checkpoint 04_05

src/training/train.py

@@ -1,62 +0,0 @@
-from __future__ import annotations
-
-"""Thin wrapper around src.training.trainer.Trainer.
-
-Kept for backward compatibility with src/main.py imports and any external
-scripts that still call `train(...)` directly. After step 4b the body of
-this module is just a delegation.
-
-Note: this module no longer runs standalone — entry point is src/main.py
-(per REQUIREMENTS_GIN_STYLE.md §5):
-    python -m src.main <preset_name>
-"""
-
-from src.conf.hardware_conf import HardwareConfig
-from src.conf.models_common_conf import ModelsCommonConfig
-from src.conf.models_dinov3_conf import DINOv3ModelsConfig
-from src.conf.models_stripnet_conf import StripNetModelsConfig
-from src.conf.pipeline_conf import PipelineConfig
-from src.conf.tracking_conf import TrackingConfig
-from src.conf.training_conf import TrainingConfig
-from src.training.trainer_new import Trainer
-
-# Type alias re-exported for callers.
-# SOFIA v1/v71 model configs exist in src/conf/ but are not yet supported
-# by the trainer (no caption-aware fusion encoder wrapper). Adding them
-# here will result in a NotImplementedError at Trainer.run().
-ModelsConfig = DINOv3ModelsConfig | StripNetModelsConfig
-
-
-def train(
-    pipeline_cfg: PipelineConfig,
-    hardware_cfg: HardwareConfig,
-    training_cfg: TrainingConfig,
-    tracking_cfg: TrackingConfig,
-    models_common_cfg: ModelsCommonConfig,
-    models_cfg: ModelsConfig,
-) -> None:
-    """Build a Trainer and run a full training cycle.
-
-    Args:
-        pipeline_cfg:      Paths, schedule (epochs/eval_every/warmup), seed, output_dir.
-        hardware_cfg:      batch_size, grad_accum, num_workers, AMP, gradient_checkpointing.
-        training_cfg:      Loss + optimizer + sampler recipe.
-        tracking_cfg:      W&B / TensorBoard / Grad-CAM / profiler.
-        models_common_cfg: backbone, baseline_mode, init_gate, lrsclip_path.
-        models_cfg:        Family-specific config selected by models_common_cfg.backbone.
-    """
-    Trainer(
-        pipeline_cfg=pipeline_cfg,
-        hardware_cfg=hardware_cfg,
-        training_cfg=training_cfg,
-        tracking_cfg=tracking_cfg,
-        models_common_cfg=models_common_cfg,
-        models_cfg=models_cfg,
-    ).run()
-
-
-if __name__ == "__main__":
-    raise SystemExit(
-        "Direct execution removed. Use: python -m src.main <preset_name>",
-    )
-