feat: register hyper paradigms in chimera/__init__.py (v5.3)

chimera/__init__.py

@@ -1,8 +1,8 @@
-"""Chimera 5.2 — CPU-first causal LM with ternary 1.58-bit weights."""
+"""Chimera 5.3 — CPU-first causal LM with ternary 1.58-bit weights."""
 
 from .config import load_config, scale_config, tiny_config
 
-__version__ = "5.2.0"
+__version__ = "5.3.0"
 
 __all__ = [
     "load_config", "scale_config", "tiny_config",
@@ -14,6 +14,11 @@ __all__ = [
     "SelfEvolutionEngine", "SemanticMemory", "InPlaceTTT",
     "EpisodicCaseMemory", "MetaGuidelineBank", "SelfFeedback",
     "LoopDepthClassifier",
+    # v5.3 — Hyper paradigms
+    "GrowLengthDataset", "GrowLengthScheduler",
+    "apply_reservoir_freezing", "SparseMeZOOptimizer",
+    "precompute_ternary_cache", "pack_documents",
+    "ProgressiveUnfreezer", "cosine_lr",
 ]
 
 
@@ -37,4 +42,10 @@ def __getattr__(name):
                 "LoopDepthClassifier"}:
         from . import evolution as _evo
         return getattr(_evo, name)
+    if name in {"GrowLengthDataset", "GrowLengthScheduler",
+                "apply_reservoir_freezing", "SparseMeZOOptimizer",
+                "precompute_ternary_cache", "pack_documents",
+                "ProgressiveUnfreezer", "cosine_lr"}:
+        from . import hyper as _hyp
+        return getattr(_hyp, name)
     raise AttributeError(name)