METHOD FOR OPTIMIZING WORKFLOW-BASED NEURAL NETWORK INCLUDING ATTENTION LAYER

A method for optimizing a workflow-based neural network including an attention layer is provided. The method comprises: training the workflow-based neural network to predict a result from input elements under a prediction model with the attention layer assigning attention placements and weights, bas...

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Bibliographic Details
Main Authors CHAN, Kai Kin, TANG, Wai Kai Arvin
Format Patent
LanguageEnglish
Published 12.09.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:A method for optimizing a workflow-based neural network including an attention layer is provided. The method comprises: training the workflow-based neural network to predict a result from input elements under a prediction model with the attention layer assigning attention placements and weights, based on an original attention function, to the input elements; obtaining an original attention mask pattern and a proposed attention mask pattern; creating an attention mask updating function based on the original attention mask pattern and the proposed attention mask pattern; and combining the attention mask updating function with the original attention function to form an updated attention function.
Bibliography:Application Number: US202318179398