Invention Application
- Patent Title: DECREASING NEURAL NETWORK INFERENCE TIMES USING SOFTMAX APPROXIMATION
-
Application No.: US16586702Application Date: 2019-09-27
-
Publication No.: US20200104686A1Publication Date: 2020-04-02
- Inventor: Yang Li , Sanjiv Kumar , Pei-Hung Chen , Si Si , Cho-Jui Hsieh
- Applicant: Google LLC
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06K9/62 ; G06F17/18 ; G06F17/16

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for decreasing neural network inference times using softmax approximation. One of the methods includes maintaining data specifying a respective softmax weight vector for each output in a vocabulary of possible neural network outputs; receiving a neural network input; processing the neural network input using one or more initial neural network layers to generate a context vector for the neural network input; and generating an approximate score distribution over the vocabulary of possible neural network outputs for the neural network input, comprising: processing the context vector using a screening model configured to predict a proper subset of the vocabulary for the context input; and generating a respective logit for each output that is in the proper subset, comprising applying the softmax weight vector for the output to the context vector.
Public/Granted literature
- US10671909B2 Decreasing neural network inference times using softmax approximation Public/Granted day:2020-06-02
Information query