dump-bisect-debug
CommunityPinpoint and resolve forward numerical bugs in neural network models.
Software Engineering#neural network#bug debugging#tensor comparison#bisecting methodology#batch invariance
AuthorProgMastermind
Version1.0.0
Installs0
System Documentation
What problem does it solve?
The dump-bisect-debug Skill identifies and resolves forward numerical bugs in neural network models by comparing the outputs of the target implementation against a known-good reference implementation.
Core Features & Use Cases
- Identify Bugs: Locate forward numerical bugs by comparing intermediate tensors from the target implementation and a known-good reference.
- Bisecting Methodology: Utilize a methodology that reduces the time to find bugs from hours to minutes by systematically bisecting layers and sub-stages.
- Batch Invariance: Handle batch-invariance bisect for models expecting identical outputs across different batch slots.
- Use Case: When dealing with a model producing incorrect outputs but unable to pinpoint the issue through code review, the Skill can trace the problem back to its root.
Quick Start
Use the dump-bisect-debug Skill to bisect and debug a neural network model by following the outlined methodology and using provided tools.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferencesassets
💻 Claude Code Installation
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Please help me install this Skill: Name: dump-bisect-debug Download link: https://github.com/ProgMastermind/ATOM/archive/main.zip#dump-bisect-debug Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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