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@ -2503,7 +2503,8 @@ class TradingOrchestrator:
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except Exception as e:
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logger.error(f"Error checking signal confirmation for {symbol}: {e}")
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return None
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def _initialize_checkpoint_manager(self):
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def _initialize_checkpoint_manager(self):
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"""Initialize the checkpoint manager for model persistence"""
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try:
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from utils.checkpoint_manager import get_checkpoint_manager
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@ -2520,8 +2521,9 @@ class TradingOrchestrator:
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logger.info("Checkpoint manager initialized for model persistence")
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except Exception as e:
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logger.error(f"Error initializing checkpoint manager: {e}")
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self.checkpoint_manager = None de
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f _save_training_checkpoints(self, models_trained: List[str], performance_score: float):
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self.checkpoint_manager = None
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def _save_training_checkpoints(self, models_trained: List[str], performance_score: float):
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"""Save checkpoints for trained models if performance improved
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This is CRITICAL for preserving training progress across restarts.
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@ -650,7 +650,8 @@ class CleanTradingDashboard:
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# Apply current leverage to unrealized P&L
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leveraged_unrealized_pnl = raw_pnl_per_unit * size * self.current_leverage
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total_session_pnl += leveraged_unrealized_pnlent_position and current_price:ent_position and current_price:ent_position and current_price:ent_position and current_price:ent_position and current_price:
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total_session_pnl += leveraged_unrealized_pnl
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side = self.current_position.get('side', 'UNKNOWN')
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size = self.current_position.get('size', 0)
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entry_price = self.current_position.get('price', 0)
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@ -664,7 +665,7 @@ class CleanTradingDashboard:
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# Apply current leverage to unrealized P&L
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leveraged_unrealized_pnl = raw_pnl_per_unit * size * self.current_leverage
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total_session_pnl += leveraged_unrealized_pnlent_position and current_price:
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total_session_pnl += leveraged_unrealized_pnl
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side = self.current_position.get('side', 'UNKNOWN')
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size = self.current_position.get('size', 0)
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entry_price = self.current_position.get('price', 0)
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