more training fixes

ANNOTATE/core/real_training_adapter.py

@@ -2507,10 +2507,11 @@ class RealTrainingAdapter:
             for batch in cached_batches:
                 grouped_batches.append(batch)
             
-            # Clear cached_batches to free memory
-            cached_batches.clear()
-            del cached_batches
-            gc.collect()
+            # Don't clear cached_batches yet - grouped_batches contains references to them
+            # We'll clear after training completes
+            # cached_batches.clear()
+            # del cached_batches
+            # gc.collect()
             
             def batch_generator():
                 """
@@ -2577,6 +2578,15 @@ class RealTrainingAdapter:
                 # Generate batches fresh for each epoch
                 for i, batch in enumerate(batch_generator()):
                     try:
+                        # DEBUG: Check if batch has timeframe data
+                        if epoch > 0 and i == 0:
+                            has_1m = batch.get('price_data_1m') is not None
+                            has_1h = batch.get('price_data_1h') is not None
+                            has_1d = batch.get('price_data_1d') is not None
+                            logger.debug(f"Epoch {epoch+1}, Batch 1: has_1m={has_1m}, has_1h={has_1h}, has_1d={has_1d}")
+                            if has_1m:
+                                logger.debug(f"  price_data_1m shape: {batch['price_data_1m'].shape}")
+                        
                         # Store prediction before training (for visualization)
                         # Only store predictions on first epoch and every 10th batch to avoid clutter
                         if epoch == 0 and i % 10 == 0 and self.orchestrator: