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Model training method and device and computer storage medium

A technology for computer storage and model training, applied in the field of big data, can solve the problems of slow training speed and low execution efficiency of TensorFlow

Pending Publication Date: 2022-03-15
北京鸿享技术服务有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But TensorFlow's training speed is slow and execution efficiency is low

Method used

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  • Model training method and device and computer storage medium
  • Model training method and device and computer storage medium
  • Model training method and device and computer storage medium

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Embodiment Construction

[0065] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0066] The terms "first", "second", "third" and the like in the description and claims of the present application and the above drawings are used to distinguish different objects, rather than to describe a specific order. Furthermore, the terms "include" and "have", as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or devices.

[0067] figure 1 A schematic structural diagram of a model training system provided by an embodiment of the present appli...

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PUM

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Abstract

The invention discloses a model training method and device and a computer storage medium. The method comprises the following steps: acquiring at least one model parameter to be updated; the at least one to-be-updated model parameter is a part of the model parameter; and inputting the at least one to-be-updated model parameter into the model to obtain a gradient value so as to update the at least one to-be-updated model parameter, so that the training speed of the model can be improved.

Description

technical field [0001] The present application relates to the field of big data, in particular to a model training method, device and computer storage medium. Background technique [0002] When promoting advertisements on a webpage, it is often necessary to predict the click-through rate of users for each advertisement, and display the advertisement with the highest predicted click-through rate in a conspicuous position on the webpage, so as to achieve the effect of advertisement promotion. Among them, the user's click rate on each advertisement is usually predicted by a deep model. Developers generally choose TensorFlow as the training framework for the model. However, the training speed of TensorFlow is slow and the execution efficiency is low. Contents of the invention [0003] Embodiments of the present application provide a model training method, device, and computer storage medium, which can increase the training speed of the model and improve execution efficiency....

Claims

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Application Information

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IPC IPC(8): G06F16/23G06F16/22G06N20/00G06Q30/02
CPCG06F16/23G06F16/2255G06N20/00G06Q30/0242
Inventor 张彦升姚磊
Owner 北京鸿享技术服务有限公司