CN115222444A - Method, apparatus, device, medium and product for outputting model information - Google Patents
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Abstract
The present disclosure provides a method, apparatus, device, medium, and product for outputting model information, relating to the field of computer technology, in particular to the field of data processing technology. The specific implementation scheme is as follows: obtaining a target model from a target memory; determining service scene information corresponding to the target model by using a target processor; determining model information layout parameters and/or model information content parameters using a target processor based on business scenario information; and outputting target model information corresponding to the target model by using the target processor based on the model information layout parameter and/or the model information content parameter. The realization mode can improve the information acquisition efficiency of the model information.
Description
Technical Field
The present disclosure relates to the field of computer technology, and more particularly to the field of data processing technology.
Background
At present, after a model is generated, model information corresponding to the model often needs to be output so that a user can intuitively know the model situation based on the model information. The model information may include model training information, model effect information, model interpretation information, model feature information, and the like.
However, in practice, it is found that, because the model information contains a large amount of information, the user needs to manually extract the information needed by the user from a large amount of model information, thereby resulting in low information acquisition efficiency.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, medium, and article of manufacture for outputting model information.
According to an aspect of the present disclosure, there is provided a method for outputting model information, including: obtaining a target model from a target memory; determining service scene information corresponding to the target model by using a target processor; determining model information layout parameters and/or model information content parameters using a target processor based on business scenario information; and outputting target model information corresponding to the target model by using the target processor based on the model information layout parameter and/or the model information content parameter.
According to another aspect of the present disclosure, there is provided an apparatus for outputting model information, including: a model obtaining unit configured to obtain a target model from a target memory; a scene determining unit configured to determine service scene information corresponding to the target model using the target processor; a parameter determination unit configured to determine a model information layout parameter and/or a model information content parameter using the target processor based on the business scenario information; and an information output unit configured to output target model information corresponding to the target model using the target processor based on the model information layout parameter and/or the model information content parameter.
According to another aspect of the present disclosure, there is provided an electronic device including: one or more processors; a memory for storing one or more programs; when executed by one or more processors, cause the one or more processors to implement a method for outputting model information as any one of above.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method for outputting model information as any one of the above.
According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements a method for outputting model information as any one of the above.
According to the technology of the present disclosure, a method for outputting model information is provided, which can improve the information acquisition efficiency of the model information.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present disclosure may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for outputting model information, according to the present disclosure;
FIG. 3 is a schematic diagram of one application scenario of a method for outputting model information according to the present disclosure;
FIG. 4 is a flow diagram of another embodiment of a method for outputting model information according to the present disclosure;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for outputting model information according to the present disclosure;
fig. 6 is a block diagram of an electronic device for implementing a method for outputting model information according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may obtain an object model that requires output of model information, and send the object model to the server 105 through the network 104, so that the server 105 generates object model information corresponding to the object model, and returns the object model information to the terminal devices 101, 102, 103, so that the terminal devices 101, 102, 103 output the object model information.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices including, but not limited to, a mobile phone, a computer, a tablet, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server providing various services, for example, the server 105 may receive the target model sent by the terminal devices 101, 102, 103 through the network 104, and determine the business scenario information corresponding to the target model; determining model information layout parameters and/or model information content parameters based on the service scene information; and generating target model information corresponding to the target model based on the model information layout parameter and/or the model information content parameter, and returning the target model information to the terminal devices 101, 102, 103 through the network 104.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for outputting model information provided in the embodiment of the present disclosure may be executed by the terminal devices 101, 102, and 103, or may be executed by the server 105, and the apparatus for outputting model information may be disposed in the terminal devices 101, 102, and 103, or may be disposed in the server 105, which is not limited in the embodiment of the present disclosure.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for an implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for outputting model information in accordance with the present disclosure is shown. The method for outputting model information of the embodiment includes the following steps:
In this embodiment, the executing agent (such as the server 105 or the terminal devices 101, 102, 103 in fig. 1) may obtain the target model requiring the output model information from the electronic device which is locally stored or which is connected in advance. The target model may be a model in various business scenarios, and may include, but is not limited to, a risk assessment model, a marketing model, and the like, which is not limited in this embodiment.
In this embodiment, the execution subject may determine the service scenario information corresponding to the target model based on a preset correspondence between the model and the scenario. Or, the execution subject may also determine the service scenario information corresponding to the target model, which is selected by the user, based on the human-computer interaction operation with the user. The service scenario information is used to describe a service scenario for which the model information needs to be output, and the representation form of the service scenario information may include, but is not limited to, a service scenario name, a service scenario identifier, a description text of the service scenario, and the like.
For the target model, one target model may be applied to multiple service scenarios, for example, a binary model may be applied to a service scenario classified by a black and white list, a service scenario labeled by a user, a service scenario for detecting a specific target, and the like. When generating the object model information corresponding to the object model, it is necessary to determine which kind of object model information under the service scenario is generated, and at this time, the service scenario information for describing the service scenario may be determined based on the above manner. Then, the execution subject may generate target model information corresponding to the target model matching the specified business scenario based on the business scenario information.
In this embodiment, the execution subject may preset a mapping relationship between the service scene and the model information layout parameter and/or the model information content parameter, so as to determine the model information layout parameter and/or the model information content parameter matching the service scene information based on the mapping relationship. The model information layout parameter is used for configuring the layout condition of the target model information, and the model information content parameter is used for configuring the content condition of the target model information. Optionally, the model information layout parameters may include a position layout parameter, a size layout parameter, a presentation form layout parameter, and the like of each piece of information in the target model information, which is not limited in this embodiment. The model information content parameter may include a content object parameter, a content right parameter, a content time parameter, and the like of each information in the target model information, which is not limited in this embodiment.
And step 204, outputting target model information corresponding to the target model by using the target processor based on the model information layout parameter and/or the model information content parameter.
In this embodiment, after obtaining the model information layout parameter and/or the model information content parameter, the execution subject may display various types of information in the target model information in a corresponding layout manner according to the model information layout parameter. And displaying the information content of various information in the target model information by corresponding content parameters according to the model information content parameters.
Alternatively, the object model information may be output in a browser-server mode.
Optionally, the target model information may include various types of information, such as training task description information, training sample information, model parameter information, and the like corresponding to model training categories, model effect evaluation index information, model historical training log information, actual application effect information of the model in a service scene, and the like corresponding to model effect categories, decision tree information, feature distribution information, sample decision path information, and the like in model interpretation categories, feature basic information, feature stability information, feature statistical information, and the like in feature analysis categories, which is not limited in this embodiment. This information may be pre-stored in the database for the specified path. When the target model information is generated, various types of information can be called from the database based on the path where the information needed to be used is located, and the target model information is formed. Thereafter, the execution subject may output the target model information at the browser.
In some optional implementation manners of this embodiment, based on the model information layout parameter and/or the model information content parameter, outputting the target model information corresponding to the target model may include: determining the layout relation among the various information based on the model information layout parameters; determining content objects displayed in each type of information and content parameters corresponding to each content object based on the content parameters of the model information, wherein the content parameters can include but are not limited to content rights and content generation time; and outputting the content objects displayed in each type of information according to the layout relation and the content parameters corresponding to each content object. By implementing the optional implementation mode, the information content of each piece of information can be output according to the layout relation between each piece of information and the content parameter of each piece of information, which are matched with the business scene, so that the pertinence of the information output of the target model is improved.
With continued reference to fig. 3, a schematic diagram of one application scenario of a method for outputting model information according to the present disclosure is shown. In the application scenario of fig. 3, the execution subject may first obtain the service scenario information 301, then determine a model information layout parameter matching the service scenario information 301, and may configure a layout situation between various types of information based on the model information layout parameter, where the layout situation may be represented as a layout diagram 302. In the layout diagram 302, different information may be displayed in different sizes according to the position layout of various types of information. Optionally, the user may delete the corresponding information by clicking a delete key on the upper right corner of each information in the layout diagram 302, thereby implementing user-defined adjustment of the layout information. Also, the executing agent may also determine a model information content parameter 303 that matches the business scenario information. Then, the executing agent may adjust the specified content of the specified information in the layout diagram based on the content parameter in the model information content parameter 303, so as to obtain the final target model information 304. Thereafter, the execution principal may output target model information 304.
The method for outputting model information provided by the above embodiment of the present disclosure can determine the service scene information corresponding to the target model, and determine the model information layout parameter and/or the model information content parameter matched with the service scene information, thereby outputting the target model information in a personalized manner based on the model information layout parameter and/or the model information content parameter, facilitating a user to quickly obtain required information based on the target model information, and thus improving the information obtaining efficiency of the model information.
With continued reference to FIG. 4, a flow 400 of another embodiment of a method for outputting model information in accordance with the present disclosure is shown. As shown in fig. 4, the method for outputting model information of the present embodiment may include the steps of:
In this embodiment, the executing agent (such as the server 105 or the terminal devices 101, 102, 103 in fig. 1) may obtain the target model requiring the output model information from the electronic device which is locally stored or which is connected in advance. The target model may be a model in various service scenarios, and may include, but is not limited to, a risk assessment model, a marketing model, and the like, which is not limited in this embodiment.
The execution main body can comprise a target memory and a target processor, wherein the target memory is used for storing various types of data, and the target processor is used for carrying out data processing on various types of data. The above object model may be stored in the object memory in advance.
In this embodiment, the execution subject may determine the service scenario information corresponding to the target model based on a preset correspondence between the model and the scenario. Or, the execution subject may also determine the service scenario information corresponding to the target model, which is selected by the user, based on the human-computer interaction with the user. The service scenario information is used to describe a service scenario for which the model information needs to be output, and the representation form of the service scenario information may include, but is not limited to, a service scenario name, a service scenario identifier, a description text of the service scenario, and the like.
For the target model, one target model may be applied to multiple service scenarios, for example, a binary model may be applied to a service scenario classified by a black and white list, a service scenario labeled by a user, a service scenario for detecting a specific target, and the like. When generating the object model information corresponding to the object model, it is necessary to determine which kind of object model information under the service scenario is generated, and at this time, the service scenario information for describing the service scenario may be determined based on the above manner. Then, the execution subject may generate target model information corresponding to the target model matching the specified business scenario based on the business scenario information.
In this embodiment, the execution main body may store at least one information submodule in advance to obtain the information submodule set. Each information sub-module may be a sub-module under each type of information, for example, the information sub-module may be a module corresponding to task description information under a model training information type, or the information sub-module may be a module corresponding to model evaluation index information under a model effect information type.
And, for each service scenario, different combinations of information submodules may be matched. For example, for the service scenario 1, the corresponding target information sub-module may be an information sub-module a, an information sub-module B, and an information sub-module C; for the service scenario 2, the corresponding target information sub-modules may be an information sub-module a and an information sub-module B.
The execution main body can select at least one target information submodule matched with the service scene based on the service scene information as a follow-up output information submodule.
In this embodiment, the execution subject may use, as the model information layout parameter, a position parameter corresponding to a position relationship between the target information sub-modules and a module layout parameter of each target information sub-module. The position relationship is used to describe the relative position between the target information sub-modules, for example, the target information sub-module a is located above the target information sub-module B. The module layout parameters of each target information submodule may include at least one of: whether to show, whether to collapse the show, whether to export to a specified format, size category of the sub-module. The size category may include three categories, large, medium and small.
In this embodiment, the model information content parameter can be determined by implementing steps 405 to 407. The target model may correspond to a plurality of model evaluation indexes, where the model evaluation indexes are used for evaluating performance of the target model, and the model evaluation indexes may include, but are not limited to, accuracy, precision, recall rate, positive sample number, positive sample rate, and the like, which is not limited in this embodiment.
Furthermore, the execution subject may determine a target model evaluation index for which the index name content needs to be replaced, from among the plurality of model evaluation indexes of the target model. For example, the executing subject may determine the above-described positive sample number and the above-described positive sample rate as the target model evaluation index.
And 406, determining an index name parameter corresponding to the target model evaluation index based on the service scene information.
In this embodiment, the execution body may store in advance a corresponding relationship between different service scenarios and an index name parameter, where the index name parameter is used to describe an index name that needs to be configured. For example, for a credit business scenario, the index name parameter corresponding to the target model evaluation index "positive sample number" may be "overdue number", and the index name parameter corresponding to the target model evaluation index "positive sample rate" may be "overdue rate"; for the marketing business scenario, the index name parameter corresponding to the target model evaluation index "positive sample number" may be "the number of converted users", and the index name parameter corresponding to the target model evaluation index "positive sample rate" may be "conversion rate".
In the present embodiment, the execution body may use the index name parameter as the model information content parameter, or the execution body may use the index name parameter as the model information content parameter in common with each of the content parameters described above.
For detailed description of each content parameter, please refer to the detailed description of step 203, which is not repeated herein.
In response to detecting an adjustment instruction for the model information layout parameters and/or the model information content parameters, an adjusted model information layout parameter and/or an adjusted model information content parameter is determined using the target processor, step 408.
In this embodiment, the execution subject may detect whether the human-machine interaction triggers the adjustment instruction based on the human-machine interaction with the user. Wherein the adjusting instruction is used for indicating to adjust the model information layout parameter and/or the model information content parameter.
Optionally, the execution main body may output a preview layout of the target model information based on the adjusted model information layout parameter and/or the adjusted model information content parameter, and the user may click and drag each information sub-module on the preview layout to adjust the layout between each information sub-module.
Optionally, the user may also adjust module layout parameters of each information sub-module, such as whether to configure the information sub-module to display, whether to fold the information sub-module, whether to export the information sub-module to a specified format, and size category of the sub-module, which is not limited in this embodiment.
Alternatively, the user may delete the specified content on the preview layout, or may change the name of the target model evaluation indicator, or may modify the content parameter of each information sub-module.
And step 409, outputting target model information according to the adjusted model information layout parameters and/or the adjusted model information content parameters.
In this embodiment, for the layout parameters according to the adjusted model information and/or the content parameters of the adjusted model information, a detailed description of the target model information is output, please refer to the layout parameters according to the model information and/or the content parameters of the model information, and it is not repeated herein.
In response to detecting a confirmation instruction for the model information layout parameters and/or the model information content parameters, target processor is used to output target model information according to the model information layout parameters and/or the model information content parameters, step 410.
In this embodiment, the execution subject may detect whether the human-machine interaction triggers a confirmation instruction based on the human-machine interaction with the user, where the confirmation instruction is used to confirm the current model information layout parameters and/or the model information content parameters.
In some optional implementations of this embodiment, outputting the target model information according to the model information layout parameter and/or the model information content parameter, using the target processor, may include: mapping at least one target information submodule to a specified output position by using a target processor according to the model information layout parameters; for the target information submodule, outputting module content corresponding to the target information submodule according to the model information content parameter; wherein, the module content at least comprises an index name.
In this implementation manner, the execution subject may map at least one target information sub-module to a specified output position for display according to a position relationship between each target information sub-module in the model information layout parameter. And for each target information submodule, outputting the module content corresponding to the target information submodule according to the model information content parameter. Specifically, the model information content parameter may include an index name parameter, and the execution subject may modify the target model evaluation index in the target information sub-module into the index name parameter based on the index name parameter, and output the module content after modifying the index name.
The method for outputting model information provided by the above embodiment of the present disclosure may further determine the model information layout parameter based on the position relationship between each target information sub-module and the module layout parameter of each target information sub-module, so that the target model information may be generated according to the module position and the module layout conforming to the service scene, and the display effect of the target model information is better. And generating a model information content parameter based on the index name matched with the service scene, and realizing the scene configuration of the index name. And the model information layout parameters and the model information content parameters can be adjusted in a user-defined mode based on the adjustment instruction triggered by the user, so that the customization degree of the target model information output is improved.
With further reference to fig. 5, as an implementation of the methods shown in the above-mentioned figures, the present disclosure provides an embodiment of an apparatus for outputting model information, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be applied to electronic devices such as a terminal device and a server.
As shown in fig. 5, the apparatus 500 for outputting model information of the present embodiment includes: a model acquisition unit 501, a scene determination unit 502, a parameter determination unit 503, and an information output unit 504.
A model obtaining unit 501 configured to obtain a target model from a target storage.
And a scene determining unit 502 configured to determine service scene information corresponding to the target model using the target processor.
A parameter determining unit 503 configured to determine model information layout parameters and/or model information content parameters using the target processor based on the service context information.
An information output unit 504 configured to output target model information corresponding to the target model using the target processor based on the model information layout parameter and/or the model information content parameter.
In some optional implementations of this embodiment, the parameter determining unit 503 is further configured to: determining at least one target information submodule corresponding to the service scene information from a preset information submodule set by using a target processor; and generating model information layout parameters based on the position relation among the at least one target information submodule and the module layout parameters of the target information submodule.
In some optional implementations of this embodiment, the parameter determining unit 503 is further configured to: determining a target model evaluation index from model evaluation indexes of a target model using a target processor; determining an index name parameter corresponding to a target model evaluation index based on the service scene information; based on the index name parameter, a model information content parameter is determined.
In some optional implementations of this embodiment, the information output unit 504 is further configured to: in response to detecting an adjustment instruction for a model information layout parameter and/or a model information content parameter, determining, using a target processor, an adjusted model information layout parameter and/or an adjusted model information content parameter; and outputting the target model information according to the adjusted model information layout parameter and/or the adjusted model information content parameter.
In some optional implementations of this embodiment, the information output unit 504 is further configured to: in response to detecting a confirmation instruction for the model information layout parameters and/or the model information content parameters, target model information is output using the target processor in accordance with the model information layout parameters and/or the model information content parameters.
In some optional implementations of this embodiment, the information output unit 504 is further configured to: mapping at least one target information submodule to a designated output position by using a target processor according to the model information layout parameters; for the target information submodule, outputting module content corresponding to the target information submodule according to the model information content parameter; wherein, the module content at least comprises an index name.
It should be understood that the units 501 to 504 described in the apparatus 500 for outputting model information correspond to respective steps in the method described with reference to fig. 2, respectively. Thus, the operations and features described above for the method for outputting model information are equally applicable to the apparatus 500 and the units included therein, and will not be described again here.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data required for the operation of the device 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, and the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 executes the respective methods and processes described above, such as a method for outputting model information. For example, in some embodiments, the method for outputting model information may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM603 and executed by the computing unit 601, one or more steps of the method for outputting model information described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured by any other suitable means (e.g., by means of firmware) to perform the method for outputting model information.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (15)
1. A method for outputting model information, comprising:
obtaining a target model from a target memory;
determining service scene information corresponding to the target model by using a target processor;
determining, using the target processor, model information layout parameters and/or model information content parameters based on the business scenario information;
and outputting target model information corresponding to the target model by using the target processor based on the model information layout parameter and/or the model information content parameter.
2. The method of claim 1, wherein said determining model information layout parameters using said target processor based on said traffic scenario information comprises:
determining at least one target information submodule corresponding to the service scene information from a preset information submodule set by using the target processor;
and generating the model information layout parameters based on the position relationship among at least one target information submodule and the module layout parameters of the target information submodule.
3. The method of claim 1, wherein said determining, using the target processor, model information content parameters based on the traffic scenario information comprises:
determining, using the target processor, a target model evaluation index from model evaluation indices of the target model;
determining an index name parameter corresponding to the target model evaluation index based on the service scene information;
determining the model information content parameter based on the index name parameter.
4. The method of claim 1, wherein the outputting, using the target processor, target model information corresponding to the target model based on the model information layout parameters and/or the model information content parameters comprises:
in response to detecting an adjustment instruction for the model information layout parameters and/or the model information content parameters, determining, using the target processor, adjusted model information layout parameters and/or adjusted model information content parameters;
and outputting the target model information according to the adjusted model information layout parameter and/or the adjusted model information content parameter.
5. The method of claim 1, wherein the outputting, using the target processor, target model information corresponding to the target model based on the model information layout parameters and/or the model information content parameters comprises:
in response to detecting a confirmation instruction for the model information layout parameters and/or the model information content parameters, outputting the target model information using the target processor in accordance with the model information layout parameters and/or the model information content parameters.
6. The method of claim 5, wherein said outputting said object model information using said object processor in accordance with said model information layout parameters and/or said model information content parameters comprises:
mapping at least one target information submodule to a designated output position using the target processor according to the model information layout parameters;
for the target information sub-module, outputting module contents corresponding to the target information sub-module according to the model information content parameters; wherein the module content at least comprises an index name.
7. An apparatus for outputting model information, comprising:
a model obtaining unit configured to obtain a target model from a target memory;
a scene determining unit configured to determine, using a target processor, service scene information corresponding to the target model;
a parameter determination unit configured to determine a model information layout parameter and/or a model information content parameter using the target processor based on the service scenario information;
an information output unit configured to output, using the target processor, target model information corresponding to the target model based on the model information layout parameter and/or the model information content parameter.
8. The apparatus of claim 7, wherein the parameter determination unit is further configured to:
determining at least one target information submodule corresponding to the service scene information from a preset information submodule set by using the target processor;
and generating the model information layout parameters based on the position relationship among at least one target information submodule and the module layout parameters of the target information submodule.
9. The apparatus of claim 7, wherein the parameter determination unit is further configured to:
determining, using the target processor, a target model evaluation index from model evaluation indices of the target model;
determining an index name parameter corresponding to the target model evaluation index based on the service scene information;
determining the model information content parameter based on the index name parameter.
10. The apparatus of claim 7, wherein the information output unit is further configured to:
in response to detecting an adjustment instruction for the model information layout parameters and/or the model information content parameters, determining, using the target processor, adjusted model information layout parameters and/or adjusted model information content parameters;
and outputting the target model information according to the adjusted model information layout parameter and/or the adjusted model information content parameter.
11. The apparatus of claim 7, wherein the information output unit is further configured to:
in response to detecting a confirmation instruction for the model information layout parameters and/or the model information content parameters, outputting the target model information using the target processor in accordance with the model information layout parameters and/or the model information content parameters.
12. The apparatus of claim 11, wherein the information output unit is further configured to:
mapping at least one target information submodule to a specified output position by using the target processor according to the model information layout parameters;
for the target information sub-module, outputting module content corresponding to the target information sub-module according to the model information content parameter; wherein the module content at least comprises an index name.
13. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.
14. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-6.
15. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115796272A (en) * | 2022-11-24 | 2023-03-14 | 北京百度网讯科技有限公司 | Model training method based on deep learning platform, data processing method and device |
| CN117371428A (en) * | 2023-09-25 | 2024-01-09 | 百度国际科技（深圳）有限公司 | Text processing method and device based on large language model |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115796272A (en) * | 2022-11-24 | 2023-03-14 | 北京百度网讯科技有限公司 | Model training method based on deep learning platform, data processing method and device |
| CN115796272B (en) * | 2022-11-24 | 2024-03-12 | 北京百度网讯科技有限公司 | Model training method based on deep learning platform, data processing method and device |
| CN117371428A (en) * | 2023-09-25 | 2024-01-09 | 百度国际科技（深圳）有限公司 | Text processing method and device based on large language model |
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