test bybit opening/closing orders

NN/models/enhanced_cnn.py

@@ -528,7 +528,7 @@ class EnhancedCNN(nn.Module):
             state_tensor = torch.as_tensor(state, dtype=torch.float32, device=self.device)
             if state_tensor.dim() == 1:
                 state_tensor = state_tensor.unsqueeze(0)
-
+        
         with torch.no_grad():
             q_values, extrema_pred, price_predictions, features, advanced_predictions = self(state_tensor)
             
@@ -537,7 +537,7 @@ class EnhancedCNN(nn.Module):
             action_idx = int(torch.argmax(action_probs_tensor, dim=1).item())
             confidence = float(action_probs_tensor[0, action_idx].item())  # Confidence of the chosen action
             action_probs = action_probs_tensor.squeeze(0).tolist()  # Convert to list of floats for return
-
+            
             # Log advanced predictions for better decision making
             if hasattr(self, '_log_predictions') and self._log_predictions:
                 # Log volatility prediction