Inference Tie-Breaker Layer for Reproducible Classification

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Solution Overview

Problem

Deep learning inference models face compatibility issues due to floating-point rounding errors, leading to inconsistent inference choices across different hardware-software stacks, especially when probabilities of multiple classes are close, causing categorical differences.

Innovation Solution

Implement a tie-breaker layer that deterministically selects an inference class by introducing a threshold value to handle near-ties in probabilistic weights, ensuring consistent results across varying computing systems.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If floating-point arithmetic is used to calculate probabilities in deep learning inference, then computational flexibility and precision are improved, but rounding errors accumulate and cause inconsistent inference choices across different hardware-software stacks

Engineering Contradiction:

Improveprobability calculation precisionVSAvoidinference choice consistency

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent applies preliminary action by introducing a tie-breaker layer before the final inference selection step. This layer proactively identifies and resolves potential floating-point rounding conflicts by comparing probabilities of top candidate classes and applying deterministic tie-breaking rules, preventing inconsistent results before they occur across different hardware platforms

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The tie-breaker layer acts as an intermediary component between the floating-point probability calculation and the final class selection. It mediates the transition by introducing a deterministic comparison mechanism that overrides floating-point inconsistencies, ensuring reliable and consistent inference choices regardless of underlying hardware variations

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If a tie-breaker layer is introduced to resolve floating-point rounding issues, then inference choice consistency is improved, but system complexity increases

Engineering Contradiction:

Improveinference choice consistencyVSAvoidinference model structure

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The tie-breaker layer applies partial action by focusing computational effort only on cases where floating-point rounding may cause issues. It selectively activates deterministic tie-breaking logic only when probabilities of candidate classes are close, rather than applying complex resolution mechanisms to all inference cases, thus minimizing added complexity

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12493784B1Tie-breaker for inference reproducibility

Publication Date: 2025.12.09 NVIDIA CORP

AI summary

Apparatuses, systems, and techniques to deterministically classify data. In at least one embodiment, inference classes with weights within a threshold range are treated as equivalent and one representative inference class is selected.