unify model names
This commit is contained in:
Dobromir Popov
@@ -15,19 +15,41 @@ import asyncio
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import logging
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import time
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import threading
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import numpy as np
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import pandas as pd
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from datetime import datetime, timedelta
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from typing import Dict, List, Optional, Any, Tuple, Union
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from dataclasses import dataclass, field
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from collections import deque
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import json
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# Try to import optional dependencies
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try:
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import numpy as np
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HAS_NUMPY = True
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except ImportError:
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np = None
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HAS_NUMPY = False
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try:
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import pandas as pd
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HAS_PANDAS = True
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except ImportError:
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pd = None
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HAS_PANDAS = False
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import os
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import shutil
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import torch
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import torch.nn as nn
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import torch.optim as optim
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# Try to import PyTorch
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try:
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import torch
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import torch.nn as nn
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import torch.optim as optim
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HAS_TORCH = True
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except ImportError:
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torch = None
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nn = None
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optim = None
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HAS_TORCH = False
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from .config import get_config
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from .data_provider import DataProvider
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@@ -227,7 +249,7 @@ class TradingOrchestrator:
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self.rl_agent.load_best_checkpoint() # This loads the state into the model
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# Check if we have checkpoints available
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from NN.training.model_manager import load_best_checkpoint
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result = load_best_checkpoint("dqn_agent")
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result = load_best_checkpoint("dqn")
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if result:
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file_path, metadata = result
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self.model_states['dqn']['initial_loss'] = getattr(metadata, 'initial_loss', None)
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@@ -267,7 +289,7 @@ class TradingOrchestrator:
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checkpoint_loaded = False
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try:
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from NN.training.model_manager import load_best_checkpoint
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result = load_best_checkpoint("enhanced_cnn")
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result = load_best_checkpoint("cnn")
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if result:
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file_path, metadata = result
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self.model_states['cnn']['initial_loss'] = 0.412
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@@ -347,57 +369,96 @@ class TradingOrchestrator:
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self.extrema_trainer = None
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# Initialize COB RL Model - UNIFIED with ModelManager
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cob_rl_available = False
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try:
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from NN.models.cob_rl_model import COBRLModelInterface
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cob_rl_available = True
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except ImportError as e:
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logger.warning(f"COB RL dependencies not available: {e}")
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cob_rl_available = False
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# Initialize COB RL model using unified approach
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self.cob_rl_agent = COBRLModelInterface(
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model_checkpoint_dir="@checkpoints/cob_rl",
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device='cuda' if torch.cuda.is_available() else 'cpu'
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)
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if cob_rl_available:
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try:
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# Initialize COB RL model using unified approach
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self.cob_rl_agent = COBRLModelInterface(
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model_checkpoint_dir="@checkpoints/cob_rl",
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device='cuda' if (HAS_TORCH and torch.cuda.is_available()) else 'cpu'
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)
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# Add COB RL to model states tracking
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self.model_states['cob_rl'] = {
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'initial_loss': None,
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'current_loss': None,
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'best_loss': None,
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'checkpoint_loaded': False
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}
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# Load best checkpoint using unified ModelManager
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checkpoint_loaded = False
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try:
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from NN.training.model_manager import load_best_checkpoint
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result = load_best_checkpoint("cob_rl")
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if result:
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file_path, metadata = result
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self.model_states['cob_rl']['initial_loss'] = getattr(metadata, 'loss', None)
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self.model_states['cob_rl']['current_loss'] = getattr(metadata, 'loss', None)
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self.model_states['cob_rl']['best_loss'] = getattr(metadata, 'loss', None)
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self.model_states['cob_rl']['checkpoint_loaded'] = True
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self.model_states['cob_rl']['checkpoint_filename'] = getattr(metadata, 'checkpoint_id', 'unknown')
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checkpoint_loaded = True
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loss_str = f"{getattr(metadata, 'loss', 'N/A'):.4f}" if getattr(metadata, 'loss', None) is not None else "N/A"
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logger.info(f"COB RL checkpoint loaded: {getattr(metadata, 'checkpoint_id', 'unknown')} (loss={loss_str})")
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except Exception as e:
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logger.warning(f"Error loading COB RL checkpoint: {e}")
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if not checkpoint_loaded:
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# New model - no synthetic data, start fresh
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self.model_states['cob_rl']['initial_loss'] = None
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self.model_states['cob_rl']['current_loss'] = None
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self.model_states['cob_rl']['best_loss'] = None
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self.model_states['cob_rl']['checkpoint_filename'] = 'none (fresh start)'
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logger.info("COB RL starting fresh - no checkpoint found")
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logger.info("COB RL Agent initialized and integrated with unified ModelManager")
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except Exception as e:
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logger.error(f"Error initializing COB RL: {e}")
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self.cob_rl_agent = None
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cob_rl_available = False
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if not cob_rl_available:
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# COB RL not available due to missing dependencies
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# Still try to load checkpoint metadata for display purposes
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logger.info("COB RL dependencies missing - attempting checkpoint metadata load only")
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# Add COB RL to model states tracking
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self.model_states['cob_rl'] = {
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'initial_loss': None,
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'current_loss': None,
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'best_loss': None,
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'checkpoint_loaded': False
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'checkpoint_loaded': False,
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'checkpoint_filename': 'dependencies missing'
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}
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# Load best checkpoint using unified ModelManager
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checkpoint_loaded = False
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# Try to load checkpoint metadata even without the model
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try:
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from NN.training.model_manager import load_best_checkpoint
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result = load_best_checkpoint("cob_rl_agent")
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result = load_best_checkpoint("cob_rl")
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if result:
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file_path, metadata = result
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self.model_states['cob_rl']['initial_loss'] = metadata.loss
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self.model_states['cob_rl']['current_loss'] = metadata.loss
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self.model_states['cob_rl']['best_loss'] = metadata.loss
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self.model_states['cob_rl']['checkpoint_loaded'] = True
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self.model_states['cob_rl']['checkpoint_filename'] = metadata.checkpoint_id
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checkpoint_loaded = True
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loss_str = f"{metadata.loss:.4f}" if metadata.loss is not None else "N/A"
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logger.info(f"COB RL checkpoint loaded: {metadata.checkpoint_id} (loss={loss_str})")
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self.model_states['cob_rl']['checkpoint_filename'] = getattr(metadata, 'checkpoint_id', 'found')
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logger.info(f"COB RL checkpoint metadata loaded (model unavailable): {getattr(metadata, 'checkpoint_id', 'unknown')}")
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else:
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logger.info("No COB RL checkpoint found")
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except Exception as e:
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logger.warning(f"Error loading COB RL checkpoint: {e}")
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logger.debug(f"Could not load COB RL checkpoint metadata: {e}")
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if not checkpoint_loaded:
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# New model - no synthetic data, start fresh
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self.model_states['cob_rl']['initial_loss'] = None
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self.model_states['cob_rl']['current_loss'] = None
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self.model_states['cob_rl']['best_loss'] = None
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self.model_states['cob_rl']['checkpoint_filename'] = 'none (fresh start)'
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logger.info("COB RL starting fresh - no checkpoint found")
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logger.info("COB RL Agent initialized and integrated with unified ModelManager")
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logger.info(" - Uses @checkpoints/ directory structure")
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logger.info(" - Follows same load/save/checkpoint flow as other models")
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logger.info(" - Integrated with enhanced real-time training system")
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except ImportError as e:
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logger.warning(f"COB RL Model not available: {e}")
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self.cob_rl_agent = None
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logger.info("COB RL initialization completed")
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logger.info(" - Uses @checkpoints/ directory structure")
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logger.info(" - Follows same load/save/checkpoint flow as other models")
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logger.info(" - Gracefully handles missing dependencies")
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# Initialize TRANSFORMER Model
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try:
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