Electronic device and control method thereof

Patent metadata

Field	Value
Publication number	US-2021279589-A1
Application number	US-201917258617-A
Country	US
Kind code	A1
Filing date	May 10, 2019
Priority date	Aug 28, 2018
Publication date	Sep 9, 2021
Grant date	—

Abstract

Disclosed is an electronic device. The electronic device comprises a storage in which sample data and a matrix included in an artificial intelligence model which is trained on the basis of the sample data are stored, and a processor, wherein the processor is configured to: on the basis of the sizes of a plurality of elements included in the matrix, obtain a first matrix pruned by converting values of elements in the number corresponding to a first proportion to zero values; on the basis of test data, obtain first accuracy of an artificial intelligence model including the first matrix; if the first accuracy is within a preset range with respect to a preset value, retrain the artificial intelligence model including the first matrix on the basis of the sample data; and, on the basis of the sizes of a plurality of elements included in the retrained first matrix, obtain a second matrix pruned by converting values of elements in the number corresponding to a second proportion, which is greater than the first proportion, to zero values.

First claim

What is claimed is:

1 . An electronic device comprising:
a storage in which sample data and a matrix included in an artificial intelligence model which is trained based on the sample data are stored, and a processor configured to: based on sizes of a plurality of elements included in the matrix, obtain a first matrix pruned by converting values of elements in the number corresponding to a first proportion to zero values, based on test data, obtain first accuracy of an artificial intelligence model including the first matrix, based on the first accuracy being within a preset range with respect to a preset value, retrain the artificial intelligence model including the first matrix based on the sample data, and based on sizes of a plurality of elements included in the retrained first matrix, obtain a second matrix pruned by converting values of elements in the number corresponding to a second proportion, which is greater than the first proportion, to zero values.

2 . The electronic device of claim 1 ,
wherein the processor is configured to: identify elements in the number corresponding to the first proportion in the order of having smaller sizes of absolute values among the plurality of elements included in the matrix, and identify elements in the number corresponding to the second proportion in the order of having smaller sizes of absolute values among the plurality of elements included in the retrained first matrix.

3 . The electronic device of claim 1 ,
wherein the processor is configured to: obtain second accuracy of an artificial intelligence model including the second matrix based on the test data, based on the second accuracy being within the preset range with respect to the preset value, retrain the artificial intelligence model including the second matrix based on the sample data, and based on sizes of a plurality of elements included in the retrained second matrix, obtain a third matrix pruned by converting values of elements in the number corresponding to a third proportion, which is greater than the second proportion, to zero values.

4 . The electronic device of claim 3 ,
wherein the processor is configured to: obtain third accuracy of an artificial intelligence model including the third matrix based on the test data, and based on the third accuracy being outside the preset range with respect to the preset value, determine the second matrix as the final matrix of the matrix included in the artificial intelligence model.

5 . The electronic device of claim 3 ,
wherein the processor is configured to: based on the number of times of pruning applied to the third matrix being a preset number of times, determine the third matrix as the final matrix of the matrix included in the artificial intelligence model.

6 . The electronic device of claim 1 ,
wherein the processor is configured to: based on the first accuracy being outside the preset range with respect to the preset value, convert values of elements in the number corresponding to a proportion smaller than the first proportion to zero values, based on the sizes of a plurality of elements included in the matrix, so as to obtain a re-pruned first matrix.

7 . The electronic device of claim 1 ,
wherein the preset value was obtained based on the accuracy of the artificial intelligence model including the matrix based on the test data.

8 . The electronic device of claim 1 ,
wherein the processor is configured to: divide the matrix into a first sub matrix and a second sub matrix through singular value decomposition (SVD) based on a first rank value, instead of a pruning operation based on the first proportion, and combine the first sub matrix and the second sub matrix to obtain the first matrix, and divide the retrained first matrix into a third sub matrix and a fourth sub matrix through SVD based on a second rank value smaller than the first rank value, instead of a pruning operation based on the second proportion, and combine the third sub matrix and the fourth sub matrix to obtain the second matrix.

9 . The electronic device of claim 8 ,
wherein the processor is configured to: obtain second accuracy of an artificial intelligence model including the second matrix based on the test data, and based on the second accuracy being outside the preset range with respect to the preset value, determine the first sub matrix and the second sub matrix as the final matrices of the matrix included in the artificial intelligence model.

10 . The electronic device of claim 8 ,
wherein the processor configured to: based on the first accuracy being outside the preset range with respect to the preset value, redivide the matrix into the first sub matrix and the second sub matrix through SVD based on a second rank value bigger than the first rank value, and combine the first sub matrix and the second sub matrix to reobtain the first matrix.

11 . A control method of an electronic device storing sample data and a matrix included in an artificial intelligence model which is trained based on the sample data, the method comprising:
based on sizes of a plurality of elements included in the matrix, obtaining a first matrix pruned by converting values of elements in the number corresponding to a first proportion to zero values; based on test data, obtaining first accuracy of an artificial intelligence model including the first matrix; based on the first accuracy being within a preset range with respect to a preset value, retraining the artificial intelligence model including the first matrix based on the sample data; and based on sizes of a plurality of elements included in the retrained first matrix, obtaining a second matrix pruned by converting values of elements in the number corresponding to a second proportion, which is greater than the first proportion, to zero values.

12 . The control method of claim 11 ,
wherein the obtaining a first matrix comprises: identifying elements in the number corresponding to the first proportion in the order of having smaller sizes of absolute values among the plurality of elements included in the matrix, and the obtaining a second matrix comprises: identifying elements in the number corresponding to the second proportion in the order of having smaller sizes of absolute values among the plurality of elements included in the retrained first matrix.

13 . The control method of claim 11 , further comprising:
obtaining second accuracy of an artificial intelligence model including the second matrix based on the test data; based on the second accuracy being within the preset range with respect to the preset value, retraining the artificial intelligence model including the second matrix based on the sample data; and based on sizes of a plurality of elements included in the retrained second matrix, obtaining a third matrix pruned by converting values of elements in the number corresponding to a third proportion, which is greater than the second proportion, to zero values.

14 . The control method of claim 13 , further comprising:
obtaining third accuracy of an artificial intelligence model including the third matrix based on the test data; and based on the third accuracy being outside the preset range with respect to the preset value, determining the second matrix as the final matrix of the matrix included in the artificial intelligence model.

15 . The control method of claim 13 , further comprising:
based on the number of times of pruning applied to the third matrix being a preset number of times, determining the third matrix as the final matrix of the matrix included in th

Assignees

• Samsung Electronics Co Ltd

Inventors

• Lee Dongsoo
• Kapoor Parichay
• Kim Byeoungwook

Classifications

• G06N3/082 Primary

  modifying the architecture, e.g. adding, deleting or silencing nodes or connections · CPC title

• G06F17/16 Primary

  Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

• G06V10/776

  Validation; Performance evaluation · CPC title

• G06F18/2163

  Partitioning the feature space · CPC title

• G06F18/25

  Fusion techniques · CPC title