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refactoring

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This commit is contained in:
Dobromir Popov
2025-09-08 23:57:21 +03:00
parent 98ebbe5089
commit c3a94600c8
50 changed files with 856 additions and 1302 deletions
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10
web/clean_dashboard.py
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@@ -4711,7 +4711,7 @@ class CleanTradingDashboard:
stored_models = []
# Use unified model registry for saving
from utils.model_registry import save_model
from NN.training.model_manager import save_model
# 1. Store DQN model
if hasattr(self.orchestrator, 'rl_agent') and self.orchestrator.rl_agent:
@@ -6129,7 +6129,7 @@ class CleanTradingDashboard:
# Save checkpoint after training
if loss_count > 0:
try:
from utils.checkpoint_manager import save_checkpoint
from NN.training.model_manager import save_checkpoint
avg_loss = total_loss / loss_count
# Prepare checkpoint data
@@ -6452,7 +6452,7 @@ class CleanTradingDashboard:
# Try to load existing transformer checkpoint first
if transformer_model is None or transformer_trainer is None:
try:
from utils.checkpoint_manager import load_best_checkpoint
from NN.training.model_manager import load_best_checkpoint
# Try to load the best transformer checkpoint
checkpoint_metadata = load_best_checkpoint("transformer", "transformer")
@@ -6687,7 +6687,7 @@ class CleanTradingDashboard:
# Save checkpoint periodically with proper checkpoint management
if transformer_trainer.training_history['train_loss']:
try:
from utils.checkpoint_manager import save_checkpoint
from NN.training.model_manager import save_checkpoint
# Prepare checkpoint data
checkpoint_data = {
@@ -6740,7 +6740,7 @@ class CleanTradingDashboard:
logger.error(f"Error saving transformer checkpoint: {e}")
# Use unified registry for checkpoint
try:
from utils.model_registry import save_checkpoint as registry_save_checkpoint
from NN.training.model_manager import save_checkpoint as registry_save_checkpoint
checkpoint_data = torch.load(checkpoint_path, map_location='cpu') if 'checkpoint_path' in locals() else checkpoint_data