egutierrez
e3c8979e8d
- cmd/fn/doctor.go - cmd/fn/main.go - cpp/apps/primitives_gallery/playground/tables/CMakeLists.txt - cpp/apps/primitives_gallery/playground/tables/data_table.cpp - cpp/apps/primitives_gallery/playground/tables/data_table_logic.cpp - cpp/apps/primitives_gallery/playground/tables/data_table_logic.h - cpp/apps/primitives_gallery/playground/tables/self_test.cpp - cpp/apps/primitives_gallery/playground/tables/tql.cpp - cpp/apps/primitives_gallery/playground/tables/viz.cpp - cpp/apps/primitives_gallery/playground/tables/viz.h - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
68 lines
1.9 KiB
Markdown
68 lines
1.9 KiB
Markdown
---
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name: cuda_available
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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 cuda_available() -> dict"
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description: "Detecta si CUDA esta disponible via torch. Devuelve device_count, nombres de GPU y version de CUDA. Si torch no esta instalado, retorna available=False sin lanzar excepcion."
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tags: [cuda, gpu, torch, pytorch, hardware, probe, ml, device]
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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: "dict con claves: available (bool), device_count (int), devices (list[str] con nombres de GPU), torch_version (str o 'not_installed'), cuda_version (str | None)"
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tested: true
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tests:
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- "sin torch retorna available=False y torch_version=not_installed"
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- "con torch sin cuda retorna available=False y device_count=0"
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- "claves del dict siempre presentes"
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test_file_path: "python/functions/ml/tests/test_cuda_available.py"
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file_path: "python/functions/ml/cuda_available.py"
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---
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## Ejemplo
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```python
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from ml.cuda_available import cuda_available
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info = cuda_available()
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# Sin GPU:
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# {
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# "available": False,
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# "device_count": 0,
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# "devices": [],
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# "torch_version": "2.3.0",
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# "cuda_version": None
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# }
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# Con GPU:
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# {
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# "available": True,
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# "device_count": 1,
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# "devices": ["NVIDIA RTX 4090"],
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# "torch_version": "2.3.0",
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# "cuda_version": "12.1"
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# }
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# Sin torch instalado:
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# {
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# "available": False,
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# "device_count": 0,
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# "devices": [],
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# "torch_version": "not_installed",
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# "cuda_version": None
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# }
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```
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## Notas
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- Nunca lanza ImportError aunque torch no este instalado.
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- `cuda_version` es la version de CUDA con la que fue compilado torch, no necesariamente la del sistema.
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- Usar junto a `torch_device_select` para elegir device y `gpu_info` para estadisticas de VRAM.
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- impure: depende del estado del hardware y de librerias del sistema en tiempo de ejecucion.
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