feat(ml): auto-commit con 14 cambios

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 01:22:02 +02:00
parent 88b5b27dc0
commit aec5d82011
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+---
+name: sdcpp_python_generate
+kind: function
+lang: py
+domain: ml
+version: "1.0.0"
+purity: impure
+signature: "def sdcpp_python_generate(sd: Any, cfg: GenerationConfig) -> ImageGenResult"
+description: "Genera una imagen con un StableDiffusion (stable-diffusion-cpp-python) usando GenerationConfig como contrato. Mapea sampler, mide duracion y retorna ImageGenResult con meta del backend."
+tags: [ml, stable-diffusion, sdcpp, inference, backend, generate, txt2img]
+uses_functions: [sdcpp_python_load_py_ml]
+uses_types: [generation_config_py_ml, image_gen_result_py_ml]
+returns: [image_gen_result_py_ml]
+returns_optional: false
+error_type: "error_go_core"
+imports: [stable_diffusion_cpp, PIL]
+params:
+  - name: sd
+    desc: "Instancia StableDiffusion cargada via sdcpp_python_load. Debe tener metodo generate_image()."
+  - name: cfg
+    desc: "Contrato de parametros de generacion. cfg.sampler debe ser uno de: euler | euler_a | dpm++2m | dpm++2m_v2 | heun | dpm2 | lcm."
+output: "ImageGenResult con image=PIL.Image (primera del batch), meta con backend/model/sampler/seed/wtype, duration_ms medido, vram_peak_mb=None."
+tested: true
+tests:
+  - "generate retorna ImageGenResult valido"
+  - "duration_ms mayor que cero"
+  - "meta backend es sdcpp_python"
+test_file_path: "python/functions/ml/tests/test_sdcpp_python_backend.py"
+file_path: "python/functions/ml/sdcpp_python_generate.py"
+---
+
+## Ejemplo
+
+```python
+import sys
+sys.path.insert(0, "python/functions/ml")
+from model_ref import ModelRef
+from generation_config import GenerationConfig
+from sdcpp_python_load import sdcpp_python_load
+from sdcpp_python_generate import sdcpp_python_generate
+
+model = ModelRef(
+    name="sd-turbo",
+    model_type="sd15",
+    quantization="fp16",
+    path="/home/lucas/vaults/imagegen_models/diffusers/sd-turbo/sd_turbo.safetensors",
+)
+sd = sdcpp_python_load(model)
+
+cfg = GenerationConfig(
+    prompt="a red cat sitting on a wooden table",
+    seed=42,
+    steps=4,
+    cfg_scale=1.0,
+    sampler="euler_a",
+    width=512,
+    height=512,
+    model=model,
+)
+result = sdcpp_python_generate(sd, cfg)
+result.image.save("/tmp/output.png")
+print(f"Generado en {result.duration_ms}ms, meta={result.meta}")
+```
+
+## Notas
+
+- El sampler mapping canonico: euler->euler, euler_a->euler_a, dpm++2m->dpmpp2m,
+  dpm++2m_v2->dpmpp2mv2, heun->heun, dpm2->dpm2, lcm->lcm.
+- API usada: `StableDiffusion.generate_image()` (binding 0.4.7+). Versiones anteriores
+  exponían `txt_to_img()` — actualizar el package si se encuentra ese error.
+- `vram_peak_mb` siempre None: stable-diffusion-cpp-python no expone medicion de VRAM.
+- `clip_skip`: -1 le dice al backend que use el valor por defecto del modelo (equivale a
+  no especificarlo). Si cfg.clip_skip es None, se pasa -1.
+- El campo `wtype` en meta se extrae via `getattr(sd, 'wtype', 'unknown')` ya que el
+  binding no garantiza el atributo en todas las versiones.
+---