refactor: move trainer/models/utils/config to tools/

tools/config.py

@@ -0,0 +1,160 @@
+"""Centralised configuration for ai_mouse.
+
+All magic numbers and hyperparameters live here so they can be tuned
+from one place, overridden per-instance, or serialised to JSON.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from pathlib import Path
+
+
+# ---------------------------------------------------------------------------
+# Training configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class TrainConfig:
+    """Hyperparameters for Flow Matching training."""
+
+    epochs: int = 300
+    batch_size: int = 64
+    lr: float = 3e-4
+    seq_len: int = 64
+    # Transformer backbone
+    d_model: int = 128
+    nhead: int = 4
+    num_layers: int = 4
+    dim_feedforward: int = 256
+    dropout: float = 0.1
+    # Flow matching
+    sigma_min: float = 1e-4
+    # Data augmentation
+    augment: bool = True
+    # Duration distribution bins
+    dist_bins: list[float] = field(
+        default_factory=lambda: [0, 50, 100, 200, 400, 600, 800, 1200, float("inf")]
+    )
+
+
+# ---------------------------------------------------------------------------
+# Generation configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class GenerateConfig:
+    """Tuneable knobs for Flow Matching inference."""
+
+    n_steps: int = 10           # Euler ODE steps
+    seq_len: int = 64
+    dt_clip_min_ms: float = 2.0
+    dt_clip_max_ms: float = 150.0
+
+
+# ---------------------------------------------------------------------------
+# Scroll subsystem configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class ScrollModeConfig:
+    """Parameters for a single scroll collection mode."""
+
+    dist_min: int
+    dist_max: int
+    success_radius: int
+
+
+SCROLL_MODES: dict[str, ScrollModeConfig] = {
+    "target": ScrollModeConfig(dist_min=500, dist_max=3000, success_radius=80),
+    "fast": ScrollModeConfig(dist_min=3000, dist_max=8000, success_radius=120),
+    "precise": ScrollModeConfig(dist_min=200, dist_max=800, success_radius=40),
+}
+
+
+@dataclass
+class ScrollTrainConfig:
+    """Hyperparameters for ScrollCVAE training."""
+
+    epochs: int = 100
+    batch_size: int = 32
+    lr: float = 5e-4
+    seq_len: int = 32
+    beta_max: float = 0.3
+    beta_warmup_epochs: int = 15
+    weight_delta: float = 1.0
+    weight_log_dt: float = 1.5
+
+
+# ---------------------------------------------------------------------------
+# Server configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class ServerConfig:
+    """Web server and data directory settings."""
+
+    host: str = "127.0.0.1"
+    port: int = 8765
+    data_dir: Path = field(default_factory=lambda: Path("data"))
+    canvas_width: int = 800
+    canvas_height: int = 600
+    open_browser: bool = True
+
+
+# ---------------------------------------------------------------------------
+# Pretraining (Balabit) configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class PretrainConfig:
+    """Hyperparameters for Balabit pretraining stage."""
+
+    epochs: int = 200
+    batch_size: int = 128
+    lr: float = 3e-4
+    seq_len: int = 64
+
+
+@dataclass
+class FinetuneConfig:
+    """Hyperparameters for fine-tuning on user-collected data."""
+
+    epochs: int = 50
+    batch_size: int = 64
+    lr: float = 1e-5  # 比预训练小一个数量级，防止灾难性遗忘
+    seq_len: int = 64
+
+
+# ---------------------------------------------------------------------------
+# Balabit adapter configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class BalabitAdapterConfig:
+    """Settings for Balabit CSV → traces.jsonl conversion."""
+
+    window_ms: int = 1200       # click 前回溯窗口
+    min_dist: int = 50          # 最小起终点距离 (px)
+    min_events: int = 5         # 最小 Move 事件数
+    max_span_ms: int = 5000     # 最大段时间跨度 (ms)
+    max_gap_ms: int = 200       # 段内相邻 Move 最大时间差
+
+
+# ---------------------------------------------------------------------------
+# Eval configuration
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class EvalConfig:
+    """Settings for evaluation report generation."""
+
+    n_samples: int = 1000
+    fft_freq_band: tuple[float, float] = (4.0, 12.0)  # 生理震颤频段 (Hz)
+    kl_bins: int = 50