use enhanced orchestrator

training/williams_market_structure.py

@@ -36,7 +36,6 @@ from typing import Dict, List, Optional, Tuple, Any
 from dataclasses import dataclass
 from enum import Enum
 
-
 # Setup logger immediately after logging import
 logger = logging.getLogger(__name__)
 
@@ -167,7 +166,6 @@ except ImportError:
     TrainingDataPacket = None
     print("Warning: TrainingDataPacket could not be imported. Using fallback interface.")
 
-
 class TrendDirection(Enum):
     UP = "up"
     DOWN = "down"
@@ -964,7 +962,6 @@ class WilliamsMarketStructure:
                     else:
                         y_train_batch = y_train
 
-
                     logger.info(f"CNN Training with X_shape: {X_train_batch.shape}, y_shape: {y_train_batch.shape}")
                     # Perform a single step of training (online learning)
                     # Use the wrapper's fit method, not the model's directly
@@ -1340,7 +1337,6 @@ class WilliamsMarketStructure:
             # Emergency fallback: return features as-is but scaled to [0,1] roughly
             return np.clip(features / (np.max(np.abs(features)) + 1e-8), -1.0, 1.0)
 
-
     def _get_cnn_ground_truth(self, 
                               previous_pivot_info: Dict[str, Any], # Contains 'pivot': SwingPoint obj of N-1
                               actual_current_pivot: SwingPoint     # This is pivot N