Upload self_healing/__init__.py

self_healing/__init__.py

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+"""
+Self-Healing Training System (SHTS)
+===================================
+
+A fully autonomous self-healing layer for Hugging Face TRL trainers.
+
+Architecture:
+  1. DETECTION  — SelfHealingCallback monitors loss, gradients, OOM, memory
+  2. DIAGNOSIS  — Root-cause classifier: NaN/divergence/OOM/data/API errors
+  3. RECOVERY   — HealingActions applies fixes: rollback, reduce LR, halve batch
+  4. ORCHESTRATION — SelfHealingTrainer retry loop with state persistence
+
+Based on:
+  - Unicron (arxiv:2401.00134): Cost-aware self-healing at cluster scale
+  - ZClip (arxiv:2504.02507): Z-score adaptive gradient clipping
+  - PTT (post-training-toolkit): DiagnosticsCallback + postmortem pattern
+  - Pioneer Agent (arxiv:2604.09791): Structured decision tree for iteration
+  - Deep Researcher (arxiv:2604.05854): Dry-run validation pattern
+
+Usage:
+    from self_healing import SelfHealingTrainer, HealingConfig
+    from trl import SFTTrainer, SFTConfig
+
+    trainer = SFTTrainer(model=model, args=training_args, train_dataset=ds, tokenizer=tok)
+    sh = SelfHealingTrainer(trainer, HealingConfig())
+    sh.train()
+
+Author: Autonomous ML Intern
+"""
+
+from .core import (
+    HealingConfig,
+    SelfHealingCallback,
+    HealingActions,
+    SelfHealingTrainer,
+    ZClip,
+    FailureType,
+    FAILURE_RECIPES,
+)
+
+__version__ = "1.0.0"
+__all__ = [
+    "HealingConfig",
+    "SelfHealingCallback", 
+    "HealingActions",
+    "SelfHealingTrainer",
+    "ZClip",
+    "FailureType",
+    "FAILURE_RECIPES",
+]