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Neural network model generation method and device

A neural network model and network technology, applied in the computer field, can solve the problems of low efficiency of the neural network model

Inactive Publication Date: 2019-10-22
TENCENT TECH (SHENZHEN) CO LTD
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Problems solved by technology

[0005] Embodiments of the present invention provide a method and device for generating a neural network model to at least solve the technical problem of low efficiency in generating a neural network model

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  • Neural network model generation method and device
  • Neural network model generation method and device
  • Neural network model generation method and device

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Embodiment Construction

[0050] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0051] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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Abstract

The invention discloses a neural network model generation method and device. The method comprises the steps of determining hyper-parameter values corresponding to hyper-parameters in a first neural network model from a hyper-parameter value set; obtaining first model accuracy of a second neural network model obtained by training the first neural network model; and under the condition that the accuracy of the first model is lower than the target accuracy, updating hyper-parameter values of part of hyper-parameters in the first neural network model to corresponding target hyper-parameter valuesin the hyper-parameter value set to obtain a third neural network model. According to the invention, the technical problem of low efficiency of generating the neural network model is solved.

Description

technical field [0001] The invention relates to the field of computers, in particular to a method and device for generating a neural network model. Background technique [0002] The current process of building neural network models is to manually adjust the neural network architecture. This method is 100% manual and is the most widely used method by researchers and machine learning engineers. The workflow is very simple, for example: design a game artificial intelligence (AI) imitation learning process, then iterate through different neural network model architectures in sequence, train the imitation learning model weights of the neural network architecture, and apply the weights to the game Observe its AI effect until the model meets the needs of AI. [0003] First of all, manual design of neural network architecture requires developers to have rich experience in deep learning and neural network architecture to be able to design a neural network architecture suitable for A...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62
CPCG06N3/08G06N3/045G06F18/29A63F13/67A63F13/803A63F13/335G06N3/082G06N5/01G06N7/01G06N3/0985A63F13/45
Inventor 黄盈周大军李旭冬
Owner TENCENT TECH (SHENZHEN) CO LTD
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