CN112685026A - Multi-language-based visual modeling platform and method - Google Patents
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Abstract
The invention discloses a visual modeling platform and a method based on multiple languages, wherein the visual modeling platform comprises: the system comprises a language management module, a data management module and a visual editing module, wherein the language management module is used for providing a plurality of programming languages; the data management module is used for converting different data formats into a uniform data format; the visual editing module is used for displaying the modeling working area, displaying the modeling component list, providing a visualization tool for modeling, defining the attribute of the visualization tool, receiving an external operation instruction for visual modeling, and packaging the edited training model. The invention supports multiple languages and data formats, is convenient for users to flexibly realize the realization of training construction, and has wider application range; the user does not need to care about the specific implementation of code writing, the user can use a simple and convenient visual modeling component and a visual modeling tool to construct, and the purposes of high flexibility and flexibility are achieved.
Description
Technical Field
The invention relates to the technical field of model construction, in particular to a visual modeling platform and a visual modeling method based on multiple languages.
Background
With the arrival of a new wave of artificial intelligence wave in recent years, machine learning related technologies are applied to many industries and fields. The code construction and training are very important links in machine learning, the success of machine learning model application is not good, the code flow construction and training mode is not good, for code flow chart construction, most of the current industry is to write codes by using an editor for debugging until a flow chart is found, and the training mode is trained by selecting a single server mode. However, this operation has a number of disadvantages: the first is that the threshold is high, the learning cost is high, and the programming ability of some persons is not strong; secondly, the training time is long, and the requirements on the performance and the programming capability of the machine are higher and higher along with the enlargement and the complexity of the training scale; thirdly, it costs a lot of labor and is not flexible and reusable.
In order to solve the defects, a single-machine multi-card (single-machine multi-GPU) technology and a visual learning (TensorBoard) technology appear in the industry, and the aim of improving the training efficiency is achieved to a certain extent. Certainly, the schemes also have some disadvantages, and a larger batch size is needed along with the complexity of the training model, because the larger the batch size is, the larger the gradient matrix stored in each parameter update is, and the gradient matrix may exceed the display memory of the GPU, which results in that the performance of a single training server is required to be improved more and more, the flexibility and the flexibility are lower, and some visualization schemes are served in the form of a third-party library, or do not depart from the code editing mode, and the visualization model construction in the true sense still cannot be realized.
Disclosure of Invention
To address at least one of the above technical problems, the present disclosure provides a visual modeling platform and method.
In a first aspect, the present invention provides a multilingual-based visual modeling platform, comprising: a language management module, a data management module and a visual editing module, wherein,
the language management module is used for providing a plurality of programming languages;
the data management module is used for converting different data formats into a uniform data format;
the visual editing module is used for displaying the modeling working area, displaying the modeling component list, providing a visualization tool for modeling, defining the attribute of the visualization tool, receiving an external operation instruction for visual modeling, and packaging the edited training model.
Optionally, the language management module is also used for conversion between different programming languages.
Optionally, the language management module supports a hybrid use of different programming languages, including but not limited to JAVA and PYTHON.
Optionally, the visual editing module is configured to receive an external operation instruction to perform visual modeling, and includes dragging a modeling component in the modeling component list to the modeling work area to perform visual modeling, reading and identifying an uploaded external modeling component, adding the external modeling component to the modeling component list, and reading and identifying the uploaded model.
Optionally, the data serialization protocols supported by the data management module include, but are not limited to, XML, JSON, Fastjson, and ProtoBuf.
Optionally, the visual modeling platform further comprises: and the execution engine module is used for providing local and distributed training, managing distributed clusters, customizing distributed simulation training and managing data resources.
Optionally, the execution engine module is further configured to monitor training resources, including but not limited to monitoring CPU usage, GPU usage, memory consumption, hard disk IO, and network IO.
Optionally, the execution engine module is further configured to monitor a training process and a training result of the training model, including but not limited to monitoring an algorithm index, where the algorithm index includes but is not limited to accuracy, recall, F1 value, AUC, and confusion matrix.
In a second aspect, the present invention provides a multilingual-based visualization modeling method, which includes performing visualization modeling using the multilingual-based visualization modeling platform in the first aspect.
Optionally, the visual modeling method includes:
and receiving an external operation instruction through a visual editing module to perform visual modeling, and packaging the edited training model.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention supports multiple languages and data formats, is convenient for users to flexibly realize the realization of training construction, and has wider application range; in addition, a user does not need to care about the specific implementation of code writing, the user can use a simple and convenient visual modeling component and a visual modeling tool to construct, and the purposes of high flexibility and flexibility are achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a block diagram of a multilingual-based visualization modeling platform according to an embodiment of the present invention;
FIG. 2 is a block diagram of another multi-lingual based visualization modeling platform provided by an embodiment of the present invention;
fig. 3 is a flowchart of a multilingual-based visualization modeling method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
As shown in fig. 1-2, an embodiment of the present invention provides a multi-language-based visualization modeling platform, which includes: a language management module, a data management module and a visual editing module, wherein,
the language management module is used for providing a plurality of programming languages;
the data management module is used for converting different data formats into a uniform data format;
the visual editing module is used for displaying the modeling working area, displaying the modeling component list, providing a visualization tool for modeling, defining the attribute of the visualization tool, receiving an external operation instruction for visual modeling, and packaging the edited training model.
In the embodiment, a plurality of languages and data formats are supported, so that a user can flexibly realize the training construction, and the method has a wider application range; based on a plurality of language structures, the characteristics of various languages are fully exerted, and due to a plurality of language structure platforms, a plurality of languages can be supported, so that various language programming is supported for customers, and convenience is brought to the use of various users; and moreover, the conversion among various different languages can realize that users using different languages jointly construct the same training model. In addition, a user does not need to care about the specific implementation of code writing, so that the user can use a simple and convenient visual modeling component and a visual modeling tool to construct a model, and the purposes of high flexibility and high flexibility are achieved.
In one embodiment of the invention, the language management module supports mixed use of different programming languages, and conversion between different programming languages. The programming languages include, but are not limited to, JAVA and PYTHON.
In the embodiment, the provided modeling component can be edited, the modeling component code editing by using JAVA and PYTHON languages is supported, the multiplexing use of the two languages mixed editing component is supported, the synchronous processing mode and the asynchronous processing mode are supported, the request needing to be processed for a long time at the server side can be automatically converted into asynchronous processing, and a user can inquire a processing result through state updating or other operations.
In an embodiment of the present invention, the visual editing module is configured to receive an external operation instruction for visual modeling, and includes dragging a modeling component in the modeling component list to the modeling work area for visual modeling, reading and identifying an uploaded external modeling component, adding the external modeling component to the modeling component list, and reading and identifying the uploaded model.
In the embodiment, the combination of user-defined code editing and graph dragging is supported, the user-defined packaging and free dragging are combined, the operation is simple, a visual training model is constructed as an example, a user can write a modeling component code uploading platform by himself to form a modeling component list consisting of a user-defined component and a platform module together, a visual training flow chart is formed in a dragging mode through free mixing and matching, and then related resources including data, models, algorithms, parameters and the like in the training process are packaged.
In one embodiment of the present invention, the data serialization protocols supported by the data management module include, but are not limited to, XML, JSON, Fastjson, and ProtoBuf.
In this embodiment, when the training result data is not explicitly specified, a corresponding training data format is automatically generated, the data is appropriately split, simulation training is performed by using an optimization method of system configuration, each training result data is compared, and relevant parameters of the optimal training result are obtained and stored in the database. And the platform data is processed in a unified manner, so that the output data format is unified, and the method can be used for structured data management and is convenient for data migration.
In one embodiment of the invention, the visual modeling platform further comprises: and the execution engine module is used for providing local and distributed training, managing distributed clusters, customizing distributed simulation training and managing data resources.
In the embodiment, local and distributed training is provided, mass data training supporting a distributed framework is used for supporting operation of various distributed frameworks, the visual modeling platform is deployed based on cluster distribution, and the distributed training mode supports two training modes of data parallel and model parallel, so that distributed visual training is realized, the use is simple, and the code training and distributed thresholds are reduced. And the method has high availability and high expansibility, and only needs to expand the distributed framework training nodes when being applied in a large scale, and the user does not need any adjustment.
In an embodiment of the present invention, the execution engine module is further configured to monitor training resources, including but not limited to monitoring CPU usage, GPU usage, memory consumption, hard disk IO, and network IO.
In this embodiment, scheduling the resources of the entire visualization modeling platform includes: the utilization rate of a CPU (Central processing Unit), the utilization rate of a GPU (graphics processing Unit), memory consumption, hard disk IO (input/output), network IO (input/output), and the like are reasonably distributed and used.
In an embodiment of the present invention, the execution engine module is further configured to monitor a training process and a training result of the training model, including but not limited to monitoring an algorithm index, where the algorithm index includes but is not limited to accuracy, recall, F1 value, AUC, and confusion matrix.
In this embodiment, the indicators can be displayed in real time in a modeling workspace or other visual interface, and the cross-comparison results of the indicators can be displayed through the visual interface.
The invention can support multiple languages and is used for providing multiple languages for the operation of clients; the learning threshold is reduced, a user does not need to pay attention to the construction and implementation of a code model, and the method has a wider application range; the learning cost is reduced, and the operation is mastered in the door quickly; the execution engine is suitable for running of various resources; the method has high availability and high expansibility, and only training nodes need to be expanded when the method is applied in a large scale; real-time monitoring, and omnibearing display of training resources and training process.
The embodiment of the invention provides a visual modeling method, which comprises the following steps:
and receiving an external operation instruction through a visual editing module to perform visual modeling, and packaging the edited training model.
In practical application, each module of the visual modeling platform provided by the present invention can be directly or correspondingly arranged on a system composed of a client and a server after function disassembly for visual modeling, as shown in fig. 3, an embodiment of the present invention provides a visual modeling method, including:
step 1, a user uploads a custom data set or obtains a data set by using mass big data of a system by using a client side, and sends a request to a server side.
In this embodiment, the visualization modeling platform can read and recognize a custom data set uploaded by a user, and can be set on and implemented by a client as a part of the function of the visualization editing module.
And 2, the server receives the corresponding request, starts an asynchronous processing mechanism and returns the execution state and the result to the client.
In this embodiment, the server returns a result of whether the upload was successful, and the creation of the model can be continued after the successful result is returned.
And 3, selecting a created template by the user through the client, and sending a request to the server.
In this embodiment, the visual modeling platform can provide a modeled template, which can be set on and implemented by the client as part of the visual editing module.
And 4, the server side receives the corresponding request, starts an asynchronous processing mechanism and returns the execution state and the result to the client side.
In this embodiment, the server returns a result of whether the creation was successful, and the creation of the model can be continued after the result of successful creation is returned.
And 5, dragging the modeling component to freely match at the client side based on the modeling component in the template according to the requirement of the user, selecting a training set, filling training parameters in the training component, and finishing the training flowchart.
In this embodiment, the user can meet some specific new algorithm optimization requirements by uploading custom written build components.
And 6, selecting a training mode (whether distributed or not and distributed operation types such as parameter servers and Ring-Allreduce) by a user, clicking to start training, and sending the encapsulated training model to a server.
In this embodiment, the visualization tool includes a selection of a training start mode and a selection of a training start mode, and may be set on the client as a part of the function of the visualization editing module.
And 7, receiving the request by the server, checking the information, performing scheduling processing after the information is confirmed to be correct, and starting visual training.
Step 8, the user can inquire through a training monitoring page: the algorithm indexes including accuracy, recall, F1 value, AUC, confusion matrix and the like, and the cross comparison result of the indexes can be displayed through a visual interface.
In this embodiment, both the monitoring query and the cross-comparison of the indexes may be used as part of a visualization tool, for example, if the visualization tool a is defined as the monitoring query and the visualization tool B is defined as the cross-comparison of the indexes, by triggering the corresponding visualization tool, the execution engine module arranged at the server returns a corresponding result, and displays the result at the client, so as to implement a related function, and may also display the result in real time in a modeling workspace or other visualization interfaces.
The invention provides a general distributed visual modeling and training scheme, supports multiple languages, is convenient for users to flexibly realize the realization of training construction, and has wider application range; distributed training, reasonably utilizing cluster resources and efficiently training; the method has high availability and high expansibility, and only the training nodes of the server side need to be expanded when the method is applied in a large scale, and the user side does not need any adjustment; the method is simple to use, and the code construction learning threshold is reduced; the most advanced optimization algorithm is built in, and the method can be directly put into production and use.
It should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the method of the invention should not be construed to reflect the intent: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing inventive embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules or units or components of the apparatus in the examples invented herein may be arranged in an apparatus as described in this embodiment or alternatively may be located in one or more apparatuses different from the apparatus in this example. The modules in the foregoing examples may be combined into one module or may be further divided into multiple sub-modules.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features of the invention in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so invented, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature of the invention in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
Furthermore, some of the described embodiments are described herein as a method or combination of method elements that can be performed by a processor of a computer system or by other means of performing the described functions. A processor having the necessary instructions for carrying out the method or method elements thus forms a means for carrying out the method or method elements. Further, the elements of the apparatus embodiments described herein are examples of the following apparatus: the apparatus is used to implement the functions performed by the elements for the purpose of carrying out the invention.
As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention is to be considered as illustrative and not restrictive in character, with the scope of the invention being indicated by the appended claims.
Claims (10)
1. A multi-language based visualization modeling platform, comprising: a language management module, a data management module and a visual editing module, wherein,
the language management module is used for providing a plurality of programming languages;
the data management module is used for converting different data formats into a uniform data format;
the visual editing module is used for displaying the modeling working area, displaying the modeling component list, providing a visualization tool for modeling, defining the attribute of the visualization tool, receiving an external operation instruction for visual modeling, and packaging the edited training model.
2. The multilingual-based visualization modeling platform of claim 1, wherein the language management module is further configured to translate between different programming languages.
3. The multilingual-based visualization modeling platform of claim 1, wherein the language management module supports a mix of different programming languages, including JAVA and/or PYTHON.
4. The multilingual-based visual modeling platform of claim 1, wherein the visual editing module is configured to receive external operation commands for visual modeling, including dragging a modeling component in the list of modeling components to the modeling workspace for visual modeling, reading and identifying an uploaded external modeling component, adding the external modeling component to the list of modeling components, and reading and identifying the uploaded model.
5. The multilingual-based visualization modeling platform of claim 1, wherein the data serialization protocols supported by the data management module comprise XML, JSON, Fastjson, and/or ProtoBuf.
6. The multilingual-based visualization platform of any of claims 1-5, further comprising: and the execution engine module is used for providing local and distributed training, managing distributed clusters, customizing distributed simulation training and managing data resources.
7. The multilingual-based visualization modeling platform of claim 6, wherein the execution engine module is further configured to monitor training resources, including CPU usage, GPU usage, memory consumption, hard disk IO, and/or network IO.
8. The multilingual-based visualization modeling platform of claim 6, wherein the execution engine module is further configured to monitor the training process and results of the training model, including monitoring algorithm metrics including accuracy, recall, F1 values, AUC, and/or confusion matrix.
9. A multi-language based visual modeling method, comprising visually modeling using the multi-language based visual modeling platform of any one of claims 1-8.
10. The multilingual-based visualization method of claim 9, wherein the visualization method comprises:
and receiving an external operation instruction through a visual editing module to perform visual modeling, and packaging the edited training model.
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Application publication date: 20210420 |