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Data processing method and device, electronic equipment and storage medium

A data processing and data technology, applied in the computer field, can solve problems such as execution errors

Pending Publication Date: 2022-02-01
SHANGHAI SENSETIME TECH DEV CO LTD
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  • Abstract
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  • Claims
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Problems solved by technology

[0004] However, if the size of the training data input in the execution phase does not match the compilation phase, it will cause execution errors

Method used

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  • Data processing method and device, electronic equipment and storage medium
  • Data processing method and device, electronic equipment and storage medium
  • Data processing method and device, electronic equipment and storage medium

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Embodiment Construction

[0054] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only It is a part of the embodiments of the present disclosure, but not all of them. The components of the disclosed embodiments generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those ski...

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Abstract

The invention provides a data processing method and device, electronic equipment and a storage medium, and the method comprises the steps of obtaining a calculation graph obtained through compiling based on a target neural network training code, wherein the calculation graph comprises a shape operation relation and a data operation relation, and the shape operation relation and the data operation relation are respectively a shape calculation rule and a data calculation rule corresponding to each network layer in the target neural network represented in a data form; and in response to an execution instruction for the calculation graph, based on the to-be-trained training data and the shape operation relationship and the data operation relationship included in the calculation graph, executing to obtain an execution result for the target neural network training code. According to the method, input training data of various sizes can be compatible in the execution stage, the determined execution result is not prone to errors, the accuracy rate is high, and efficient network training is further ensured.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular, to a data processing method, device, electronic equipment, and storage medium. Background technique [0002] In order to efficiently implement the training of the neural network model, you can use the deep learning framework to write the code to implement the neural network model, and run the code of the neural network model through the framework. Among them, the deep learning framework needs to first compile the neural network model into a static calculation graph, and can realize model training for multiple training data by executing the calculation graph multiple times. [0003] In the process of compiling the calculation graph, the shape of the tensor corresponding to the input or output of the model is usually fixed, and in order to ensure the smooth progress of the model training, the same shape must be used in the process of executing the calculation graph. ...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06F8/41G06F17/15G06F17/16
CPCG06N3/04G06N3/08G06F8/41G06F17/16G06F17/15
Inventor 李周洋
Owner SHANGHAI SENSETIME TECH DEV CO LTD
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