A parameterized control method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a parameterized control method and device, electronic equipment and storage medium, relates to the field of artificial intelligence, and in particular to automatic driving technology. The specific implementation scheme comprises the following steps: loading a candidate parameter configuration unit from the cloud for a generated computing task; selecting at least one target parameter configuration unit matched with the computing task from the candidate parameter configuration unit; and updating the parameter content included in the target parameter configuration unit to the computing task. The present disclosure can conveniently and efficiently configure parameters for various types of automatic driving computing tasks.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of artificial intelligence, in particular to automatic driving technology, and more particularly to a parameterized control method and device, electronic equipment, storage medium and computer program product. BACKGROUND

[0002] With the development of science and technology, more and more tools in life tend to be intelligent, especially unmanned vehicles, which will greatly facilitate people's life in the future.

[0003] In order to ensure the stable operation of unmanned vehicles, there are a large number of complex computing tasks in the unmanned vehicle system that need to be processed in time and efficiently. SUMMARY

[0004] The present disclosure provides a parameterized control method and device, electronic equipment, storage medium and computer program product.

[0005] According to an aspect of the present disclosure, a parameterized control method is provided, comprising:

[0006] loading a candidate parameter configuration unit from the cloud for a generated computing task;

[0007] selecting at least one target parameter configuration unit matched with the computing task from the candidate parameter configuration unit;

[0008] updating the parameter content included in the target parameter configuration unit to the computing task.

[0009] According to an aspect of the present disclosure, a parameterized control device is provided, comprising:

[0010] a loading module configured to load a candidate parameter configuration unit from the cloud for a generated computing task;

[0011] a screening module configured to select at least one target parameter configuration unit matched with the computing task from the candidate parameter configuration unit;

[0012] a parameter configuration module configured to update the parameter content included in the target parameter configuration unit to the computing task.

[0013] According to another aspect of the present disclosure, an electronic equipment is provided, comprising:

[0014] at least one processor; and

[0015] a memory in communication connection with the at least one processor; wherein

[0016] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the parameterized control method of any embodiment of the present disclosure.

[0017] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, the computer instructions being used to cause a computer to perform the parameterized control method of any embodiment of the present disclosure.

[0018] 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 the parameterized control method of any embodiment of the present disclosure.

[0019] According to the technology of the present disclosure, various types of automatic driving computing tasks can be conveniently and efficiently parameterized.

[0020] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings are used to better understand the present scheme and do not limit the present disclosure. Among them:

[0022] Figure 1 is a flowchart of a parameterized control method provided by an embodiment of the present disclosure;

[0023] Figure 2 is a flowchart of another parameterized control method provided by an embodiment of the present disclosure;

[0024] Figure 3a is a flowchart of another parameterized control method provided by an embodiment of the present disclosure;

[0025] Figure 3b is a schematic diagram of a tree structure matching rule provided by an embodiment of the present disclosure;

[0026] Figure 3c is a schematic diagram of a candidate parameter configuration unit provided by an embodiment of the present disclosure;

[0027] Figure 4 is a flowchart of another parameterized control method provided by an embodiment of the present disclosure;

[0028] Figure 5 is a structural schematic diagram of a parameterized control device provided by an embodiment of the present disclosure;

[0029] Figure 6 is a block diagram of an electronic device for implementing the parameterized control method of an embodiment of the present disclosure. Detailed Implementation

[0030] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0031] Currently, configuring parameters for autonomous driving computing tasks requires embedding the necessary runtime parameters into the code. The specified parameters are read from the code and submitted simultaneously with the computing task. However, this approach maintains a separate set of parameters for different types of tasks, resulting in severe coupling between parameters and code. Furthermore, each parameter modification necessitates a re-deployment, leading to low efficiency in configuring computing task parameters. Therefore, this disclosure proposes a parameterized control method, the specific process of which is illustrated in the following embodiment.

[0032] Figure 1 This is a flowchart illustrating a parameterized control method according to an embodiment of the present disclosure. This embodiment is applicable to configuring parameters for computational tasks related to autonomous driving, typically for configuring parameters for computational tasks in an autonomous driving simulation cloud platform. The method can be executed by a parameterized control device, which is implemented in software and / or hardware and integrated into an electronic device.

[0033] For details, see Figure 1 The parameterized control method is as follows:

[0034] S101. For the generated computing task, load the candidate parameter configuration unit from the cloud.

[0035] In the embodiments of the present disclosure, the computing task can be optionally related to automatic driving, and the number of candidate parameter configuration units is multiple, and the candidate parameter configuration units are preset for different computing tasks, and each candidate parameter configuration unit includes parameter content required for running the computing task, wherein the parameter content can be composed of a running parameter and a parameter value. The preset candidate parameter configuration unit is saved in the cloud, and when the parameter configuration of the newly generated computing task is needed, the candidate parameter configuration unit can be loaded from the cloud, and then the parameter configuration is performed according to the steps of S102-S103. In order to find the target parameter configuration unit matched with the computing task, all the candidate parameter configuration units saved in the cloud can be loaded locally. It should be noted that the parameter content required for different computing tasks is saved in the cloud in the form of parameter configuration units, so that the parameter content does not need to be embedded in the code, and the decoupling of the parameter content and the code is realized. Moreover, when the parameters corresponding to a certain computing task are updated, only the new candidate parameter configuration unit needs to be added in the cloud, and the corresponding update identifier is used for marking, and the code does not need to be frequently modified.

[0036] S102, selecting at least one target parameter configuration unit matched with the computing task from the candidate parameter configuration units.

[0037] In the embodiments of the present disclosure, the number of candidate parameter configuration units loaded from the cloud is multiple, so it is necessary to select the target parameter configuration unit matched with the computing task from the candidate parameter configuration units to ensure that the computing task submitted subsequently can be stably executed. It should be noted that since the parameter content required for the computing task is updated or modified, the number of target parameter configuration units matched with the computing task is at least one.

[0038] S103, updating the parameter content included in the target parameter configuration unit to the computing task.

[0039] In the embodiments of the present disclosure, if the number of target parameter configuration units matched with the computing task is one, the parameter content included in the target parameter configuration unit is directly updated and takes effect in the computing task; if the number of target parameter configuration units matched with the computing task is two or more, the last updated target parameter configuration unit is determined according to the update identifier of the parameter configuration unit, and then the parameter content in the last updated target parameter configuration unit is updated to the computing task, and the other target parameter configuration units are discarded; or, the parameter content in the other target parameter configuration units is first updated to the computing task, and then the previous parameter content is covered by the parameter content in the last updated target parameter configuration unit. In this way, the parameter configuration of the computing task is realized.

[0040] In the embodiments of the present disclosure, the parameters required for the computing tasks of different services are saved in the cloud in the form of candidate parameter configuration units, so that the parameters are not embedded in the code, and the parameters and the code are decoupled; when there is a new computing task, the candidate parameter configuration units are loaded from the cloud, and a target parameter configuration unit matching the computing task is selected from the candidate parameter configuration units, and then the parameters in the target parameter configuration unit are updated to the computing task to realize the parameter configuration of the computing task, so that the efficiency of parameter configuration can be ensured.

[0041] Figure 2 is a flowchart of another parameterized control method according to an embodiment of the present disclosure. Referring to Figure 2 , the parameterized control method is as follows:

[0042] S201, loading a candidate parameter configuration unit from the cloud for the generated computing task.

[0043] In the embodiments of the present disclosure, the candidate parameter configuration unit includes not only the parameter content but also the priority and the matching rule; the priority can be represented by a number, and the larger the number, the higher the priority, and for the same parameter, the parameter content with high priority covers the parameter content with low priority; it should be noted that for parameter A, the cloud has saved a candidate parameter configuration unit unit1 including the value of parameter A with priority 1, now the user modifies the value of parameter A and generates a new candidate parameter configuration unit unit2, in order to ensure that unit2 takes effect when the parameter is configured, the priority of unit2 is set to be greater than the priority of unit1. In this way, when parameter A is configured, the parameter content in unit2 can cover the parameter content in unit1.

[0044] The matching rule is used to judge whether the computing task matches the parameter content in the candidate parameter configuration unit. On this basis, at least one target parameter configuration unit matching the computing task can be selected from the candidate parameter configuration units through the steps of S202-S203.

[0045] S202, sorting the candidate parameter configuration units according to the priority of the candidate parameter configuration units.

[0046] Optionally, the values of the priorities of the candidate parameter configuration units are obtained first, and then the candidate parameter configuration units are sorted in descending order of priority or in ascending order of priority, so that the sorting result of the candidate parameter configuration units can be the sorting result in descending order of priority or the sorting result in ascending order of priority.

[0047] S203, according to the sorting result, traversing the candidate parameter configuration units in sequence, and each time a candidate parameter configuration unit is traversed, the following operation is performed until the traversal ends: judging whether the computing task meets the matching rule included in the candidate parameter configuration unit; if yes, the candidate parameter configuration unit is taken as the target parameter configuration unit, and the next candidate parameter configuration unit is started to be traversed; if not, the next candidate parameter configuration unit is directly traversed.

[0048] In the embodiments of the present disclosure, in order to find the target parameter configuration unit matched with the computing task from all candidate configuration units, the candidate parameter configuration units are traversed in sequence according to the order from low to high priority, and each time a candidate parameter configuration unit is traversed, it is judged whether the computing task meets the matching rule, and if yes, it is selected as the target parameter configuration unit, otherwise the next candidate parameter configuration unit is traversed. In this way, all target parameter configuration units with different priorities matched with the computing task can be selected. Further, the parameter content included in the target parameter configuration unit is updated to the computing task, and the specific process can be referred to S204.

[0049] It should be noted that the candidate parameter configuration unit also includes a hit probability value, which is used to determine whether the computing task can hit the candidate parameter configuration unit, wherein the hit probability value included in the candidate parameter configuration unit is set by the user according to actual needs. Before judging whether the computing task meets the matching rule in the candidate parameter configuration unit, the following operation is also included: judging whether the computing task can hit the candidate parameter configuration unit according to the hit probability. Optionally, by comparing the size of the random probability value associated with the computing task and the hit probability value of the candidate parameter configuration unit, it is determined whether the computing task can hit the candidate parameter configuration unit, wherein the random probability value is a random number between 0-100% randomly generated when the computing task is initiated or generated. If the random probability value is greater than the hit probability value, it is determined that the computing task cannot hit the candidate parameter configuration unit, and the next candidate parameter configuration unit can be directly traversed; otherwise, if the random probability value is less than the hit probability value, it is determined that the computing task can hit the candidate parameter configuration unit, and further judgment is needed according to the matching rule, and the specific process is described above. In this way, coarse screening is realized before judging whether the matching rule is met, the number of rule matching judgments is reduced, and the overall efficiency of parameter configuration is ensured.

[0050] S204, according to the order from low to high priority, the parameter content in each target parameter configuration unit is updated to the computing task in sequence.

[0051] In the embodiments of the present disclosure, for the same parameter, the parameter content of the high priority parameter overrides the parameter content of the low priority parameter. Therefore, in order from low to high priority, the parameter content in each target parameter configuration unit is updated into the computing task in turn, so that for the same parameter, the parameter value of the high priority parameter overrides the parameter value of the low priority parameter, and it is ensured that the target parameter configuration unit of the high priority can finally take effect.

[0052] In the embodiments of the present disclosure, the target parameter configuration unit matched with the computing task can be accurately selected through the matching rule, and it is ensured that the parameter configuration unit of the high priority can finally take effect by updating the parameter content in each target parameter configuration unit into the computing task in order from low to high priority.

[0053] Figure 3a is a flowchart of another parameterized control method according to the embodiments of the present disclosure. Referring to Figure 3a , the parameterized control method is as follows:

[0054] S301, obtaining the matching rule, priority and parameter content constructed by a user for any type of computing task.

[0055] S302, constructing a parameter configuration unit according to the matching rule, priority and parameter content, and uploading the constructed parameter configuration unit to the cloud as a candidate parameter configuration unit.

[0056] In the embodiments of the present disclosure, the user will construct the corresponding matching rule, priority and parameter content for the computing task in the following two cases: (1) initially constructing the candidate parameter unit; (2) when the user needs to modify a certain parameter.

[0057] The matching rule includes at least one logical operator, and each logical operator corresponds to at least one matching condition. Common logical operators include "or" (at least one of all conditions is true), "and" (all conditions are true) and "not" (none of all conditions is true), etc. The user can customize the logical operator according to actual needs, and when the logical result is true, it indicates that the parameter content is hit. The matching condition is usually related to the business, such as "the task name meets a certain regular expression", "who is the task submitter", "which type of task it belongs to", etc.

[0058] The most basic matching rule currently contains one logical operator and several matching conditions. In the parameterized control process, for the computing task, only the matching conditions are sequentially judged, and then the logical operator is used to determine whether the current configuration rule is true, that is, whether the parameter content under the parameter configuration unit Unit including the matching rule takes effect in the computing task.

[0059] If more refined control is needed, or more complex matching logic is needed for a certain business, the basic matching rule cannot meet the requirement. Therefore, consider the following case: when the condition in a matching rule is another matching rule, i.e., there is a nested relationship, a matching rule of a tree structure as shown in FIG. 3 is formed, and the root node and the intermediate parent node of the tree structure are logical operators, and the other leaf nodes are matching conditions. Figure 3b

[0060] In this way, the parameter configuration unit can be constructed according to the obtained matching rule, priority, and parameter content. It should be noted that the parameter configuration unit also includes a hit probability value, and the hit probability value is used to determine whether the computing task can hit the parameter configuration unit. The hit probability value of each parameter configuration unit is set by the user according to actual needs. For example, the hit probability value of the parameter configuration unit can be set to 60%. Since a random probability value between 0 and 100% is randomly generated for each computing task when the computing task is initiated or generated, that is, each computing task is associated with a random probability value in advance, it is only necessary to compare the size of the random probability value associated with the computing task and the hit probability value included in the parameter configuration unit to determine whether the computing task can hit the parameter configuration unit. Specifically, if the random probability value associated with the computing task is greater than 60%, it is determined that the computing task cannot hit the parameter configuration unit, that is, the computing task does not match the parameter configuration unit, and subsequent matching rule judgment is not needed. If the random probability value associated with the computing task is less than 60%, it is determined that the computing task can hit the parameter configuration unit, and further judgment is needed according to the matching rule.

[0061] On the basis of the above, the constructed parameter configuration unit is uploaded to the cloud as a candidate parameter configuration unit, and the structure of the candidate parameter configuration unit can be referred to as shown in FIG. 4. Figure 3c

[0062] It should be noted that through the matching logic of the tree structure, when it is needed to determine whether the parameter content under the candidate parameter configuration unit Unit is effective (i.e., whether it needs to be updated into the computing task), it is necessary to determine whether the outermost matching rule and the nested matching rule therein are true, so the recursive idea can be used to determine whether the computing task satisfies the matching rule. The matching rule of the tree structure makes the matching condition more refined, and the matching function more powerful.

[0063] Through the steps of S301-S302, the candidate parameter configuration unit can be constructed and saved in the cloud, which provides a guarantee for the subsequent implementation of parameterized control.

[0064] S303, for the generated computing task, load the candidate parameter configuration unit from the cloud. ​​

[0065] S304, selecting at least one target parameter configuration unit matching the computing task from the candidate parameter configuration units.

[0066] S305, updating the parameter content included in the target parameter configuration unit to the computing task.

[0067] The steps of S303-S305 can refer to the descriptions of the above embodiments, and will not be described here.

[0068] In the embodiments of the present disclosure, the matching rule of the candidate parameter configuration unit is set to a tree structure, so that the matching condition is more refined, and the matching function is more powerful. In addition, the present disclosure scheme can realize the modification of the parameters by adding new candidate configuration units, without having to modify the code to realize the parameter modification as in the prior art.

[0069] Figure 4 is a flowchart of another parameterized control method according to an embodiment of the present disclosure. In the embodiments of the present disclosure, the matching rule in the candidate parameter configuration unit is a matching rule for task circumscription and segmentation; and each computing task includes a plurality of subtasks. Referring to Figure 4 , the parameterized control method is as follows:

[0070] S401, for any computing task in the global task, determining a matching rule for task circumscription and segmentation satisfied by the computing task.

[0071] In the embodiments of the present disclosure, the global task includes an automatic driving batch computing task, the scale of which can reach millions per day, which brings great challenges to the data storage and computing nodes of the infrastructure. Under the current distributed computing and storage background, how to finely schedule the global task to each database or computing node and achieve uniform distribution of computing tasks is an urgent demand. In order to solve this problem, in the embodiments, the matching rule in the candidate parameter configuration unit is a matching rule for task circumscription and segmentation; and the matching rule for task circumscription and segmentation can divide each computing task in the global task into different task groups. For example, the global task includes 10 computing tasks (represented by job1-job10), it is determined by matching that job1-job4 satisfy the matching rule A for task circumscription and segmentation, and job5-job10 satisfy the matching rule B for task circumscription and segmentation, so that job1-job4 belong to the same task group, and job5-job10 belong to the same task group.

[0072] It should be noted that the process of determining the matching rule for task circle and division satisfied by any computing task is as follows: according to the priority of the loaded candidate parameter configuration unit, the candidate parameter configuration unit is sorted; according to the sorting result, the candidate parameter configuration unit is traversed in turn, and the following operations are performed for each traversed candidate parameter configuration unit until the traversal ends: judging whether the computing task satisfies the matching rule for task circle and division included in the candidate parameter configuration unit; if satisfied, record and start traversing the next candidate parameter configuration unit; if not satisfied, directly traverse the next candidate parameter configuration unit. Finally, according to the record result, the computing task set corresponding to each matching rule for task circle and division is determined. In addition, the running parameters of the computing task are also updated according to the matching result.

[0073] S402, distribute the subtasks included in the computing task to the multiple task buckets under the matching rule, and add the corresponding bucket identifier to the subtasks in each task bucket.

[0074] In the embodiment of the present disclosure, each matching rule for task circle and division is associated with a certain number (user-defined number) of task buckets for caching computing tasks. For any matching rule for task circle and division, after determining the computing task set satisfying the matching rule, the number of subtasks included in each computing task is determined, and then all subtasks included in all computing tasks in the set are evenly distributed to the task buckets, and the corresponding bucket identifier is added to the subtasks in each task bucket.

[0075] S403, according to the database or computing node pre-associated with the bucket identifier, schedule the subtasks with the bucket identifier to the corresponding database or computing node.

[0076] In the embodiment of the present disclosure, each bucket identifier is pre-associated with a database or computing node, so that the subtasks with the bucket identifier can be scheduled to the corresponding database or computing node according to the database or computing node pre-associated with the bucket identifier, so as to realize task allocation and ensure the load balancing of the database or computing node.

[0077] In the embodiment of the present disclosure, the computing task is circled and divided by parameterized control mode, and the tasks with different bucket labels are scheduled to different databases or computing nodes, so as to achieve the load balancing of the database or computing node.

[0078] Figure 5 is a structural schematic diagram of the parameterized control device according to the embodiment of the present disclosure, and the embodiment can be applied to the case of parameter configuration of the computing task related to automatic driving. Referring to Figure 5 , the device comprises:

[0079] The loading module 501 is configured to load the candidate parameter configuration unit from the cloud for the generated computing task;

[0080] The screening module 502 is configured to select at least one target parameter configuration unit matched with the computing task from the candidate parameter configuration unit;

[0081] The parameter configuration module 503 is configured to update the parameter content included in the target parameter configuration unit to the computing task.

[0082] On the basis of the above embodiment, the candidate parameter configuration unit further includes a priority and a matching rule;

[0083] The screening module is further configured to:

[0084] sort the candidate parameter configuration units according to the priority of the candidate parameter configuration units;

[0085] According to the sorting result, the candidate parameter configuration units are traversed in sequence, and the following operations are performed when each candidate parameter configuration unit is traversed until the traversal ends:

[0086] determine whether the computing task meets the matching rule included in the candidate parameter configuration unit;

[0087] If yes, the candidate parameter configuration unit is taken as the target parameter configuration unit, and the next candidate parameter configuration unit is started to be traversed;

[0088] If no, the next candidate parameter configuration unit is directly traversed.

[0089] On the basis of the above embodiment, the parameter configuration module is further configured to:

[0090] update the parameter content in each target parameter configuration unit to the computing task in sequence according to the priority from low to high; wherein, for the same parameter, the parameter content with high priority covers the parameter content with low priority.

[0091] On the basis of the above embodiment, the method further comprises:

[0092] The obtaining module is configured to obtain the matching rule, the priority and the parameter content constructed by the user for any type of computing task; wherein, the matching rule is tree structure data, and the root node and the intermediate parent node of the tree structure are logical operators, and the other leaf nodes are matching conditions;

[0093] The uploading module is configured to construct the parameter configuration unit according to the matching rule, the priority and the parameter content, and upload the constructed parameter configuration unit to the cloud as the candidate parameter configuration unit.

[0094] On the basis of the above-mentioned embodiment, optionally, the candidate parameter configuration unit further comprises a hit probability value, and the hit probability value is used to determine whether the computing task can hit the candidate parameter configuration unit.

[0095] On the basis of the above-mentioned embodiment, optionally, the matching rule in the candidate parameter configuration unit is a matching rule for task bounding and segmentation; and each computing task comprises a plurality of subtasks.

[0096] The apparatus further comprises:

[0097] A determination module is configured to determine, for any computing task in the global task, a matching rule for task bounding and segmentation that is satisfied by the computing task.

[0098] A distribution module is configured to uniformly distribute the subtasks comprised in the computing task into a plurality of task buckets under the matching rule, and add a corresponding bucket identifier to the subtasks in each task bucket.

[0099] A scheduling module is configured to schedule the subtasks with the bucket identifier to corresponding databases or computing nodes according to the databases or computing nodes that are pre-associated with the bucket identifier.

[0100] The parameterized control apparatus provided in the embodiments of the present disclosure can execute the parameterized control method provided in any of the embodiments of the present disclosure, and has the corresponding function modules and beneficial effects of the execution method. The contents not described in detail in the present embodiment can refer to the description in any of the method embodiments of the present disclosure.

[0101] In the technical solution of the present disclosure, the acquisition, storage and application of user personal information comply with relevant laws and regulations and do not violate public order and good customs.

[0102] According to the embodiments of the present disclosure, the present disclosure further provides an electronic device, a readable storage medium and a computer program product.

[0103] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present disclosure described and / or claimed in this document.

[0104] As Figure 6As shown, the device 600 includes a computing unit 601 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from the storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0105] Various components in the device 600 are connected to the I / O interface 605, including an input unit 606 such as a keyboard, a mouse, etc., an output unit 607 such as various types of displays, speakers, etc., a storage unit 608 such as a magnetic disk, an optical disk, etc., and a communication unit 609 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0106] The computing unit 601 can be various general and / or special purpose processing components with 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 special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 601 performs various methods and processes described above, such as the parameterized control method. For example, in some embodiments, the parameterized control method can be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the parameterized control method described above can be performed. Alternatively, in other embodiments, the computing unit 601 can be configured to perform the parameterized control method by any other appropriate means, such as by means of firmware.

[0107] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0108] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0109] In the context of the present disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can 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 the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0110] 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 the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; 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 can be received in any form, including acoustic, speech, or tactile input.

[0111] 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 a local area network (LAN), a wide area network (WAN), and the Internet.

[0112] The computer system can 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 can arise by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0113] It should be understood that various forms of flow shown above can be used, with steps reordered, added, or removed. For example, steps recited in the present disclosure can be performed in parallel, in series, or in a different order, without limitation herein, so long as the desired results of the technology of the present disclosure are achieved.

[0114] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above.

Claims

1. A parameterized control method, comprising: loading, for a generated computing task, candidate parameter configuration units from a cloud; selecting, from the candidate parameter configuration units, at least one target parameter configuration unit matching the computing task; updating parameter content included in the target parameter configuration unit to the computing task; wherein the candidate parameter configuration units further include priority and matching rules; selecting, from the candidate parameter configuration units, at least one target parameter configuration unit matching the computing task, comprises: sorting the candidate parameter configuration units according to the priority of the candidate parameter configuration units; according to the sorting result, sequentially traversing the candidate parameter configuration units, and for each traversed candidate parameter configuration unit, performing the following operations until the traversal ends: judging whether the computing task satisfies the matching rule included in the candidate parameter configuration unit; if yes, taking the candidate parameter configuration unit as the target parameter configuration unit, and starting to traverse the next candidate parameter configuration unit; if no, directly traversing the next candidate parameter configuration unit.

2. The method of claim 1, wherein, the updating of the parameter content included in the target parameter configuration unit to the computing task, comprises: sequentially updating the parameter content in each target parameter configuration unit to the computing task in order of priority from low to high; wherein for the same parameter, the parameter content with high priority covers the parameter content with low priority. 3.The method of claim 1, further comprising: obtaining matching rules, priority and parameter content constructed by a user for any type of computing task; wherein the matching rules are tree structure data, and the root node and intermediate parent nodes of the tree structure are logical operators, and other leaf nodes are matching conditions; constructing parameter configuration units according to the matching rules, priority and parameter content, and uploading the constructed parameter configuration units to the cloud as the candidate parameter configuration units. 4.The method of claim 1, wherein the candidate parameter configuration units further include a hit probability value, and the hit probability value is used to determine whether the computing task can hit the candidate parameter configuration unit.

5. The method of claim 1, wherein, the matching rules in the candidate parameter configuration units are matching rules for task bounding and segmentation; and each computing task includes multiple subtasks; the method further comprises: for any computing task in a global task, determining the matching rule for task bounding and segmentation satisfied by the computing task; distributing the subtasks included in the computing task to multiple task buckets under the matching rule, and adding a corresponding bucket identifier to the subtasks in each task bucket; according to a database or a computing node pre-associated with the bucket identifier, scheduling the subtasks with the bucket identifier to the corresponding database or computing node. 6.A parameterized control apparatus, comprising: a loading module configured to load, for a generated computing task, candidate parameter configuration units from a cloud; a screening module configured to select, from the candidate parameter configuration units, at least one target parameter configuration unit matching the computing task; and The parameter configuration module is configured to update parameter content in the target parameter configuration unit to the computing task. The candidate parameter configuration unit further comprises a priority and a matching rule. The screening module is further configured to: sort the candidate parameter configuration units according to the priority of the candidate parameter configuration units; according to the sorting result, sequentially traverse the candidate parameter configuration units, and perform the following operations for each candidate parameter configuration unit until the traversal ends: determine whether the computing task meets the matching rule included in the candidate parameter configuration unit; if yes, the candidate parameter configuration unit is taken as the target parameter configuration unit, and the next candidate parameter configuration unit is started to be traversed; if no, the next candidate parameter configuration unit is directly traversed.

7. The apparatus of claim 6, wherein, The parameter configuration module is further configured to: in the order from low to high priority, sequentially update the parameter content in each target parameter configuration unit to the computing task; wherein, for the same parameter, the parameter content with high priority covers the parameter content with low priority.

8. The apparatus of claim 6, further comprising: an acquisition module configured to acquire a matching rule, a priority and parameter content constructed by a user for any type of computing task; wherein, the matching rule is tree structure data, and the root node and intermediate parent node of the tree structure are logical operators, and other leaf nodes are matching conditions; an uploading module configured to construct a parameter configuration unit according to the matching rule, the priority and the parameter content, and upload the constructed parameter configuration unit to the cloud as the candidate parameter configuration unit.

9. The apparatus of claim 6, the candidate parameter configuration unit further comprises a hit probability value, the hit probability value is used to determine whether the computing task can hit the candidate parameter configuration unit.

10. The apparatus of claim 6, wherein, The matching rule in the candidate parameter configuration unit is a matching rule for task bounding and segmentation; each computing task comprises a plurality of subtasks; The apparatus further comprises: a determination module configured to determine, for any computing task in a global task, a matching rule for task bounding and segmentation met by the computing task; a distribution module configured to distribute the subtasks included in the computing task to a plurality of task buckets under the matching rule, and add a corresponding bucket identifier to the subtasks in each task bucket; a scheduling module configured to schedule the subtasks with the bucket identifier to a corresponding database or computing node according to a database or computing node pre-associated with the bucket identifier.

11. An electronic device, comprising: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the parameterized control method of any one of claims 1-5.

12. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to enable the computer to perform the parameterized control method of any one of claims 1-5.

13. A computer program product comprising a computer program which, when executed by a processor, implements the parameterized control method according to any one of claims 1-5.

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