical gap between training and deployment caused by repeated code writing and manual conversion and deployment for different tasks in traditional model training and deployment.

A system that captures runtime data for a pipeline execution, generates an intermediate hierarchical file that includes relationships between the captured data, and converts the intermediate file to alternative format pipeline files, such as YAML files. The present system employs dynamic instrumentation of pipeline executions, regardless of their type, to capture data during pipeline execution. This approach not only facilitates the capture of comprehensive execution data but also leverages this information to seamlessly generate equivalent pipelines on alternative continuous integration platforms.

The invention relates to the field of firmware updating, and discloses a firmware updating method and device of an IOS system and a storage medium. The method comprises the following steps: receiving firmware metadata, and generating a firmware downloading HTML file based on the firmware metadata; the firmware is analyzed to download the HTML file, and a firmware information YAML file is generated; analyzing and downloading the firmware information YAML file to obtain a firmware resource package; all firmware resource packages are placed in a resource storage area, and a firmware resource library is generated; on the basis of a CI / CD tool, a firmware release page is collected regularly, and a firmware update index is generated; when a firmware updating instruction of a user is received, the updated firmware resource library is inquired according to firmware information corresponding to the firmware updating instruction, an updated firmware package is obtained, and the updated firmware package is loaded. In the embodiment of the invention, the firmware resource packet does not need to be manually managed, and the specified firmware resource packet is automatically updated, so that the firmware packet management efficiency and timeliness of the IOS system are improved.

The invention provides an automatic report generation system and method based on a hybrid analytic model and a template engine, and the system comprises a hybrid document analysis module which converts an input semi-structured document into a structured YAML data file, builds and retains a context hierarchical relation through maintaining a stack data structure, and generates an automatic report when a title with a level of N is analyzed; popping up all title nodes with levels greater than or equal to N in the stack, and then pressing the title nodes with the current level of N into the stack; the multi-source data fusion and processing module is used for expanding static data extracted from the YAML data file based on the YAML data file; and the report generation module based on the template engine is used for realizing separation of contents and formats and dynamically generating table rows or paragraphs. According to the method and the device, the structured information with the context relation can be accurately and completely extracted from the semi-structured source document or the mixed document with variable formats, and the analysis precision, the data processing flexibility and the expansibility of the mixed document are effectively improved.

The application discloses an AST-aware hybrid block processing system for RAG system and belongs to the technical field of natural language processing.The application comprises the following steps: parsing a Markdown document and constructing an abstract syntax tree; performing one-time segmentation according to the title level of the abstract syntax tree node type, performing secondary segmentation when the text block length exceeds a threshold value, and setting an overlapping area; cleaning the content of the text block; parsing YAML Frontmatter metadata and traceability information in the header of the Markdown document; connecting with an external server through an end-to-end cloud pipeline; and realizing multi-process parallel and streaming processing through a parallel processing architecture.The application can realize end-to-end automation and high-performance parallel processing under the premise of ensuring block accuracy and semantic integrity.

The invention provides a unified operation and maintenance method and device for heterogeneous infrastructures, and belongs to the technical field of computer software, and the method comprises the following steps: obtaining a declarative YAML configuration file defined with resource pool information, global variables and application configuration information, and analyzing the configuration file to obtain a structured configuration object; identifying target resource types contained in application information, global variables and resource pool information in the structured configuration object; matching a corresponding target application template from a predefined template library, and rendering the target application template based on the global variable to generate an execution instruction; based on the execution instruction, generating an independent Ansible execution file for each application; and running the Ansible execution file to complete application installation, and after the application installation is completed, realizing state sharing between the applications based on a context management mechanism. According to the method, the problems of high configuration complexity, difficulty in ensuring consistency and difficulty in hybrid deployment in operation and maintenance management can be solved.

The invention relates to the technical field of cloud computing, and particularly provides a method and device for dynamically virtualizing video card resources in a container environment, and the method comprises the following steps: S1, deploying a basic container environment; s2, installing a display card driver; s3, a virtual configuration file gpu-profile. Yaml of the graphics card is added, and a virtual configuration file gpu-profile. Yaml is added; s4, installing a container engine plug-in; and S5, deploying container services. Compared with the prior art, the utilization rate of graphics card resources can be greatly improved, and the cost is reduced.

This application discloses a water plant cluster management method, apparatus, equipment, and storage medium based on a large language model and intelligent agents, relating to the field of artificial intelligence technology. The method includes: a main intelligent agent receiving tasks and sending asynchronous call messages containing load data to expert sub-intelligent agents in various domains; the sub-intelligent agents determining the current context by combining a YAML metadata dictionary and industry specifications, and judging whether industrial simulation is involved through a large language model. If so, the corresponding local code script is called, scheduled to a containerized physical isolation sandbox, and after passing the whitelist comparison by the permission control module, the result is calculated based on the load data and returned to the main intelligent agent. The main intelligent agent integrates multi-source datasets and calls the ACP proxy encapsulation module to construct JSON semantic instructions for managing the water plant cluster, thereby improving the efficiency of water plant cluster management.

The application relates to the technical field of Fintech (Fintech), and discloses a task scheduling method, which comprises the following steps: when an operation task is received, a container corresponding to the operation task is created; a preset mapping relationship table is queried, and a target Kubernetes cluster is determined according to a container parameter of the container; operation task corresponding running parameters are sent to a target Kubernetes interface corresponding to the target Kubernetes cluster, the running parameters are converted into a yaml file through the target Kubernetes interface, and the target Kubernetes cluster executes the operation task according to the yaml file. The application also discloses a task scheduling device, equipment and a computer readable storage medium. In the application, a Kubenetes Gateway device is used to replace a Kubernetes control plane, and high-efficiency management of a Kubenetes cluster is realized.

The invention provides a one-button land intelligent identification and segmentation method and system. The system comprises a configuration file unit, a configuration analyzer, a dynamic data set register, a self-adaptive model factory and a unified training assembly line. The configuration file unit is connected with the configuration analyzer, and the configuration analyzer is connected with the dynamic data set registrar and the self-adaptive model factory, reads and analyzes the YAML configuration file, and transmits an analysis result to the dynamic data set registrar and the self-adaptive model factory; the dynamic data set register receives data set configuration from the configuration analyzer, transmits meta-information to the adaptive model factory, and transmits the data loader to the unified training assembly line; the adaptive model factory receives the model configuration from the configuration parser, receives the meta-information from the dynamic data set registrar, and transmits the adapted model to the unified training assembly line. According to the method, the manual workload is reduced, errors caused by manually modifying model parameters are eliminated, and the experiment iteration efficiency is improved.

The application provides a multi-objective conflict coordination method for model mapping configuration optimization, relates to the technical field of model-based system engineering, and focuses on a personalized configuration extension mechanism in a SysML to Modelica automatic mapping process, and especially realizes an innovation breakthrough in conflict detection and optimization coordination mechanism between personalized configuration and basic configuration. The application flexibly defines special mapping relationships from SysML elements to Modelica elements through configuration files (such as XML, JSON, YAML and the like), the configuration content can be directly embedded into multiple sub-processes such as model analysis, type mapping, attribute relationship and behavior constraint, and the standardized interface is deeply integrated, so that the customization and fine-grained capability of automatic mapping are improved.

The invention discloses a multi-database adaptation center construction method based on JDBC, which comprehensively adapts to a current mainstream database and a domestic database, adopts SpringBoot framework integration, connects different databases through a unified JDBC interface, configures a corresponding special drive for each database type, ensures connection compatibility, integrates a MyBatis persistent layer framework, and provides a multi-database adaptation center construction method based on JDBC. The method comprises the following steps: establishing an independent SQL adaptation mechanism for different database types, isolating specific SQL grammar differences of each database, realizing automatic adaptation of SQL statements, initializing SQL scripts by adopting version number naming specifications, performing intelligent analysis and priority ranking on SQL files through a user-defined algorithm when a service is started, executing database upgrading strictly according to a version number increasing sequence, and realizing automatic adaptation of SQL statements. Automatic version migration of a database structure is achieved, database types are flexibly switched through a YAML configuration file, and connection access, switching and development of different databases are completed without code modification.

Container data structure (.v7g.md) for audit-proof business document management, characterized by ◯ a YAML front matter section (10) with a time-ordered UUIDv7 identifier (11) according to RFC 9562, a document type (12), predecessor references (13) to predecessor documents, successor references (14) to successor documents and match key fields (15) for automatic chain association, ◯ a Markdown section (20) for human-readable metadata and descriptions, o embedded JSON code blocks (30) containing machine-processable business data, and ◯ a Git commit hash reference (40) for cryptographic integrity proof.

The invention discloses a switch configuration management method and device, electronic equipment and a storage medium. The switch configuration management method comprises the following steps: receiving target configuration data in a YAML format configured for a target switch; converting the target configuration data in the YAML format into target configuration data in a JSON format, and generating task data according to the target configuration data in the JSON format; and according to the task data, converting the target configuration data in the JSON format into target configuration data in an XML format, and sending a configuration instruction containing the target configuration data in the XML format to the target switch, so that the target switch executes the configuration instruction. The complexity of switch configuration management can be reduced, and the efficiency of switch configuration management can be improved.

The embodiment of the application discloses a method and device for cross-cluster deployment of an application, a terminal and a medium, and belongs to the technical field of computers. The application provides a target resource template, configures application parameters, generates a declaration style YAML file and creates a deployment resource. When deploying a first task, the number of copies and the image tag of the deployment resource are updated. Based on the deployment resource in the Kubernetes cluster, a resource controller is created. The resource controller pulls the image and starts the target instance pod of the target number of copies to complete the deployment of the application. The image is built after running the pipeline and stored in the private warehouse harbor. Since the application templates the declaration style YAML file, the general configuration is automatically filled, and the difficulty of cross-cluster deployment of the application by the development and operation personnel through the pipeline is reduced.

The invention discloses an aerospace cluster-oriented cloud-native programming model framework deployment method. The method comprises the following steps of: defining a hardware cluster in an aerospace cluster as a plurality of nodes; deploying bottom layer operating system software and a cluster scheduler on each node, wherein the cluster scheduler is used for realizing clustering and large-scale management of the container; the method comprises the following steps of: configuring a network environment for each node and installing container software, assigning at least one node as a Master node through a script, and adding other nodes as Worker nodes into the Master node to form a Master-Worker cluster; and packaging the aerospace application program into a container mirror image, uploading the container mirror image to a mirror image warehouse of a Master-Worker cluster, and deploying the aerospace application program into the Master-Worker cluster in a container form through a yaml configuration file. According to the method, the cloud native technology is applied to an aerospace cluster scene through a standardized deployment process, and the problem that a traditional framework is insufficient in the aspects of task rapid self-organization and efficient collaboration is solved.

The application discloses a template cluster-based vulnerability scanning method and device, and a storage medium, and comprises the following steps: in response to a vulnerability scanning request initiated by a user, determining a scanning target of the vulnerability scanning request; loading at least one YAML classification template suitable for the scanning target to form a template cluster; performing global request merging and path optimization on the basis of address information of the scanning target and request specifications of each YAML classification template in the template cluster to obtain a detection request set; sending the detection request set to the scanning target, and receiving a response data set returned by the scanning target on the basis of the detection request set; extracting response matching rules of each YAML classification template in the template cluster, and performing matching analysis on the response data set by using the response matching rules; and generating a vulnerability detection report according to a matching analysis result. Through template rule encapsulation and global intelligent optimization, the application realizes scanning request order reduction and resource efficient utilization, and significantly improves detection efficiency and accuracy.

The application discloses an intelligent workflow arrangement method and system based on natural language generation. A complete workflow can be automatically generated and registered through natural language description, avoiding direct generation of a long JSON / YAML configuration file, and instead generating concise SDK calling code, thereby effectively improving creation efficiency and robustness. Through high-level abstraction and encapsulation of underlying components, the application changes the task of a large language model from "generating a configuration file" to "generating calling code", significantly reduces complexity, improves generation accuracy and execution efficiency, and is suitable for rapid construction and deployment of various intelligent agent platforms.

The application provides a management method for analyzing an OPC UA information model, which listens to a user terminal, obtains a YAML format file corresponding to a task executed by the user terminal, sends a YAML file confirmed to be intact after examination to an OPC UA server, constructs a corresponding OPC UA information model by using the OPC UA server, feeds back the OPC UA information model to the user terminal for loading, feeds back a notification message to the OPC UA server according to loading state information of the OPC UA information model, so that the OPC UA server performs different mode operations on the backup OPC UA information model, and the method constructs the OPC UA information model after analyzing the YAML format file, and when the OPC UA information model is loaded on the user terminal, the loading state information of the model is used as a benchmark to effectively and comprehensively detect and optimize the OPC UA information model, thereby improving the operation reliability and accuracy of the OPC UA information model.