nvrx-attr

por nvidia

Camada de orquestração sobre os módulos de atribuição do nvidia_resiliency_ext. Fornece análise de logs, análise de fr e feedback de injeção de falhas orientado ao Megatron-LM…

npx skills add https://github.com/nvidia/nvidia-resiliency-ext --skill nvrx-attr

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Attribution Skills

High-level orchestration layer over the nvidia_resiliency_ext.attribution modules. Each subdirectory is a self-contained skill with its own SKILL.md and helper scripts.

Skills

Directory	Purpose	Entry point
`log-analysis/`	Analyze SLURM job logs for failure root-cause and restart decisions	`NVRxLogAnalyzer` (`nvrx_logsage.py`)
`fr-analysis/`	Analyze NCCL flight-recorder dumps for collective-hang root-cause	`CollectiveAnalyzer` (`fr_attribution.py`)
`fault-injection-loop/`	Run a batched SLURM fault-injection feedback loop and score attribution accuracy	`prepare_node_alloc.sh` / `watch_and_analyze.sh`

How skills relate to the library

src/nvidia_resiliency_ext/
├── attribution/
│   ├── log_analyzer/nvrx_logsage.py      ← log-analysis implementation
│   ├── trace_analyzer/fr_attribution.py  ← fr-analysis implementation
│   ├── analyzer/engine.py                ← combined orchestration entry point
│   └── combined_log_fr/                  ← optional log + FR fusion
└── skills/
    └── nvrx-attr/                        ← this skill bundle
        ├── log-analysis/
        ├── fr-analysis/
        └── fault-injection-loop/

The Analyzer (analyzer/engine.py) is the recommended entry point when you need request coalescing, result caching, or the combined LOG_AND_TRACE pipeline. Use the individual skills when you want to run one analysis type directly without the full coalescing stack.

Common prerequisites

LLM_API_KEY environment variable, LLM_API_KEY_FILE, or ~/.llm_api_key
Package installed: pip install 'nvidia-resiliency-ext[attribution]' or pip install -e '.[attribution]' from repo root
The fault-injection loop has only been validated with Megatron-LM training scripts

Fault-Loop Local Setup

Before using fault-injection-loop/, create the local config file from the tracked template and fill in your site-specific values:

cp scripts/user.env.example scripts/user.env

The feedback-loop scripts require src/nvidia_resiliency_ext/skills/nvrx-attr/scripts/user.env to exist at runtime. Keep user.env local and untracked.