Debugging deep neural networks

US11694090B2 · kind B2 · utility

Assignee

• International Business Machines Corporation · US

Inventors

• Rahul Aralikatte · Bengaluru, IN
• Srikanth Govindaraj Tamilselvam · Ezhil Nagar, IN
• Shreya Khare · Bengaluru, IN
• Naveen Panwar · Bengaluru, IN
• Anush Sankaran · Kanchinakote, IN
• Senthil Kumar Kumarasamy Mani · New Delhi, IN

Key dates

• Filing date: Apr 10, 2019
• Grant date: Jul 4, 2023
• Expiry date: May 4, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N5/022
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method, computer system, and a computer program product for debugging a deep neural network is provided. The present invention may include identifying, automatically, one or more debug layers associated with a deep learning (DL) model design/code, wherein the identified one or more debug layers include one or more errors, wherein a reverse operation is introduced for the identified one or more debug layers. The present invention may then include presenting, to a user, a debug output based on at least one break condition, wherein in response to determining the at least one break condition is satisfied, triggering the debug output to be presented to the user, wherein the presented debug output includes a fix for the identified one or more debug layers in the DL model design/code and at least one actionable insight.