Multi-task collaborative quantum cloud code graph dynamic generation method and system

Abstract

The invention relates to a multi-task collaborative quantum cloud code graph dynamic generation method and system, and the method comprises the steps: arranging N authorized order items into a code generation task queue according to the check sequence of the N authorized order items checked by a user, and carrying out the code generation task queue for the authorized order items which are not bound with a cloud parameter template, based on the commodity association dimension, the task association dimension and the equipment association dimension, generating a recommendation parameter template as a code generation parameter template, and when a code generation instruction is received, executing a code generation task on N authorized order items in sequence according to a code generation sequence of a code generation task queue, and automatically loading the code generation parameters in the corresponding code generation parameter template to generate a corresponding quantum cloud code graph, and realizing dynamic switching of the code generation task queue according to the new code generation instruction and the new code generation task queue. Therefore, dynamic switching of multiple tasks is achieved, the code generation parameters of the quantum cloud code graph are optimized, the error rate is reduced, and meanwhile the generation quality of the quantum cloud code graph is improved.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method and system for dynamic generation of quantum cloud code and code image through multi-task collaboration. Background Technology

[0002] Quantum cloud codes, as a high-anti-counterfeiting and high-capacity coding technology, are widely used in product traceability, anti-counterfeiting authentication, and logistics tracking. Their core component is the efficient and accurate generation of code images. However, with the increasing scale of product production and the diversification of orders, existing quantum cloud code generation technologies are gradually revealing numerous shortcomings, making it difficult to meet the needs of enterprises for efficient production and refined management. Specifically: (a) The code generation device can only process one authorized order item at a time and can only support single-task serial processing, and cannot achieve dynamic switching of multiple tasks; (ii) The generation parameters of quantum cloud code map mostly rely on local manual input or a single cloud template call, which is not only inefficient but also has a high error rate, affecting the generation quality of quantum cloud code map. Summary of the Invention

[0003] The technical problem to be solved by the present invention is: the present invention provides a method and system for dynamic generation of quantum cloud code map by multi-task collaboration, which supports the execution of code generation tasks for multiple authorized order items, and can realize dynamic switching of multiple tasks, optimize the code generation parameters of quantum cloud code map, reduce the error rate, and improve the generation quality of quantum cloud code map.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a method for dynamic generation of quantum cloud code graphs through multi-task collaboration, comprising: Retrieve the N authorized order items selected by the user, and arrange the N authorized order items into a code generation task queue according to the user's selection order; Determine whether there are any authorized order items in the code generation task queue that are not bound to cloud parameter templates. If they exist, mark the authorized order items that are not bound to cloud parameter templates as order items to be configured, generate recommended parameter templates for the order items to be configured based on preset dimensions, and use the recommended parameter templates as the code generation parameter templates for the order items to be configured. If they do not exist, directly use the cloud parameter templates bound to each authorized order item as the corresponding code generation parameter templates. The preset dimensions are product association dimension, task association dimension, and device association dimension. When a code generation instruction is received from the user, the code generation task is executed sequentially on N authorized order items according to the code generation order of the code generation task queue. For each authorized order item, the code generation parameters in the corresponding code generation parameter template are automatically loaded to generate the corresponding quantum cloud code map. When the code generation task for all authorized order items in the code generation task queue is completed, it is determined whether there is a new code generation task queue and a new code generation instruction. If there is, the new code generation task queue is automatically switched to execute the new code generation task according to the new code generation instruction, until all code generation task queues are completed, realizing the dynamic switching of code generation task queues.

[0005] The beneficial effects of this invention are as follows: It enables the execution of code generation tasks for multiple authorized order items using a code generation task queue, overcoming the limitation of existing technologies where a device can only process one authorized order item at a time. Furthermore, it supports dynamic switching between multiple code generation task queues, ensuring continuous execution of code generation tasks and improving the efficiency and stability of quantum cloud code generation. A dual strategy of automatic parameter template recommendation and direct reuse of cloud parameter templates is employed. For authorized order items not bound to cloud parameter templates, recommended parameter templates are generated without manual configuration. These recommended templates are generated based on product association, task association, and device association dimensions, improving their objectivity and rationality. Simultaneously, for authorized order items already bound to cloud parameter templates, their cloud parameter templates are directly reused, simplifying the parameter configuration process, reducing error rates, and improving the quality of subsequent quantum cloud code generation.

[0006] Optionally, the step of generating the recommended parameter template for the order item to be configured based on preset dimensions includes: Based on the product association dimension, extract the product information of the order item to be configured, extract the historical parameter template that is the same as the product information from the local database, and use the historical parameter template as the product association parameter template. The product information includes product type and packaging specifications. Based on the task association dimension, it is determined whether there is a preceding order item for the order item to be configured. If there is, the cloud parameter template bound to the preceding order item is used as the task association parameter template. The preceding order item is an authorized order item that is located before the order item to be configured in the code generation task queue and has been bound to a cloud parameter template. Based on the device association dimension, the parameter range of each parameter in the local device parameter template is obtained. Based on the parameter range, each parameter in the product association parameter template and each parameter in the task association parameter template are filtered respectively, and parameters that exceed the parameter range are removed to obtain the filtered product association parameter template and the filtered task association parameter template. Extract core parameter items from the filtered product association parameter template, and extract collaborative parameter items that do not conflict with the core parameter items from the filtered task association parameter template. Generate a set of recommended parameter templates based on the core parameter items and the collaborative parameter items. The set of recommended parameter templates contains at least one recommended parameter template. Each recommended parameter template in the recommended parameter template set is scored according to a preset scoring index, and the optimal recommended parameter template is selected based on the scoring results.

[0007] As described above, historical parameter templates are reused based on the product information of the order item to be configured, and cloud parameter templates of previous order items are reused according to the order of authorized order items in the code generation task queue. This reduces redundant parameter configuration and solves the problem of low historical parameter reuse rate in existing technologies. Furthermore, each parameter in the product-related parameter template and each parameter in the task-related parameter template are filtered separately by the parameter range of each parameter in the local device parameter template. This ensures that the obtained recommended parameter template is compatible with the capabilities of the local device, avoids code generation interruption due to parameters exceeding the parameter range, and improves the code generation efficiency of the quantum cloud code map.

[0008] Optionally, if present, the step of using the cloud parameter template bound to the preceding order item as the task association parameter template includes: Determine whether the number of the preceding order items is greater than 1. If so, use the cloud parameter template bound to the preceding order item closest to the order item to be configured as the task association parameter template. or All common parameters in the cloud parameter templates bound to the pre-order items are integrated into a task-related parameter template.

[0009] As described above, when multiple preceding order items exist, various cloud parameter templates are provided to enhance flexibility. Selecting the cloud parameter template closest to the order item to be configured ensures the continuity of adjacent authorized order items in the same code generation task queue, adapting to continuous production scenarios. Integrating common parameters from the cloud parameter templates bound to all preceding order items improves the universality of task-related parameter templates.

[0010] Optionally, the preset scoring indicators include product matching indicators and historical usage indicators. The step of scoring each recommendation parameter template in the recommendation parameter template set according to the preset scoring indicators, and obtaining and selecting the optimal recommendation parameter template based on the scoring results, includes: Based on the product matching index, the core parameter items in each recommended parameter template are matched with the product information of the order item to be configured to obtain the corresponding matching quantity. The matching quantity is then input into the first formula for calculation to obtain the product matching degree of each recommended parameter template. The first formula is: ; in, This indicates the product matching degree of the recommended parameter template i. This indicates the number of matches for the recommended parameter template i. This represents the total number of core parameters in the recommended parameter template i; Based on the historical usage metrics, the historical usage count of each recommended parameter template is obtained. Simultaneously, the total usage count of all historical raw code parameter templates with the same product type as the order item to be configured is obtained. The total usage count and the historical usage count of each recommended parameter template are then input into a second formula for calculation to obtain the historical matching degree of each recommended parameter template. The second formula is: ; in, This represents the historical matching degree of the recommended parameter template i. Q represents the historical usage count of the recommended parameter template i, and Q represents the total historical usage count of all raw code parameter templates that are of the same product type as the order item to be configured. The historical matching degree and corresponding product matching degree of each recommended parameter template are input one by one into the third formula for calculation, so as to score each recommended parameter template and obtain the score result of each recommended parameter template. The third formula is: ; in, This represents the rating result of the recommended parameter template i. Indicates the first weight. Indicates the second weight; The recommended parameter template corresponding to the highest rating result is selected from all the rating results as the optimal recommended parameter template.

[0011] As described above, the product matching degree reflects the compatibility between the core parameters of the recommended parameter template and the product information of the order item to be configured, while the historical matching degree reflects the actual usage of the recommended parameter template. By using this method to select the optimal recommended parameter template, the problem of subjectivity in the selection is avoided, and the accuracy and practicality of the recommended parameter template are further improved.

[0012] Optionally, using the recommended parameter template as the generation parameter template for the order item to be configured includes: The recommended parameter template is sent to the user, and the user selects the inheritance mode for the recommended parameter template. The inheritance mode includes full inheritance, partial inheritance, and custom modification. When the inheritance mode is full inheritance, the recommended parameter template is directly used as the generated code parameter template for the order item to be configured; When the inheritance mode is partial inheritance, the parameters revised by the user are recorded in real time. The parameter range of each parameter in the local device parameter template is obtained based on the device association dimension. The parameters revised by the user are verified for compliance according to the parameter range. If the compliance verification passes, the parameters revised by the user are updated to the recommended parameter template to obtain the updated recommended parameter template. The updated recommended parameter template is used as the code parameter template for the order item to be configured. If the compliance verification fails, a pop-up reminder is issued and the range of parameters that can be revised is marked.

[0013] As described above, the system provides users with two flexible inheritance modes for recommended parameter templates to optimize user experience. For partial inheritance, compliance checks are performed to ensure the efficiency of subsequent quantum cloud code generation. In cases where compliance checks fail, a pop-up reminder will be issued and the range of parameters that can be revised will be indicated, thus reducing the operational threshold for users.

[0014] Optionally, the step of sequentially executing code generation tasks on N authorized order items according to the code generation order of the code generation task queue includes: Obtain the timestamp of the code generation instruction, and simultaneously obtain the authorization validity period, remaining code quantity, and number of codes to be generated for each authorized order item; Based on the authorization validity period, remaining code quantity, number of pending codes, and timestamp of each authorized order item, dual constraints are generated for each authorized order item. Based on the dual constraints, the corresponding authorized order item is validated to determine whether it meets the corresponding dual constraints. If it does, the authorized order item passes the validity check; otherwise, it fails the validity check. The dual constraints include a first constraint and a second constraint. The first constraint is that the authorization validity period of each authorized order item covers the timestamp. The second constraint is that the remaining code quantity for each authorized order item is greater than 0 and greater than the corresponding number of codes to be generated; Generate code tasks for authorized order items that have passed validity verification in the code generation task queue according to the code generation order.

[0015] As described above, a validity check of authorized order items has been added before executing the code generation task. That is, the validity check is performed by constructing a dual constraint condition based on the authorization validity period and the remaining code quantity. This can avoid the compliance risk of authorization expiration and prevent production interruption due to insufficient code quantity during the execution of the code generation task. Moreover, each authorized order item has its own unique dual constraint condition, which improves the accuracy of the validity check and further improves the efficiency of subsequent quantum cloud code generation.

[0016] Optionally, before generating the dual constraint conditions for each authorized order item based on the authorization validity period, remaining code quantity, number of pending codes, and the timestamp for each authorized order item, the following steps are included: Determine whether a user's order replacement request has been received. If so, obtain the original code quantity of the authorized order item corresponding to the order replacement request, regenerate the temporary authorization code quantity based on the original code quantity and a first preset ratio, and add the temporary authorization code quantity to the remaining code quantity of the authorized order item corresponding to the order replacement request to obtain the remaining code quantity after addition. or Determine whether there exists an authorized order item in the code generation task queue that has the same product information as the authorized order item corresponding to the order replenishment application, and whose remaining code quantity is greater than the corresponding number of codes to be generated and whose difference between the remaining code quantity and the corresponding number of codes to be generated exceeds a first difference threshold. If such an authorized order item exists, then the corresponding authorized order item is designated as a scheduled order item. A second preset proportion of the remaining code quantity is allocated from the scheduled order item and added as a temporary authorized code quantity to the remaining code quantity of the authorized order item corresponding to the order replenishment application, thus obtaining the added remaining code quantity.

[0017] As described above, when a user's order replenishment request is received, temporary authorization codes can be added. This means that the user's temporary order replenishment needs can be met without resubmitting the authorization order, optimizing the user experience. Furthermore, two methods for adding temporary authorization codes are provided to improve adaptability. First, temporary authorization codes are generated based on the original code quantity of the authorized order item corresponding to the order replenishment request, ensuring the reasonableness of the temporary authorization code quantity. Second, temporary authorization codes are scheduled for authorized order items in the code generation task queue that have the same product information as the authorized order item corresponding to the order replenishment request, have a remaining code quantity greater than the corresponding number of codes to be generated, and the difference between the remaining code quantity and the corresponding number of codes to be generated exceeds a first difference threshold. This improves the efficient utilization of existing resources and avoids wasting code quantity.

[0018] Optionally, the step of automatically loading the corresponding raw code parameters from the raw code parameter template for each authorized order item to generate the corresponding quantum cloud code image includes: During the generation of the quantum cloud code map for each authorized order item, the operating status of the code generation device and the quality of the generated quantum cloud code map are synchronously and in real time, and the corresponding operating status detection results and code generation quality detection results are obtained. Based on the running status detection result and the code quality detection result of each authorized order item, it is determined whether the code parameters in the corresponding code parameter template need to be dynamically adjusted. If the running status detection result meets the first dynamic adjustment condition and / or the code quality meets the second dynamic adjustment condition, the dynamic adjustment process is triggered to dynamically adjust the code parameters in the corresponding code parameter template to obtain the dynamically adjusted code parameters, and the corresponding quantum cloud code map is generated based on the dynamically adjusted code parameters. The first dynamic adjustment condition is: the CPU load in the operation status detection result exceeds a first load threshold, and the time exceeding the first load threshold exceeds a first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the first remaining amount threshold. or The printing error rate in the operational status detection results exceeds the first error threshold; The second dynamic adjustment condition is: the clarity of the code image in the generated code quality detection result is lower than the first clarity threshold; The number of missing code points in the code quality detection results exceeds the first missing threshold.

[0019] As described above, by synchronously and in real-time detecting the operating status of the code generation device and the quality of the generated quantum cloud code image, the code generation parameters in the code generation parameter template can be dynamically adjusted. This solves the problem that the code generation parameters in the existing technology are fixed and cannot cope with the fluctuations in the status of the code generation device and the changes in the quality of the code image. It improves the production stability and adaptability of the quantum cloud code image and can adapt to complex and ever-changing production environments.

[0020] Optionally, obtaining the corresponding running status detection results and code quality detection results includes: Based on the running status detection results and code quality detection results of each authorized order item, it is determined whether an abnormal warning needs to be issued. If the running status detection results reach the first warning trigger condition and / or the code quality detection results reach the second warning trigger condition, an abnormal warning is triggered. The first warning trigger condition is: The CPU load in the operation status detection result exceeds the second load threshold, and the time exceeding the second load threshold exceeds the second time threshold, wherein the second load threshold is different from the first load threshold, and the second time threshold is different from the first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the second remaining amount threshold, wherein the second remaining amount threshold is different from the first remaining amount threshold; or The printing error rate in the operational status detection results exceeds the second error threshold; The second warning trigger condition is: The failure rate in the quality inspection results of the generated code exceeds the first failure threshold.

[0021] As described above, the generation process of quantum cloud code maps is monitored in real time, and anomaly warnings are supported to further ensure the production stability of quantum cloud code maps.

[0022] In a second aspect, the present invention provides a multi-task collaborative quantum cloud code dynamic generation system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the multi-task collaborative quantum cloud code dynamic generation method described in the first aspect.

[0023] The technical effects of the multi-task collaborative quantum cloud code dynamic generation system provided in the second aspect are the same as those of the multi-task collaborative quantum cloud code dynamic generation method provided in the first aspect. Attached Figure Description

[0024] Figure 1 This is a flowchart of a multi-task collaborative quantum cloud code dynamic generation method provided in this embodiment; Figure 2 This is a schematic diagram of the overall process of a multi-task collaborative quantum cloud code dynamic generation method provided in this embodiment; Figure 3 This is a flowchart illustrating the abnormality warning and dynamic adjustment process involved in this embodiment; Figure 4 This is a schematic diagram of the structure of a multi-task collaborative quantum cloud code dynamic generation system provided in this embodiment.

[0025] [Explanation of Labels in the Attached Image] 1. A multi-task collaborative quantum cloud code and code map dynamic generation system; 2. Processor; 3. Memory. Detailed Implementation

[0026] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0027] Example 1 Please refer to Figures 1 to 3 This invention provides a method for dynamic generation of quantum cloud code maps through multi-task collaboration, comprising the following steps: S1. Obtain the N authorized order items selected by the user, and arrange the N authorized order items into a code generation task queue according to the user's selection order; In this embodiment, as Figure 2 As shown, the system provides users with an authorization application and device management interface, as well as cloud parameter template management functionality. Users can create and maintain multiple cloud parameter templates, which can be divided into regular parameter templates and masked parameter templates. These templates can be directly linked to specific order items during authorization applications. Users can select multiple authorized order items at once. The system retrieves the N selected authorized order items and arranges them into a code generation task queue according to the user's selection order, where N is a positive integer.

[0028] S2. Determine whether there are any authorized order items in the code generation task queue that are not bound to cloud parameter templates. If they exist, mark the authorized order items that are not bound to cloud parameter templates as order items to be configured, generate a recommended parameter template for the order items to be configured based on preset dimensions, and use the recommended parameter template as the code generation parameter template for the order items to be configured. If they do not exist, directly use the cloud parameter template bound to each authorized order item as the corresponding code generation parameter template. The preset dimensions are product association dimension, task association dimension, and device association dimension. In this embodiment, as Figure 2 As shown, if there are authorized order items in the code generation task queue that are not bound to cloud parameter templates, a corresponding recommended parameter template will be automatically generated for them. The authorized order items that are not bound to cloud parameter templates will be marked as order items to be configured. Recommended parameter templates for order items to be configured will be generated based on product association, task association, and device association dimensions. The recommended parameter templates will be used as the code generation parameter templates for order items to be configured. Conversely, if an authorized order item is already bound to a cloud parameter template, the bound cloud parameter template will be directly reused and used as the corresponding code generation parameter template.

[0029] At this point, the step S2 of generating the recommended parameter template for the order item to be configured based on the preset dimensions includes: S21. Extract the product information of the order item to be configured based on the product association dimension, extract the historical parameter template that is the same as the product information from the local database, and use the historical parameter template as the product association parameter template. The product information includes product type and packaging specifications. S22. Based on the task association dimension, determine whether there is a preceding order item for the order item to be configured. If there is, use the cloud parameter template bound to the preceding order item as the task association parameter template. The preceding order item is an authorized order item that is located before the order item to be configured in the code generation task queue and has been bound to a cloud parameter template. In this embodiment, as Figure 2 As shown, product information for the order item to be configured is extracted based on the product association dimension. Product information includes, but is not limited to, product type and packaging specifications. Historical parameter templates identical to the product information are extracted from the local database and used as product association parameter templates. It should be further noted that if no historical parameter template with exactly the same product type and packaging specifications exists in the local database, the template with the same product type is searched first, then the similarity of the packaging specifications is calculated, and the historical parameter template with the highest similarity is selected as the product association parameter template. Based on the task association dimension, it is determined whether the order item to be configured has a preceding order item, i.e., an authorized order item that precedes the order item to be configured in the same code generation task queue and has been bound to a cloud parameter template. If such an order item exists, the cloud parameter template bound to the preceding order item is used as the task association parameter template.

[0030] At this point, the step S22, which states that if the cloud parameter template bound to the preceding order item exists, will be used as the task association parameter template, includes: S221. Determine whether the number of the preceding order items is greater than 1. If so, use the cloud parameter template bound to the preceding order item closest to the order item to be configured as the task association parameter template. or S222. Integrate the common parameters in the cloud parameter templates bound to all the preceding order items into a task-related parameter template.

[0031] In this embodiment, if the number of preceding order items is greater than 1, that is, there is more than one preceding order item, two different methods are provided for selecting the task association parameter template. Method 1: Use the cloud parameter template bound to the preceding order item closest to the order item to be configured as the task association parameter template. The distance here refers to the order distance between the two in the code generation task queue. Method 2: Integrate the common parameters in the cloud parameter templates bound to all preceding order items into the task association parameter template.

[0032] S23. Based on the device association dimension, obtain the parameter range of each parameter in the local device parameter template. Based on the parameter range, filter each parameter in the product association parameter template and each parameter in the task association parameter template respectively, and remove parameters that exceed the parameter range to obtain the filtered product association parameter template and the filtered task association parameter template. S24. Extract core parameter items from the filtered product association parameter template, and extract collaborative parameter items that do not conflict with the core parameter items from the filtered task association parameter template. Generate a recommended parameter template set based on the core parameter items and the collaborative parameter items. The recommended parameter template set contains at least one recommended parameter template. S25. Score each recommended parameter template in the set of recommended parameter templates according to the preset scoring index, and select the optimal recommended parameter template based on the scoring results.

[0033] In this embodiment, as Figure 2 As shown, the parameter range of each parameter in the local device parameter template is obtained based on the device association dimension. The parameters in the local device parameter template include, but are not limited to: the maximum DPI of the local code-generating device, the supported code dot size range, the maximum printing area of ​​the connected printer, and consumable compatibility parameters. Based on the parameter range, each parameter in the product association parameter template and each parameter in the task association parameter template are filtered, removing parameters that exceed the parameter range. If all parameters in a product association parameter template or a task association parameter template exceed the parameter range, the entire product association parameter template or the entire task association parameter template is directly removed, resulting in filtered product association parameter templates and filtered task association parameter templates.

[0034] Core parameter items are extracted from the filtered product-related parameter template. These core parameter items include, but are not limited to, code point size, encoding density, image size, and device computing power limit. Simultaneously, non-conflicting collaborative parameter items are extracted from the filtered task-related parameter template. These collaborative parameter items include, but are not limited to, output format, generation thread, and cache time. At least one recommended parameter template is generated based on the core parameter items and collaborative parameter items. All recommended parameter templates constitute a recommended parameter template set. The rules for determining whether there is a conflict between core parameter items and collaborative parameter items are as follows: 1. Functional correlation judgment rules: Whether the function of the collaborative parameter item is mutually exclusive with the function of the core parameter item. For example, whether the parallel processing logic corresponding to the number of generation threads conflicts with the precise generation logic of code point size. 2. Numerical compatibility judgment rules: Whether the current value of the collaborative parameter item exceeds the compatibility range of the core parameter item, for example: whether the maximum value of the generated thread exceeds the upper limit of the device's computing power.

[0035] Each recommended parameter template in the recommended parameter template set is scored according to the preset scoring criteria, and the optimal recommended parameter template is selected based on the scoring results.

[0036] At this point, step S25 includes: S251. Match the core parameter items in each recommended parameter template with the product information of the order item to be configured according to the product matching index to obtain the corresponding matching quantity. Input the matching quantity one by one into the first formula for calculation to obtain the product matching degree of each recommended parameter template. The first formula is: ; in, This indicates the product matching degree of the recommended parameter template i. This indicates the number of matches for the recommended parameter template i. This represents the total number of core parameters in the recommended parameter template i; S252. Obtain the historical usage count of each recommended parameter template based on the historical usage metrics, and simultaneously obtain the total usage count of all historical raw code parameter templates with the same product type as the order item to be configured. Input the total usage count and the historical usage count of each recommended parameter template into the second formula for calculation to obtain the historical matching degree of each recommended parameter template. The second formula is: ; in, This represents the historical matching degree of the recommended parameter template i. Q represents the historical usage count of the recommended parameter template i, and Q represents the total historical usage count of all raw code parameter templates that are of the same product type as the order item to be configured. S253. Input the historical matching degree and corresponding product matching degree of each recommended parameter template into the third formula for calculation, so as to score each recommended parameter template and obtain the score result of each recommended parameter template. The third formula is: ; in, This represents the rating result of the recommended parameter template i. Indicates the first weight. Indicates the second weight; S254. Select the recommended parameter template corresponding to the highest rating result from all the rating results as the optimal recommended parameter template.

[0037] In this embodiment, as Figure 2 As shown, the preset scoring indicators include product matching indicators and historical usage indicators. Product matching reflects the compatibility between the core parameters of the recommended parameter template and the product information of the order item to be configured, while historical matching reflects the actual usage of the recommended parameter template. Based on the product matching indicators, the core parameters of each recommended parameter template are matched with the product information of the order item to be configured, resulting in a corresponding number of matches. This matching is based on a preset indirect association mapping relationship, which establishes a relationship between product information and parameters based on historical generated code data. The obtained number of matches is input into the first formula for calculation to obtain the product matching degree of each recommended parameter template. Based on the historical usage indicators, the historical usage count of each recommended parameter template is obtained, along with the total usage count of all historical generated code parameter templates of the same product type as the order item to be configured. All historical generated code parameter templates include historically generated recommended parameter templates and historically bound cloud parameter templates. The total usage count and the historical usage count of each recommended parameter template are input into the second formula for calculation to obtain the historical matching degree of each recommended parameter template. The historical matching degree and corresponding product matching degree of each recommended parameter template are input one by one into the third formula for calculation, thereby scoring each recommended parameter template and obtaining a score result for each template. The first weight in the third formula is 0.6, and the second weight is 0.4, which can be adjusted according to actual needs.

[0038] At this point, step S2, which involves using the recommended parameter template as the code parameter template for the order item to be configured, includes: S26. Send the recommended parameter template to the user and receive the inheritance mode selected by the user for the recommended parameter template. The inheritance mode includes full inheritance, partial inheritance and custom modification. S27. When the inheritance mode is full inheritance, the recommended parameter template is directly used as the generated code parameter template of the order item to be configured. S28. When the inheritance mode is partial inheritance, the parameters revised by the user are recorded in real time. The parameter range of each parameter in the local device parameter template is obtained based on the device association dimension. The parameters revised by the user are verified for compliance according to the parameter range. If the compliance verification passes, the parameters revised by the user are updated to the recommended parameter template to obtain the updated recommended parameter template. The updated recommended parameter template is used as the code parameter template for the order item to be configured. If the compliance verification fails, a pop-up reminder is issued and the range of parameters that can be revised is marked.

[0039] In this embodiment, as Figure 2 As shown, the generated recommended parameter template will be sent to the user, who can choose different inheritance modes. If the inheritance mode is full inheritance, the recommended parameter template will be directly used as the raw code parameter template for the order item to be configured. If the inheritance mode is partial inheritance, the parameters revised by the user will be recorded in real time, and compliance verification will be performed on the revised parameters. The compliance verification method is the same as the filtering process in step S23. Based on the device association dimension, the parameter range of each parameter in the local device parameter template will be obtained. The revised parameters will be verified according to the parameter range. If the compliance verification passes, that is, the revised parameters of the user are within the parameter range, the revised parameters of the user will be updated in the recommended parameter template, and the updated recommended parameter template will be used as the raw code parameter template for the order item to be configured. Otherwise, if the compliance verification fails, a pop-up reminder will be issued and the range of parameters that can be revised will be marked for the user's reference, and the user can revise again.

[0040] S3. When a code generation instruction is received from the user, the code generation task is executed sequentially on N authorized order items according to the code generation order of the code generation task queue. For each authorized order item, the code generation parameters in the corresponding code generation parameter template are automatically loaded to generate the corresponding quantum cloud code map. When the code generation task of all authorized order items in the code generation task queue is completed, it is determined whether there is a new code generation task queue and a new code generation instruction. If there is, the new code generation task queue is automatically switched to execute the new code generation task according to the new code generation instruction, until all code generation task queues are completed, realizing the dynamic switching of code generation task queues.

[0041] In this embodiment, as Figure 2 As shown, when a user-issued code generation command is received, the code generation task is executed sequentially on N authorized order items according to the code generation order in the code generation task queue. The code generation order is the order of the authorized order items in the queue. If there are authorized order items with priority, the code generation task is executed on those with priority. For each authorized order item, the corresponding code generation parameters in the corresponding code generation parameter template are automatically loaded to generate the corresponding quantum cloud code map. When the code generation tasks for all authorized order items in the queue are completed, it is determined whether a switch is needed. If a new code generation task queue and a new code generation command exist, the system automatically switches to the new queue to execute the new code generation task, achieving dynamic switching of the code generation task queue. If only a new code generation task queue exists but no new code generation command is received, the system remains in standby mode. If no new code generation task queue exists, the code generation process terminates.

[0042] At this point, step S3, which involves sequentially executing code generation tasks on the N authorized order items according to the code generation order of the code generation task queue, includes: S31. Obtain the timestamp of the code generation instruction, and at the same time obtain the authorization validity period, remaining code quantity, and number of codes to be generated for each authorized order item; S32. Generate dual constraints for each authorized order item based on the authorization validity period, remaining code quantity, number of pending codes, and the timestamp. Perform validity verification on the corresponding authorized order item based on the dual constraints to determine whether the authorized order item meets the corresponding dual constraints. If it does, the authorized order item passes the validity verification; otherwise, the authorized order item fails the validity verification. The dual constraints include a first constraint and a second constraint. The first constraint is that the authorization validity period of each authorized order item covers the timestamp. The second constraint is that the remaining code quantity for each authorized order item is greater than 0 and greater than the corresponding number of codes to be generated; In this embodiment, as Figure 2 As shown, before executing the code generation task, the validity of each authorized order item is verified. Based on the obtained authorization validity period, remaining code quantity, number of codes to be generated, and the timestamp of the code generation instruction for each authorized order item, a double constraint condition is constructed for each authorized order item. The validity of the corresponding authorized order item is then verified based on this double constraint condition. If the authorization validity period of the authorized order item covers the timestamp, and the remaining code quantity is greater than 0 and greater than the corresponding number of codes to be generated, then the authorized order item satisfies the double constraint condition and passes the validity verification; otherwise, it fails the validity verification.

[0043] At this point, before generating the dual constraint conditions for each authorized order item based on the authorization validity period, remaining code quantity, number of pending codes, and the timestamp in step S32, the following is included: S321. Determine whether a user's order replenishment request has been received. If so, obtain the original code quantity of the authorized order item corresponding to the order replenishment request, regenerate the temporary authorization code quantity based on the original code quantity and the first preset ratio, and add the temporary authorization code quantity to the remaining code quantity of the authorized order item corresponding to the order replenishment request to obtain the remaining code quantity after addition. or S322. Determine whether there exists an authorized order item in the code generation task queue that has the same product information as the authorized order item corresponding to the order replenishment application, and whose remaining code quantity is greater than the corresponding number of codes to be generated and whose difference between the remaining code quantity and the corresponding number of codes to be generated exceeds a first difference threshold. If such an authorized order item exists, the corresponding authorized order item is designated as a scheduled order item. A second preset proportion of the remaining code quantity is allocated from the scheduled order item and added as a temporary authorized code quantity to the remaining code quantity of the authorized order item corresponding to the order replenishment application, thereby obtaining the added remaining code quantity.

[0044] In this embodiment, users can submit temporary order replenishment requests. When a user's order replenishment request is received, a temporary authorization code quantity can be added, and two methods for adding the temporary authorization code quantity are provided. Method 1: Obtain the original code quantity of the authorized order item corresponding to the order replenishment request, and regenerate the temporary authorization code quantity based on the original code quantity and a first preset ratio, where the first preset ratio is 50%, that is, 50% of the original code quantity is used as the temporary authorization code quantity; Method 2: If there is an authorized order item in the code generation task queue that has the same product information as the authorized order item corresponding to the order replenishment request, and the remaining code quantity is greater than the corresponding number of codes to be generated, and the difference between the remaining code quantity and the corresponding number of codes to be generated exceeds a first difference threshold, then the authorized order item is regarded as a scheduled order item, and the remaining code quantity of the second preset ratio is scheduled from the scheduled order item as the temporary authorization code quantity. At this time, the second preset ratio can be the same as or different from the first preset ratio, and can be set according to the actual situation. The obtained temporary authorization code quantity is added to the remaining code quantity of the authorized order item corresponding to the order replenishment request to obtain the remaining code quantity after addition.

[0045] S33. Generate code tasks for authorized order items that have passed validity verification in the code generation task queue in the order of code generation.

[0046] In this embodiment, as Figure 2 As shown, code generation tasks are executed sequentially on authorized order items that have passed validity checks, according to the code generation task queue.

[0047] At this point, step S3, which involves automatically loading the corresponding raw code parameters from the raw code parameter template for each authorized order item to generate the corresponding quantum cloud code image, includes: S34. During the generation of the quantum cloud code map for each authorized order item, the operating status of the code generation device and the quality of the generated quantum cloud code map are synchronously and in real time detected to obtain the corresponding operating status detection results and code generation quality detection results. In this embodiment, as Figure 2 As shown, during the generation of the quantum cloud code map for each authorized order item, the operating status of the code generation device and the quality of the generated quantum cloud code map are simultaneously monitored in real time, yielding corresponding operating status detection results and code generation quality detection results. These results are used not only for the dynamic adjustment of code generation parameters but also for anomaly warnings. Specifically: At this point, obtaining the corresponding running status detection result and code quality detection result in step S34 includes: S341. Determine whether an abnormal warning is needed based on the running status detection result and the code quality detection result of each authorized order item. If the running status detection result reaches the first warning trigger condition and / or the code quality detection result reaches the second warning trigger condition, then an abnormal warning is triggered. The first warning trigger condition is: The CPU load in the operation status detection result exceeds the second load threshold, and the time exceeding the second load threshold exceeds the second time threshold, wherein the second load threshold is different from the first load threshold, and the second time threshold is different from the first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the second remaining amount threshold, wherein the second remaining amount threshold is different from the first remaining amount threshold; or The printing error rate in the operational status detection results exceeds the second error threshold; The second warning trigger condition is: The failure rate in the quality inspection results of the generated code exceeds the first failure threshold.

[0048] In this embodiment, as Figure 3 As shown, if the operation status detection result meets the first warning trigger condition, namely: if the CPU load in the operation status detection result exceeds the second load threshold, and the time exceeding the second load threshold exceeds the second time threshold; or, the consumable balance is lower than the second balance threshold; or, the printing error rate exceeds the second error threshold, then it is considered that the first warning trigger condition has been met, and an abnormal warning is triggered. The second load threshold is 70%, the first time threshold is 3 minutes, the second balance threshold is 15%, and the second error threshold is 0.3%.

[0049] and / or If the quality inspection result of the generated code reaches the second warning trigger threshold, that is, if the non-compliance rate in the generated code quality inspection result exceeds the first non-compliance threshold, an anomaly warning is triggered, where the first non-compliance threshold is 2%. All thresholds in this embodiment can be adjusted according to actual conditions. The methods for triggering anomaly warnings include, but are not limited to, pop-ups, notification bars, SMS messages, and voice broadcasts. Furthermore, the processing results of anomaly warnings are automatically recorded and stored in the cloud for subsequent traceability.

[0050] S35. Based on the running status detection result and the code quality detection result of each authorized order item, determine whether it is necessary to dynamically adjust the code parameters in the corresponding code parameter template. If the running status detection result meets the first dynamic adjustment condition and / or the code quality meets the second dynamic adjustment condition, then trigger the dynamic adjustment process, dynamically adjust the code parameters in the corresponding code parameter template, obtain the dynamically adjusted code parameters, and continue to generate the corresponding quantum cloud code map based on the dynamically adjusted code parameters. The first dynamic adjustment condition is: the CPU load in the operation status detection result exceeds a first load threshold, and the time exceeding the first load threshold exceeds a first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the first remaining amount threshold. or The printing error rate in the operational status detection results exceeds the first error threshold; The second dynamic adjustment condition is: the clarity of the code image in the generated code quality detection result is lower than the first clarity threshold; The number of missing code points in the code quality detection results exceeds the first missing threshold.

[0051] In this embodiment, as Figure 3 As shown, when the running status detection results meet the first dynamic adjustment condition, namely, the CPU load in the running status detection results exceeds the first load threshold and the time exceeding the first load threshold exceeds the first time threshold, or the printing error rate exceeds the first error threshold, or the consumable balance is lower than the first balance threshold, the mechanism for triggering the abnormal warning is more lenient than the mechanism for triggering the dynamic adjustment process. Therefore, the first load threshold is not only different from the second load threshold, but also higher than the second load threshold, and the first time threshold is higher than the second time threshold. For example, if the second load threshold is 70%, then the first load threshold is 80%; if the second time threshold is 3 minutes, then the first time threshold is 5 minutes. That is, the abnormal warning is triggered first to remind the user to make adjustments. If the user does not handle the abnormal warning, the dynamic adjustment process is automatically triggered to prevent further deterioration. Similarly, the first balance threshold is lower than the second balance threshold. For example, if the second balance threshold is 15%, then the first balance threshold is 10%. The first error threshold is higher than the second error threshold. For example, if the second error threshold is 0.3%, then the first error threshold is 0.4%.

[0052] Example 2 Please refer to Figure 4The present invention provides a multi-task collaborative quantum cloud code dynamic generation system 1, including a memory 3, a processor 2, and a computer program stored in the memory 3 and run on the processor 2. When the processor 2 executes the computer program, it implements the steps in Embodiment 1.

[0053] Since the systems / devices described in the above embodiments of the present invention are systems / devices used to implement the methods of the above embodiments of the present invention, those skilled in the art can understand the specific structure and modifications of the systems / devices based on the methods described in the above embodiments of the present invention, and therefore will not be repeated here. All systems / devices used in the methods of the above embodiments of the present invention fall within the scope of protection of the present invention.

[0054] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0056] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0057] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0058] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0059] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A method for dynamic generation of quantum cloud code maps through multi-task collaboration, characterized in that, include: Retrieve the N authorized order items selected by the user, and arrange the N authorized order items into a code generation task queue according to the user's selection order; Determine whether there are any authorized order items in the code generation task queue that are not bound to cloud parameter templates. If they exist, mark the authorized order items that are not bound to cloud parameter templates as order items to be configured, generate recommended parameter templates for the order items to be configured based on preset dimensions, and use the recommended parameter templates as the code generation parameter templates for the order items to be configured. If they do not exist, directly use the cloud parameter templates bound to each authorized order item as the corresponding code generation parameter templates. The preset dimensions are product association dimension, task association dimension, and device association dimension. When a code generation instruction is received from the user, the code generation task is executed sequentially on N authorized order items according to the code generation order of the code generation task queue. For each authorized order item, the code generation parameters in the corresponding code generation parameter template are automatically loaded to generate the corresponding quantum cloud code map. When the code generation task for all authorized order items in the code generation task queue is completed, it is determined whether there is a new code generation task queue and a new code generation instruction. If there is, the new code generation task queue is automatically switched to execute the new code generation task according to the new code generation instruction, until all code generation task queues are completed, realizing the dynamic switching of code generation task queues.

2. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 1, characterized in that, The recommended parameter template for generating the order item to be configured based on preset dimensions includes: Based on the product association dimension, extract the product information of the order item to be configured, extract the historical parameter template that is the same as the product information from the local database, and use the historical parameter template as the product association parameter template. The product information includes product type and packaging specifications. Based on the task association dimension, it is determined whether there is a preceding order item for the order item to be configured. If there is, the cloud parameter template bound to the preceding order item is used as the task association parameter template. The preceding order item is an authorized order item that is located before the order item to be configured in the code generation task queue and has been bound to a cloud parameter template. Based on the device association dimension, the parameter range of each parameter in the local device parameter template is obtained. Based on the parameter range, each parameter in the product association parameter template and each parameter in the task association parameter template are filtered respectively, and parameters that exceed the parameter range are removed to obtain the filtered product association parameter template and the filtered task association parameter template. Extract core parameter items from the filtered product association parameter template, and extract collaborative parameter items that do not conflict with the core parameter items from the filtered task association parameter template. Generate a set of recommended parameter templates based on the core parameter items and the collaborative parameter items. The set of recommended parameter templates contains at least one recommended parameter template. Each recommended parameter template in the recommended parameter template set is scored according to a preset scoring index, and the optimal recommended parameter template is selected based on the scoring results.

3. The method for dynamic generation of quantum cloud code maps through multi-task collaboration as described in claim 2, characterized in that, If such a template exists, then the cloud parameter template bound to the preceding order item will be used as the task association parameter template, including: Determine whether the number of the preceding order items is greater than 1. If so, use the cloud parameter template bound to the preceding order item closest to the order item to be configured as the task association parameter template. or All common parameters in the cloud parameter templates bound to the pre-order items are integrated into a task-related parameter template.

4. The method for dynamic generation of quantum cloud code maps through multi-task collaboration as described in claim 2, characterized in that, The preset scoring indicators include product matching indicators and historical usage indicators. The step of scoring each recommendation parameter template in the recommendation parameter template set according to the preset scoring indicators, and then selecting the optimal recommendation parameter template based on the scoring results, includes: Based on the product matching index, the core parameter items in each recommended parameter template are matched with the product information of the order item to be configured to obtain the corresponding matching quantity. The matching quantity is then input into the first formula for calculation to obtain the product matching degree of each recommended parameter template. The first formula is: ； in, This indicates the product matching degree of the recommended parameter template i. This indicates the number of matches for the recommended parameter template i. This represents the total number of core parameters in the recommended parameter template i; Based on the historical usage metrics, the historical usage count of each recommended parameter template is obtained. Simultaneously, the total usage count of all historical raw code parameter templates with the same product type as the order item to be configured is obtained. The total usage count and the historical usage count of each recommended parameter template are then input into a second formula for calculation to obtain the historical matching degree of each recommended parameter template. The second formula is: ； in, This represents the historical matching degree of the recommended parameter template i. Q represents the historical usage count of the recommended parameter template i, and Q represents the total historical usage count of all raw code parameter templates that are of the same product type as the order item to be configured. The historical matching degree and corresponding product matching degree of each recommended parameter template are input one by one into the third formula for calculation, so as to score each recommended parameter template and obtain the score result of each recommended parameter template. The third formula is: ； in, This represents the rating result of the recommended parameter template i. Indicates the first weight. Indicates the second weight; The recommended parameter template corresponding to the highest rating result is selected from all the rating results as the optimal recommended parameter template.

5. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 1, characterized in that, The step of using the recommended parameter template as the code parameter template for the order item to be configured includes: The recommended parameter template is sent to the user, and the user selects the inheritance mode for the recommended parameter template. The inheritance mode includes full inheritance, partial inheritance, and custom modification. When the inheritance mode is full inheritance, the recommended parameter template is directly used as the generated code parameter template for the order item to be configured; When the inheritance mode is partial inheritance, the parameters revised by the user are recorded in real time. The parameter range of each parameter in the local device parameter template is obtained based on the device association dimension. The parameters revised by the user are verified for compliance according to the parameter range. If the compliance verification passes, the parameters revised by the user are updated to the recommended parameter template to obtain the updated recommended parameter template. The updated recommended parameter template is used as the code parameter template for the order item to be configured. If the compliance verification fails, a pop-up reminder is issued and the range of parameters that can be revised is marked.

6. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 1, characterized in that, The step of sequentially executing code generation tasks on N authorized order items according to the code generation order of the code generation task queue includes: Obtain the timestamp of the code generation instruction, and simultaneously obtain the authorization validity period, remaining code quantity, and number of codes to be generated for each authorized order item; Based on the authorization validity period, remaining code quantity, number of pending codes, and timestamp of each authorized order item, dual constraints are generated for each authorized order item. Based on the dual constraints, the corresponding authorized order item is validated to determine whether it meets the corresponding dual constraints. If it does, the authorized order item passes the validity check; otherwise, it fails the validity check. The dual constraints include a first constraint and a second constraint. The first constraint is that the authorization validity period of each authorized order item covers the timestamp. The second constraint is that the remaining code quantity for each authorized order item is greater than 0 and greater than the corresponding number of codes to be generated; Generate code tasks for authorized order items that have passed validity verification in the code generation task queue according to the code generation order.

7. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 6, characterized in that, Before generating the dual constraint conditions for each authorized order item based on the authorization validity period, remaining code quantity, number of pending codes, and the timestamp, the following steps are included: Determine whether a user's order replacement request has been received. If so, obtain the original code quantity of the authorized order item corresponding to the order replacement request, regenerate the temporary authorization code quantity based on the original code quantity and a first preset ratio, and add the temporary authorization code quantity to the remaining code quantity of the authorized order item corresponding to the order replacement request to obtain the remaining code quantity after addition. or Determine whether there exists an authorized order item in the code generation task queue that has the same product information as the authorized order item corresponding to the order replenishment application, and whose remaining code quantity is greater than the corresponding number of codes to be generated and whose difference between the remaining code quantity and the corresponding number of codes to be generated exceeds a first difference threshold. If such an authorized order item exists, then the corresponding authorized order item is designated as a scheduled order item. A second preset proportion of the remaining code quantity is allocated from the scheduled order item and added as a temporary authorized code quantity to the remaining code quantity of the authorized order item corresponding to the order replenishment application, thus obtaining the added remaining code quantity.

8. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 1, characterized in that, The automatic loading of the corresponding raw code parameters from the raw code parameter template for each authorized order item to generate the corresponding quantum cloud code image includes: During the generation of the quantum cloud code map for each authorized order item, the operating status of the code generation device and the quality of the generated quantum cloud code map are synchronously and in real time, and the corresponding operating status detection results and code generation quality detection results are obtained. Based on the running status detection result and the code quality detection result of each authorized order item, it is determined whether the code parameters in the corresponding code parameter template need to be dynamically adjusted. If the running status detection result meets the first dynamic adjustment condition and / or the code quality meets the second dynamic adjustment condition, the dynamic adjustment process is triggered to dynamically adjust the code parameters in the corresponding code parameter template to obtain the dynamically adjusted code parameters, and the corresponding quantum cloud code map is generated based on the dynamically adjusted code parameters. The first dynamic adjustment condition is: the CPU load in the operation status detection result exceeds a first load threshold, and the time exceeding the first load threshold exceeds a first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the first remaining amount threshold. or The printing error rate in the operational status detection results exceeds the first error threshold; The second dynamic adjustment condition is: the clarity of the code image in the generated code quality detection result is lower than the first clarity threshold; The number of missing code points in the code quality detection results exceeds the first missing threshold.

9. The method for dynamic generation of quantum cloud code graphs through multi-task collaboration as described in claim 1, characterized in that, The obtained corresponding running status detection results and code quality detection results include: Based on the running status detection results and code quality detection results of each authorized order item, it is determined whether an abnormal warning needs to be issued. If the running status detection results reach the first warning trigger condition and / or the code quality detection results reach the second warning trigger condition, an abnormal warning is triggered. The first warning trigger condition is: The CPU load in the operation status detection result exceeds the second load threshold, and the time exceeding the second load threshold exceeds the second time threshold, wherein the second load threshold is different from the first load threshold, and the second time threshold is different from the first time threshold; or The remaining amount of consumables in the operation status detection result is lower than the second remaining amount threshold, wherein the second remaining amount threshold is different from the first remaining amount threshold; or The printing error rate in the operational status detection results exceeds the second error threshold; The second warning trigger condition is: The failure rate in the quality inspection results of the generated code exceeds the first failure threshold.

10. A multi-task collaborative quantum cloud code dynamic generation system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

Images