Invention Grant
- Patent Title: Debugging deep neural networks
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Application No.: US16380437Application Date: 2019-04-10
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Publication No.: US11694090B2Publication Date: 2023-07-04
- Inventor: Rahul Aralikatte , Srikanth Govindaraj Tamilselvam , Shreya Khare , Naveen Panwar , Anush Sankaran , Senthil Kumar Kumarasamy Mani
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Steven M. Bouknight
- Main IPC: G06N3/02
- IPC: G06N3/02 ; G06N3/10 ; G06N3/04 ; G06N3/08 ; G06F11/36

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.
Public/Granted literature
- US20200327420A1 DEBUGGING DEEP NEURAL NETWORKS Public/Granted day:2020-10-15
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