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Model using method and device

A model and learning model technology, applied in the field of computer communication, can solve the problem of single method of reasoning speed

Pending Publication Date: 2020-10-09
BEIJING XIAOMI PINECONE ELECTRONICS CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The existing method of optimizing the reasoning speed of the model is relatively simple

Method used

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Embodiment Construction

[0048] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present disclosure as recited in the appended claims.

[0049] The terminology used in the present disclosure is for the purpose of describing particular embodiments only, and is not intended to limit the present disclosure. As used in this disclosure and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood...

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Abstract

The invention provides a model using method and device. The model using method is applied to the terminal, wherein a deep learning model is built in the terminal, and the terminal combines the operators associated with the use in the plurality of operators according to the use information of the plurality of operators in the deep learning model within a period of running time, so as to reduce thenumber of the operators in the deep learning model and obtain a combined first deep learning model. Compared with a deep learning model before combination, the number of operators in the combined deeplearning model is small, so that the frequency of placing the execution results of the operators in the memory and reading the execution results of the operators from the memory for other operators to use in the model reasoning process is reduced, the reasoning speed of the model is increased, and the reasoning time of the model is shortened.

Description

technical field [0001] The present disclosure relates to the technical field of computer communication, in particular to a method and device for using a model. Background technique [0002] After the deep learning model is constructed, the deep learning model is trained, and the trained deep learning model is deployed in the terminal. [0003] At present, the inference speed of the deep learning model is optimized by configuring high-performance hardware resources for the terminal. The existing way of optimizing the inference speed of the model is relatively simple. Contents of the invention [0004] In order to overcome the problems existing in related technologies, the present disclosure provides a model using method and device. [0005] According to the first aspect of the embodiments of the present disclosure, a method for using a model is provided, which is applied to a terminal, the terminal has a built-in deep learning model, and the method includes: [0006] Obt...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N20/00
CPCG06N20/00
Inventor 叶剑武
Owner BEIJING XIAOMI PINECONE ELECTRONICS CO LTD
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