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Design method, device and equipment based on deep learning general task framework model

A framework model and deep learning technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problem that the model is difficult to balance computing power and accuracy

Pending Publication Date: 2022-07-08
XIAMEN MEITUZHIJIA TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] In view of this, the purpose of the present invention is to propose a design method, device and equipment based on a deep learning general task framework model, aiming to solve the problem that the existing models are difficult to balance computing power and accuracy

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  • Design method, device and equipment based on deep learning general task framework model
  • Design method, device and equipment based on deep learning general task framework model
  • Design method, device and equipment based on deep learning general task framework model

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[0034] In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained b...

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Abstract

The invention discloses a deep learning-based universal task framework model design method, device and equipment and a storage medium, and the method comprises the steps: constructing a universal task framework model which comprises an iterable task model and an index model; performing forward reasoning operation on input data through the iterable task model to obtain a target result; characteristic parameters output by the iterable task model are obtained through the index model to serve as input for forward reasoning operation, and an index result is obtained; and according to the index result, judging whether the iterable task model takes the target result as input to carry out the forward reasoning operation of the next round of iteration or not. And it can be flexibly ensured that optimal balance is achieved in the aspects of computing power and precision.

Description

technical field [0001] The present invention relates to the technical field of model design, in particular to a design method, device and equipment for a general task framework model based on deep learning. Background technique [0002] At present, in the field of artificial intelligence, the research and achievements of deep learning can be described as unparalleled, and at the same time, a large number of artificial intelligence companies have been born. In the scene, the hardware and software requirements of the device are different, and the computing power and performance vary from person to person. At the same time, we know that deep learning models generally consume computing power, and large models (referring to a large number of parameters) The recognition effect is good, but it requires a high cost of computing power. Small models require less computing power, but at the same time, the effect is worse than that of large models. Therefore, how to balance the relation...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/08G06N3/084G06N3/044G06N3/045
Inventor 李江曲晓超刘利朋卢波肖塞
Owner XIAMEN MEITUZHIJIA TECH