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- .claude/CLAUDE.md - .claude/commands/subagentes.md - .claude/rules/INDEX.md - .mcp.json - bash/functions/cybersecurity/analyze_dns.md - bash/functions/cybersecurity/audit_http_headers.md - bash/functions/cybersecurity/audit_ssh_config.md - bash/functions/cybersecurity/check_firewall.md - bash/functions/cybersecurity/detect_suspicious_users.md - bash/functions/cybersecurity/encrypt_file.md - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
59 lines
1.9 KiB
Markdown
59 lines
1.9 KiB
Markdown
---
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name: gpu_info
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kind: function
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lang: py
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domain: ml
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version: "1.0.0"
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purity: impure
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signature: "def gpu_info() -> list[dict]"
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description: "Consulta nvidia-smi para obtener informacion de cada GPU NVIDIA: nombre, VRAM total y libre, version de driver y CUDA. Devuelve lista vacia si nvidia-smi no esta disponible, sin lanzar excepcion."
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tags: [gpu, nvidia, cuda, vram, hardware, probe, ml, nvidia-smi, pendiente-usar]
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uses_functions: []
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uses_types: []
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returns: []
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returns_optional: false
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error_type: "error_go_core"
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imports: []
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params: []
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output: "lista de dicts por GPU con claves: index (int), name (str), vram_total_mb (int), vram_free_mb (int), driver_version (str), cuda_version (str). Lista vacia si nvidia-smi no esta disponible."
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tested: true
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tests:
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- "sin nvidia-smi devuelve lista vacia"
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- "formato CSV correcto devuelve lista con un dict por GPU"
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- "fila malformada en CSV se ignora sin excepcion"
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test_file_path: "python/functions/ml/tests/test_gpu_info.py"
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file_path: "python/functions/ml/gpu_info.py"
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---
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## Ejemplo
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```python
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from ml.gpu_info import gpu_info
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gpus = gpu_info()
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# Sin nvidia-smi: []
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# Con una GPU:
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# [
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# {
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# "index": 0,
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# "name": "NVIDIA GeForce RTX 4090",
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# "vram_total_mb": 24564,
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# "vram_free_mb": 22000,
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# "driver_version": "535.183.01",
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# "cuda_version": "8.9"
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# }
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# ]
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for gpu in gpus:
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pct = 100 * (1 - gpu["vram_free_mb"] / gpu["vram_total_mb"])
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print(f"GPU {gpu['index']}: {gpu['name']} — VRAM {pct:.1f}% usada")
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```
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## Notas
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- Usa `--query-gpu=compute_cap` como aproximacion de la version CUDA soportada. El campo `cuda_version` del output es la compute capability (ej. "8.9"), no la version CUDA del driver.
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- Robusto a `FileNotFoundError` (nvidia-smi no instalado), `TimeoutExpired` (driver colgado), y `OSError`.
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- Para datos de torch (no nvidia-smi), usar `cuda_available`.
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- impure: consulta hardware y estado del sistema en tiempo de ejecucion.
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