CN107992299A - Neutral net hyper parameter extraction conversion method, system, device and storage medium - Google Patents

Neutral net hyper parameter extraction conversion method, system, device and storage medium Download PDF

Info

Publication number
CN107992299A
CN107992299A CN201711207509.3A CN201711207509A CN107992299A CN 107992299 A CN107992299 A CN 107992299A CN 201711207509 A CN201711207509 A CN 201711207509A CN 107992299 A CN107992299 A CN 107992299A
Authority
CN
China
Prior art keywords
hyper parameter
target template
conversion
neutral net
configuration parameters
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201711207509.3A
Other languages
Chinese (zh)
Other versions
CN107992299B (en
Inventor
李雪雷
丁良奎
王丽
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhengzhou Yunhai Information Technology Co Ltd
Original Assignee
Zhengzhou Yunhai Information Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhengzhou Yunhai Information Technology Co Ltd filed Critical Zhengzhou Yunhai Information Technology Co Ltd
Priority to CN201711207509.3A priority Critical patent/CN107992299B/en
Publication of CN107992299A publication Critical patent/CN107992299A/en
Application granted granted Critical
Publication of CN107992299B publication Critical patent/CN107992299B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00Arrangements for software engineering
    • G06F8/30Creation or generation of source code
    • G06F8/33Intelligent editors
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Stored Programmes (AREA)

Abstract

This application discloses a kind of neutral net hyper parameter extraction conversion method, system, device and computer-readable recording medium, including:Using the network profile and hyper parameter storage file for changing neutral net in script extraction Caffe frames, network configuration parameters, hyper parameter dimension and positional information are obtained respectively;Using change script by network configuration parameters, hyper parameter dimension and positional information be converted to the corresponding form of target template, and be written in target template;Using target template, object format file is generated;The application extracts network profile and hyper parameter storage file using script is changed, obtain parameters, parameters are written in target template, utilize target template corresponding with the form of object format file, generate object format file, hyper parameter storage file is completed to the conversion of the FPGA object format files that can be run, conversion of the hyper parameter storage file to the FPGA object format files that can be run is automatically performed, improves efficiency.

Description

Neutral net hyper parameter extraction conversion method, system, device and storage medium
Technical field
The present invention relates to deep learning isomery to accelerate field, more particularly to a kind of neutral net hyper parameter extraction conversion side Method, system, device and computer-readable recording medium.
Background technology
Caffe is a clear and efficient deep learning frame, based on C++/CUDA frameworks, support order line, Python and MATLAB interfaces;A set of basic programming framework can be provided inside it in the direct seamless switchings of CPU and GPU, To realize the depth convolutional neural networks under GPU parallel architectures, deep learning scheduling algorithm.Based on the network under Caffe frames Configuration file plays the role of defining its network model, mainly defines all convolutional layers and the number being connected with convolutional layer According to stream, you can according to the network defined in network profile, complete the training or test of network model.Based on Caffe frames Lower hyper parameter is all stored under hyper parameter storage file, the network parameter that this document is finished with structured form storage training.Cause Handling mass data for deep learning needs substantial amounts of computing capability, and the development of itself is also faced with numerous predicaments, such as depth Learning software autgmentability is not high enough, calculated performance is not high enough, the problems such as energy consumption is big etc. is identified on deep learning line.
The common accelerating engine of deep learning has GPU and FPGA.GPU has more core calculations unit, this allows it to possess More powerful parallel processing capability, is the current more common acceleration means of deep learning calculating platform.But its high valency The power consumption of lattice and super large brings problems to large scale deployment.And to give full play to the performance of GPU, it is necessary to wait pending The data of processing reach certain magnitude, and which increase the time delay of data processing.FPGA is programmable gate array, it can pass through Reconstruction calculations unit is programmed, comparing GPU has the characteristics of low-power consumption, low delay, high performance-price ratio.
In the prior art, can not be grafted directly to based on the neutral net hyper parameter storage file made under Caffe frames Operation on FPGA seriously affects efficiency, it is necessary to the manually conversion of progress file.
Therefore, how to research and develop one kind and neutral net hyper parameter storage file be efficiently transplanted to operation method on FPGA, It is current technological difficulties.
The content of the invention
In view of this, it is an object of the invention to provide a kind of neutral net hyper parameter extraction conversion method, system, device And computer-readable recording medium, neutral net hyper parameter storage file can be efficiently transplanted on FPGA and run.It has Body scheme is as follows:
A kind of neutral net hyper parameter extracts conversion method, including:
Using the network profile and hyper parameter storage file for changing neutral net in script extraction Caffe frames, divide Huo Qu not network configuration parameters, hyper parameter dimension and positional information;
The network configuration parameters, the hyper parameter dimension and the positional information are converted to using the conversion script With the corresponding form of target template, and it is written in the target template;
Using the target template, object format file is generated;
Wherein, the target template is template corresponding with the form of the object format file.
Optionally, it is described to obtain network using the network profile for changing neutral net in script extraction Caffe frames The process of parameter is configured, including:
Using the conversion script, travel through and extract the configuration parameter number of each convolutional layer in the network profile According to obtaining the network configuration parameters.
Optionally, it is described using the hyper parameter storage file for changing neutral net in script extraction Caffe frames, obtain super The process of parameter dimensions and positional information, including:
Using the conversion script according to the network configuration parameters, obtained from the hyper parameter storage file described super Parameter dimensions and the positional information.
Optionally, it is described to utilize the conversion script by the network configuration parameters, the hyper parameter dimension and institute's rheme Confidence breath be converted to the corresponding form of target template, and be written in the target template, generate object format file Process, including:
The network configuration parameters, the hyper parameter dimension and the positional information are converted to using the conversion script Storage format corresponding with the target template;
The target template is called, makes the storage format of target template described in the conversion scripts match, by the network Configuration parameter, the hyper parameter dimension and the positional information are written in the target template, generate object format file.
The invention also discloses a kind of neutral net hyper parameter to extract converting system, including:
Parameter extraction module, for using change script extraction Caffe frames in neutral net network profile and Hyper parameter storage file, obtains network configuration parameters, hyper parameter dimension and positional information respectively;
Template writing module, for using it is described conversion script by the network configuration parameters, the hyper parameter dimension and The positional information be converted to the corresponding form of target template, and be written in the target template;
File generating module, for utilizing the target template, generates object format file;
Wherein, the target template is template corresponding with the form of the object format file.
Optionally, the parameter extraction module, including:
Network parameter extraction unit, for utilizing the conversion script, travels through and extracts every in the network profile The configuration parameter data of a convolutional layer, obtains the network configuration parameters.
Optionally, the parameter extraction module, including:
Hyper parameter extraction unit, for utilizing the conversion script according to the network configuration parameters, from the hyper parameter The hyper parameter dimension and the positional information are obtained in storage file.
Optionally, the template writing module, including:
Format conversion unit, for using it is described conversion script by the network configuration parameters, the hyper parameter dimension and The positional information is converted to storage format corresponding with the target template;
Template writing unit, for calling the target template, makes depositing for target template described in the conversion scripts match Form is stored up, the network configuration parameters, the hyper parameter dimension and the positional information are written in the target template, it is raw Into object format file.
The invention also discloses a kind of neutral net hyper parameter to extract conversion equipment, including:
Memory, for storing instruction;Wherein, described instruction is using nerve in conversion script extraction Caffe frames The network profile and hyper parameter storage file of network, obtain network configuration parameters, hyper parameter dimension and positional information respectively; The network configuration parameters, the hyper parameter dimension and the positional information are converted to and target mould using the conversion script The corresponding form of plate, and be written in the target template;Using the target template, object format file is generated;Wherein, The target template is template corresponding with the form of the object format file;
Processor, for performing the instruction in the memory.
The invention also discloses a kind of computer-readable recording medium, god is stored with the computer-readable recording medium Conversion program is extracted through network hyper parameter, the neutral net hyper parameter extraction conversion program is realized as before when being executed by processor The step of stating neutral net hyper parameter extraction conversion method.
In the present invention, neutral net hyper parameter extraction conversion method, including:Extracted using script is changed in Caffe frames The network profile and hyper parameter storage file of neutral net, obtain network configuration parameters, hyper parameter dimension and position respectively Information;It is corresponding with target template using changing script by network configuration parameters, hyper parameter dimension and positional information and being converted to Form, and be written in target template;Using target template, object format file is generated;Wherein, target template is and target lattice The corresponding template of form of formula file.
The present invention is literary using the network profile of neutral net and hyper parameter storage in script extraction Caffe frames is changed Part, obtains network configuration parameters, hyper parameter dimension and positional information, so that parameters be converted to and target template phase respectively Corresponding form so that network configuration parameters, hyper parameter dimension and positional information can be written in target template, finally utilized Target template corresponding with the form of object format file, generates object format file, completes hyper parameter storage file to FPGA The conversion for the object format file that can be run, using changing script and target template, it is only necessary to as soon as time conversion command manually is assigned, Conversion of the hyper parameter storage file to the FPGA object format files that can be run can be automatically performed, improve efficiency, reduce because Wrong possibility caused by human error.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this The embodiment of invention, for those of ordinary skill in the art, without creative efforts, can also basis The attached drawing of offer obtains other attached drawings.
Fig. 1 extracts conversion method flow diagram for a kind of neutral net hyper parameter disclosed by the embodiments of the present invention;
Fig. 2 extracts conversion method flow diagram for another neutral net hyper parameter disclosed by the embodiments of the present invention;
Fig. 3 extracts conversion system structure schematic diagram for a kind of neutral net hyper parameter disclosed by the embodiments of the present invention.
Embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, those of ordinary skill in the art are obtained every other without making creative work Embodiment, belongs to the scope of protection of the invention.
It is understood that since the neutral net established under Caffe frames can not directly be run on FPGA, need for this The neutral net established under Caffe frames is converted to the file format that can be run on FPGA, the present invention is implemented for this Example discloses a kind of neutral net hyper parameter extraction conversion method, and shown in Figure 1, this method includes:
Step S11:Stored using the network profile of neutral net and hyper parameter in script extraction Caffe frames is changed File, obtains network configuration parameters, hyper parameter dimension and positional information respectively.
Specifically, after conversion command input by user is received, built using changing script and extracting based on Caffe frames The network profile and hyper parameter storage file of vertical neutral net, and obtain out network from network profile respectively and match somebody with somebody Parameter is put, excess of export parameter dimensions and positional information are obtained from hyper parameter storage file.
Step S12:Network configuration parameters, hyper parameter dimension and positional information are converted to and target mould using script is changed The corresponding form of plate, and be written in target template.
Specifically, script is changed by the file format of the network configuration parameters got, hyper parameter dimension and positional information Be converted to the corresponding form of target template, and be saved in conversion script in, recycle conversion script by network configuration parameters, Hyper parameter dimension and positional information are write in target template accordingly.
Step S13:Using target template, object format file is generated.
Specifically, since target template is template corresponding with the form of object format file, i.e. target template is target Formatted file does not write data unprocessed form, so after target template is filled in, object format is generated using target template File, completes conversion of the hyper parameter storage file to the FPGA object format files that can be run.
As it can be seen that the network profile for changing neutral net in script extraction Caffe frames is utilized in the embodiment of the present invention With hyper parameter storage file, network configuration parameters, hyper parameter dimension and positional information are obtained respectively, so that parameters be changed For with the corresponding form of target template so that network configuration parameters, hyper parameter dimension and positional information can be written to target In template, target template corresponding with the form of object format file is finally utilized, generates object format file, completes hyper parameter Storage file to the FPGA object format files that can be run conversion, using changing script and target template, it is only necessary to manually assign Conversion command, so that it may be automatically performed conversion of the hyper parameter storage file to the FPGA object format files that can be run, improve Efficiency, reduces wrong possibility caused by human error.
Wherein, transfer of the embodiment of the present invention change of feet originally can be the script based on Python editor, and target template is Mustache templates, object format file are OpenCL files, and certainly according to the change of practical operation situation, programming language can be with It is changed according to practical application request, is not limited herein.
The embodiment of the invention discloses a kind of specific neutral net hyper parameter extraction conversion method, implement relative to upper one Example, the present embodiment have made further instruction and optimization to technical solution.It is shown in Figure 2, specifically:
Step S21:Using script is changed, travel through and extract the configuration parameter number of each convolutional layer in network profile According to obtaining network configuration parameters.
Specifically, using the configuration parameter data for changing each convolutional layer in script traverses network configuration file, while often After the configuration parameter data for traversing a convolutional layer, extracted, obtain the configuration parameter data collection of all convolutional layers, match somebody with somebody Supplemental characteristic defecate collection is put as the network configuration parameters in network profile.
For example, when conversion script is the script based on Python editor, conversion script is chosen neural in Caffe frames The network profile of network, and network profile is appointed as Net parameters, then travel through each convolutional layer in Net parameters Configuration parameter data, conversion script extract the configuration parameter data of each convolutional layer, obtain network configuration parameters at the same time.
Step S22:Using script is changed according to network configuration parameters, hyper parameter dimension is obtained from hyper parameter storage file And positional information.
Step S23:Network configuration parameters, hyper parameter dimension and positional information are converted to and target mould using script is changed The corresponding storage format of plate.
Specifically, conversion script by the array of network configuration parameters, hyper parameter dimension and positional information with target template In corresponding storage format deposit conversion script.
For example, during conversion script and mustache templates based on Python editor, the dictionary of script itself is changed It is corresponding with the dictionary of mustache templates, therefore, script is changed by the number of network configuration parameters, hyper parameter dimension and positional information Group is converted to storage format corresponding with the dictionary of target template and is stored in the dictionary of conversion script itself.
Step S24:Invocation target template, makes the storage format of conversion scripts match target template, by network configuration parameters, Hyper parameter dimension and positional information are written in target template, generate object format file.
For example, during conversion script and mustache templates based on Python editor, invocation target template, makes conversion The dictionary format of scripts match target template, by change script dictionary include network configuration parameters, hyper parameter dimension and In the array write-in target template of positional information, so as to be deposited using the hyper parameter that target template generation OpenCL codes can be run Store up bin file.
The present invention also further discloses a kind of neutral net hyper parameter extraction converting system, and shown in Figure 3, this is System includes:
Parameter extraction module 11, for utilizing the network profile for changing neutral net in script extraction Caffe frames With hyper parameter storage file, network configuration parameters, hyper parameter dimension and positional information are obtained respectively;
Template writing module 12, script is changed by network configuration parameters, hyper parameter dimension and positional information turn for utilizing Be changed to the corresponding form of target template, and be written in target template;
File generating module 13, for using target template, generating object format file;
Wherein, target template is template corresponding with the form of object format file.
As it can be seen that the network profile for changing neutral net in script extraction Caffe frames is utilized in the embodiment of the present invention With hyper parameter storage file, network configuration parameters, hyper parameter dimension and positional information are obtained respectively, so that parameters be changed For with the corresponding form of target template so that network configuration parameters, hyper parameter dimension and positional information can be written to target In template, target template corresponding with the form of object format file is finally utilized, generates object format file, completes hyper parameter Storage file to the FPGA object format files that can be run conversion, using changing script and target template, it is only necessary to manually assign Conversion command, so that it may be automatically performed conversion of the hyper parameter storage file to the FPGA object format files that can be run, improve Efficiency, reduces wrong possibility caused by human error.
In the embodiment of the present invention, above-mentioned parameter extraction module 11, can specifically include network parameter extraction unit and super ginseng Number extraction unit;Wherein,
Network parameter extraction unit, for using script is changed, traveling through and extracting each convolutional layer in network profile Configuration parameter data, obtain network configuration parameters.
Hyper parameter extraction unit, for using script is changed according to network configuration parameters, being obtained from hyper parameter storage file Take hyper parameter dimension and positional information.
Above-mentioned template writing module 12, can specifically include format conversion unit and template writing unit;Wherein,
Format conversion unit, script is changed by the conversion of network configuration parameters, hyper parameter dimension and positional information for utilizing For storage format corresponding with target template;
Template writing unit, for invocation target template, makes the storage format of conversion scripts match target template, by network Configuration parameter, hyper parameter dimension and positional information are written in target template, generate object format file.
In addition, the embodiment of the invention also discloses a kind of neutral net hyper parameter to extract conversion equipment, including:
Memory, for storing instruction;Wherein, instruct using neutral net in conversion script extraction Caffe frames Network profile and hyper parameter storage file, obtain network configuration parameters, hyper parameter dimension and positional information respectively;Utilize Conversion script by network configuration parameters, hyper parameter dimension and positional information be converted to the corresponding form of target template, and write Enter into target template;Using target template, object format file is generated;Wherein, target template is and object format file The corresponding template of form;
Processor, for performing the instruction in memory.
More specifical instruction on being stored in above-mentioned memory may be referred to corresponding interior disclosed in previous embodiment Hold, no longer repeated herein.
In addition, the embodiment of the invention also discloses a kind of computer-readable recording medium, on computer-readable recording medium Neutral net hyper parameter extraction conversion program is stored with, neutral net hyper parameter extraction conversion program is realized when being executed by processor Such as the step of neutral net hyper parameter extracts conversion method in previous embodiment.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation Between there are any actual relationship or order.Moreover, term " comprising ", "comprising" or its any other variant meaning Covering non-exclusive inclusion, so that process, method, article or equipment including a series of elements not only include that A little key elements, but also including other elements that are not explicitly listed, or further include for this process, method, article or The intrinsic key element of equipment.In the absence of more restrictions, the key element limited by sentence "including a ...", is not arranged Except also there are other identical element in the process, method, article or apparatus that includes the element.
Professional further appreciates that, with reference to each exemplary unit of the embodiments described herein description And algorithm steps, can be realized with electronic hardware, computer software or the combination of the two, in order to clearly demonstrate hardware and The interchangeability of software, generally describes each exemplary composition and step according to function in the above description.These Function is performed with hardware or software mode actually, application-specific and design constraint depending on technical solution.Specialty Technical staff can realize described function to each specific application using distinct methods, but this realization should not Think beyond the scope of this invention.
Above to a kind of neutral net hyper parameter extraction conversion method, system, device and computer provided by the present invention Readable storage medium storing program for executing is described in detail, and specific case used herein carries out the principle of the present invention and embodiment Illustrate, the explanation of above example is only intended to help to understand the method and its core concept of the present invention;Meanwhile for ability The those skilled in the art in domain, according to the thought of the present invention, there will be changes, comprehensive in specific embodiments and applications Upper described, this specification content should not be construed as limiting the invention.

Claims (10)

1. a kind of neutral net hyper parameter extracts conversion method, it is characterised in that including:
Using the network profile and hyper parameter storage file for changing neutral net in script extraction Caffe frames, obtain respectively Take network configuration parameters, hyper parameter dimension and positional information;
Using the conversion, script is by the network configuration parameters, the hyper parameter dimension and the positional information is converted to and mesh The corresponding form of template is marked, and is written in the target template;
Using the target template, object format file is generated;
Wherein, the target template is template corresponding with the form of the object format file.
2. neutral net hyper parameter according to claim 1 extracts conversion method, it is characterised in that described utilize changes foot The network profile of neutral net obtains the process of network configuration parameters in this extraction Caffe frames, including:
Using the conversion script, travel through and extract the configuration parameter data of each convolutional layer in the network profile, obtain To the network configuration parameters.
3. neutral net hyper parameter according to claim 2 extracts conversion method, it is characterised in that described utilize changes foot The hyper parameter storage file of neutral net in this extraction Caffe frames, obtains the process of hyper parameter dimension and positional information, bag Include:
Using the conversion script according to the network configuration parameters, the hyper parameter is obtained from the hyper parameter storage file Dimension and the positional information.
4. neutral net hyper parameter according to any one of claims 1 to 3 extracts conversion method, it is characterised in that described The network configuration parameters, the hyper parameter dimension and the positional information are converted to and target mould using the conversion script The corresponding form of plate, and be written in the target template, the process of object format file is generated, including:
Using the conversion, script is by the network configuration parameters, the hyper parameter dimension and the positional information is converted to and institute State the corresponding storage format of target template;
The target template is called, makes the storage format of target template described in the conversion scripts match, by the network configuration Parameter, the hyper parameter dimension and the positional information are written in the target template, generate object format file.
5. a kind of neutral net hyper parameter extracts converting system, it is characterised in that including:
Parameter extraction module, for being joined using the network profile for changing neutral net in script extraction Caffe frames with super Number storage file, obtains network configuration parameters, hyper parameter dimension and positional information respectively;
Template writing module, for using the conversion script by the network configuration parameters, the hyper parameter dimension and described Positional information be converted to the corresponding form of target template, and be written in the target template;
File generating module, for utilizing the target template, generates object format file;
Wherein, the target template is template corresponding with the form of the object format file.
6. neutral net hyper parameter according to claim 5 extracts converting system, it is characterised in that the parameter extraction mould Block, including:
Network parameter extraction unit, for utilizing the conversion script, travels through and extracts and each rolled up in the network profile The configuration parameter data of lamination, obtains the network configuration parameters.
7. neutral net hyper parameter according to claim 6 extracts converting system, it is characterised in that the parameter extraction mould Block, including:
Hyper parameter extraction unit, for, according to the network configuration parameters, being stored using the conversion script from the hyper parameter The hyper parameter dimension and the positional information are obtained in file.
8. converting system is extracted according to claim 5 to 7 any one of them neutral net hyper parameter, it is characterised in that described Template writing module, including:
Format conversion unit, for using the conversion script by the network configuration parameters, the hyper parameter dimension and described Positional information is converted to storage format corresponding with the target template;
Template writing unit, for calling the target template, makes the storage lattice of target template described in the conversion scripts match Formula, the network configuration parameters, the hyper parameter dimension and the positional information are written in the target template, generate mesh Mark formatted file.
9. a kind of neutral net hyper parameter extracts conversion equipment, it is characterised in that including:
Memory, for storing instruction;Wherein, described instruction is using neutral net in conversion script extraction Caffe frames Network profile and hyper parameter storage file, obtain network configuration parameters, hyper parameter dimension and positional information respectively;Utilize The conversion script is converted to the network configuration parameters, the hyper parameter dimension and the positional information and target template phase Corresponding form, and be written in the target template;Using the target template, object format file is generated;Wherein, it is described Target template is template corresponding with the form of the object format file;
Processor, for performing the instruction in the memory.
10. a kind of computer-readable recording medium, it is characterised in that be stored with nerve net on the computer-readable recording medium Network hyper parameter extracts conversion program, and the neutral net hyper parameter extraction conversion program realizes that right such as will when being executed by processor The step of seeking any one of 1 to the 4 neutral net hyper parameter extraction conversion method.
CN201711207509.3A 2017-11-27 2017-11-27 Neural network hyper-parameter extraction and conversion method, system, device and storage medium Active CN107992299B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711207509.3A CN107992299B (en) 2017-11-27 2017-11-27 Neural network hyper-parameter extraction and conversion method, system, device and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711207509.3A CN107992299B (en) 2017-11-27 2017-11-27 Neural network hyper-parameter extraction and conversion method, system, device and storage medium

Publications (2)

Publication Number Publication Date
CN107992299A true CN107992299A (en) 2018-05-04
CN107992299B CN107992299B (en) 2021-08-10

Family

ID=62032328

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711207509.3A Active CN107992299B (en) 2017-11-27 2017-11-27 Neural network hyper-parameter extraction and conversion method, system, device and storage medium

Country Status (1)

Country Link
CN (1) CN107992299B (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108920177A (en) * 2018-06-28 2018-11-30 郑州云海信息技术有限公司 Mapping method of the deep learning model configuration file to FPGA configuration file
CN108985448A (en) * 2018-06-06 2018-12-11 北京大学 Neural Networks Representation standard card cage structure
CN109242105A (en) * 2018-08-17 2019-01-18 第四范式(北京)技术有限公司 Tuning method, apparatus, equipment and the medium of hyper parameter in machine learning model
CN109858610A (en) * 2019-01-08 2019-06-07 广东浪潮大数据研究有限公司 A kind of accelerated method of convolutional neural networks, device, equipment and storage medium
CN110689138A (en) * 2018-12-29 2020-01-14 北京中科寒武纪科技有限公司 Operation method, device and related product
CN110764744A (en) * 2018-07-25 2020-02-07 赛灵思公司 Intermediate representation generation method and device for neural network computation
CN111181758A (en) * 2019-08-01 2020-05-19 腾讯科技(深圳)有限公司 Configuration file generation method and device
WO2021031137A1 (en) * 2019-08-21 2021-02-25 深圳鲲云信息科技有限公司 Artificial intelligence application development system, computer device and storage medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160342888A1 (en) * 2015-05-20 2016-11-24 Nec Laboratories America, Inc. Memory efficiency for convolutional neural networks operating on graphics processing units
CN106886487A (en) * 2015-12-15 2017-06-23 北京京航计算通讯研究所 Method for evaluating FPGA software reliabilities
CN107229969A (en) * 2017-06-21 2017-10-03 郑州云海信息技术有限公司 A kind of convolutional neural networks implementation method and device based on FPGA
CN107316013A (en) * 2017-06-14 2017-11-03 西安电子科技大学 Hyperspectral image classification method with DCNN is converted based on NSCT
CN107341545A (en) * 2017-07-25 2017-11-10 郑州云海信息技术有限公司 A kind of deep neural network arithmetic system and method
WO2017193769A1 (en) * 2016-05-11 2017-11-16 星环信息科技(上海)有限公司 Method and apparatus for conversion between machine learning models

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160342888A1 (en) * 2015-05-20 2016-11-24 Nec Laboratories America, Inc. Memory efficiency for convolutional neural networks operating on graphics processing units
CN106886487A (en) * 2015-12-15 2017-06-23 北京京航计算通讯研究所 Method for evaluating FPGA software reliabilities
WO2017193769A1 (en) * 2016-05-11 2017-11-16 星环信息科技(上海)有限公司 Method and apparatus for conversion between machine learning models
CN107316013A (en) * 2017-06-14 2017-11-03 西安电子科技大学 Hyperspectral image classification method with DCNN is converted based on NSCT
CN107229969A (en) * 2017-06-21 2017-10-03 郑州云海信息技术有限公司 A kind of convolutional neural networks implementation method and device based on FPGA
CN107341545A (en) * 2017-07-25 2017-11-10 郑州云海信息技术有限公司 A kind of deep neural network arithmetic system and method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
YIJIN GUAN 等: "FP-DNN: An Automated Framework for Mapping Deep Neural Networks onto FPGAs with RTL-HLS Hybrid Templates", 《IN PROCEEDINGS OF THE IEEE INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM 2017)》 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108985448A (en) * 2018-06-06 2018-12-11 北京大学 Neural Networks Representation standard card cage structure
CN108985448B (en) * 2018-06-06 2020-11-17 北京大学 Neural network representation standard framework structure
CN108920177A (en) * 2018-06-28 2018-11-30 郑州云海信息技术有限公司 Mapping method of the deep learning model configuration file to FPGA configuration file
CN110764744A (en) * 2018-07-25 2020-02-07 赛灵思公司 Intermediate representation generation method and device for neural network computation
CN110764744B (en) * 2018-07-25 2023-12-08 赛灵思公司 Intermediate representation generation method and device for neural network calculation
CN109242105A (en) * 2018-08-17 2019-01-18 第四范式(北京)技术有限公司 Tuning method, apparatus, equipment and the medium of hyper parameter in machine learning model
CN109242105B (en) * 2018-08-17 2024-03-15 第四范式(北京)技术有限公司 Code optimization method, device, equipment and medium
CN110689138A (en) * 2018-12-29 2020-01-14 北京中科寒武纪科技有限公司 Operation method, device and related product
US11893414B2 (en) 2018-12-29 2024-02-06 Cambricon Technologies Corporation Limited Operation method, device and related products
CN109858610A (en) * 2019-01-08 2019-06-07 广东浪潮大数据研究有限公司 A kind of accelerated method of convolutional neural networks, device, equipment and storage medium
CN111181758A (en) * 2019-08-01 2020-05-19 腾讯科技(深圳)有限公司 Configuration file generation method and device
WO2021031137A1 (en) * 2019-08-21 2021-02-25 深圳鲲云信息科技有限公司 Artificial intelligence application development system, computer device and storage medium

Also Published As

Publication number Publication date
CN107992299B (en) 2021-08-10

Similar Documents

Publication Publication Date Title
CN107992299A (en) Neutral net hyper parameter extraction conversion method, system, device and storage medium
CN103135976B (en) code automatic generation method and device
CN101763064B (en) Numerical control machining process design system and method of aircraft complex components facing process object
CN104573122B (en) It is a kind of from AIX platforms to the oracle database Migration tools of K UX platform migrations
CN108269063A (en) The online synergic editing method of word document and system
CN104978411B (en) A kind of automobile development method and apparatus of bullet train
JP2019526143A (en) Method and apparatus for performing transform-based learning on medical images
CN103049383A (en) Development and testing cloud system
CN101464799A (en) MPI parallel programming system based on visual modeling and automatic skeleton code generation method
CN107480115B (en) Method and system for format conversion of caffe frame residual error network configuration file
CN110516817A (en) A kind of model training data load method and device
CN102830973A (en) Method and layered structure for double-layer MVC (model, view and controller) developed by Web application with mass data
CN109710357A (en) A kind of method and system based on Unity3D engine implementation server operation
CN113779663B (en) BIM-based subway station enclosure structure three-dimensional modeling method, system and medium
Biscarat et al. Towards a realistic track reconstruction algorithm based on graph neural networks for the HL-LHC
CN110263860A (en) A kind of freeway traffic flow prediction technique and device
CN103400050A (en) Multiple-user cooperative nuclear reactor risk determining method and system
CN102375897A (en) System for generating dendrogram of welding and assembly structure of vehicle body
CN105488052B (en) Structural data is switched to the method and system of format formfile
KR101087197B1 (en) The method of linking computer aided design system with product data management system in real time
CN104112052B (en) Design method and device for side wall framework structure of electric locomotive
CN102880749A (en) 2D-3D (two-dimensional-three-dimensional) union layout method of communication satellite
CN104599318B (en) A kind of method and system of the seamless fusion of plant three-dimensional model gridding
CN101216769A (en) Hiberarchy system description language SmartC to C code automatic conversion method
CN113806923A (en) Pharmacokinetic-pharmacodynamic model hyper-parameter automatic learning method and device based on nlmixr package

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant