公开(公告)号：US20220207329A1

公开(公告)日：2022-06-30

申请号：US17558327

申请日：2021-12-21

Applicant: Snap Inc.

Inventor： Jian Ren ,  Oliver Woodford ,  Sergey Tulyakov ,  Jiazhuo Wang ,  Qing Jin

IPC: G06N3/04 ,  G06N3/08

Abstract: Systems and methods herein describe an image compression system. The image compression system generates a first generative adversarial network (GAN), identifies a threshold, based on the threshold, generates a second GAN by pruning channels of the first GAN, trains the second GAN using similarity-based knowledge distillation from the first GAN, and stores the trained second GAN.

公开(公告)号：US20240053959A1

公开(公告)日：2024-02-15

申请号：US18331660

申请日：2023-06-08

Applicant: Snap Inc.

Inventor： Denys Makoviichuk ,  Jiazhuo Wang ,  Yang Wen

IPC: G06F7/483

CPC classification number: G06F7/483

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for automatic quantization of a floating point model. The program and method provide for providing a floating point model to an automatic quantization library, the floating point model being configured to represent a neural network, and the automatic quantization library being configured to generate a first quantized model based on the floating point model; providing a function to the automatic quantization library, the function being configured to run a forward pass on a given dataset for the floating point model; causing the automatic quantization library to generate the first quantized model based on the floating point model; causing the automatic quantization library to calibrate the first quantized model by running the first quantized model on the function; and converting the calibrated first quantized model to a second quantized model.