公开(公告)号：US20210019630A1

公开(公告)日：2021-01-21

申请号：US16982441

申请日：2018-07-26

Applicant: Anbang YAO ,  Aojun ZHOU ,  Kuan WANG ,  Hao ZHAO ,  Yurong CHEN ,  Intel Corporation

Inventor： Anbang Yao ,  Aojun Zhou ,  Kuan Wang ,  Hao Zhao ,  Yurong Chen

IPC: G06N3/08 ,  G06K9/62 ,  G06N3/04

Abstract: Methods, apparatus, systems and articles of manufacture for loss-error-aware quantization of a low-bit neural network are disclosed. An example apparatus includes a network weight partitioner to partition unquantized network weights of a first network model into a first group to be quantized and a second group to be retrained. The example apparatus includes a loss calculator to process network weights to calculate a first loss. The example apparatus includes a weight quantizer to quantize the first group of network weights to generate low-bit second network weights. In the example apparatus, the loss calculator is to determine a difference between the first loss and a second loss. The example apparatus includes a weight updater to update the second group of network weights based on the difference. The example apparatus includes a network model deployer to deploy a low-bit network model including the low-bit second network weights.

公开(公告)号：US20250117639A1

公开(公告)日：2025-04-10

申请号：US18886625

申请日：2024-09-16

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Aojun Zhou ,  Kuan Wang ,  Hao Zhao ,  Yurong Chen

IPC: G06N3/063 ,  G06F18/21 ,  G06F18/214 ,  G06N3/047 ,  G06N3/084

Abstract: Methods, apparatus, systems and articles of manufacture for loss-error-aware quantization of a low-bit neural network are disclosed. An example apparatus includes a network weight partitioner to partition unquantized network weights of a first network model into a first group to be quantized and a second group to be retrained. The example apparatus includes a loss calculator to process network weights to calculate a first loss. The example apparatus includes a weight quantizer to quantize the first group of network weights to generate low-bit second network weights. In the example apparatus, the loss calculator is to determine a difference between the first loss and a second loss. The example apparatus includes a weight updater to update the second group of network weights based on the difference. The example apparatus includes a network model deployer to deploy a low-bit network model including the low-bit second network weights.

公开(公告)号：US12112256B2

公开(公告)日：2024-10-08

申请号：US16982441

申请日：2018-07-26

Applicant: Intel Corporation ,  Anbang Yao ,  Aojun Zhou ,  Kuan Wang ,  Hao Zhao ,  Yurong Chen

Inventor： Anbang Yao ,  Aojun Zhou ,  Kuan Wang ,  Hao Zhao ,  Yurong Chen

IPC: G06N3/063 ,  G06F18/21 ,  G06F18/214 ,  G06N3/047 ,  G06N3/084

CPC classification number: G06N3/063 ,  G06F18/2148 ,  G06F18/217 ,  G06N3/047 ,  G06N3/084

Abstract: Methods, apparatus, systems and articles of manufacture for loss-error-aware quantization of a low-bit neural network are disclosed. An example apparatus includes a network weight partitioner to partition unquantized network weights of a first network model into a first group to be quantized and a second group to be retrained. The example apparatus includes a loss calculator to process network weights to calculate a first loss. The example apparatus includes a weight quantizer to quantize the first group of network weights to generate low-bit second network weights. In the example apparatus, the loss calculator is to determine a difference between the first loss and a second loss. The example apparatus includes a weight updater to update the second group of network weights based on the difference. The example apparatus includes a network model deployer to deploy a low-bit network model including the low-bit second network weights.