The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 30, 2026

Filed:

Feb. 03, 2020
Applicant:

Ambarella International Lp, Santa Clara, CA (US);

Inventors:

Santosh Chilkunda, Santa Clara, CA (US);

Malhar Palkar, Cupertino, CA (US);

Tong Yu, New York, NY (US);

Assignee:

Ambarella International LP, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/082 (2023.01); G06N 7/08 (2006.01); G06N 20/10 (2019.01);
U.S. Cl.
CPC ...
G06N 3/082 (2013.01); G06N 7/08 (2013.01); G06N 20/10 (2019.01);
Abstract

A method of pruning a pre-trained model comprises the steps of (a) constructing a stochastic super net and (b) training the stochastic super net to determine a particular candidate block selection that provides an optimal level of sparsity for each of the layers based upon a cost function. The stochastic super net generally represents a layer-wise search space with a fixed macro-architecture. A number of layers of the macro-architecture and input/output dimensions of each of the layers of the macro-architecture are essentially the same as the pre-trained model. Each layer comprises a plurality of candidate blocks. A sparsity of each of the candidate blocks in a respective layer is different. A training dataset used to train the pre-trained model is used to train the stochastic super net.


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