init gogo

crypto/gogo/main.py

@@ -0,0 +1,47 @@
+# main.py
+
+import asyncio
+import torch
+import torch.nn as nn
+import torch.optim as optim
+from data.live_data import LiveDataManager
+from model.transformer import Transformer
+from training.train import train
+from data.data_utils import preprocess_data  # Import preprocess_data
+
+async def main():
+    symbol = 'BTC/USDT'
+    data_manager = LiveDataManager(symbol)
+
+    # Model parameters (adjust for ~1B parameters)
+    input_dim = 6 + len([5, 10, 20, 60, 120, 200])  # OHLCV + EMAs
+    d_model = 512
+    num_heads = 8
+    num_layers = 6
+    d_ff = 2048
+    dropout = 0.1
+
+    model = Transformer(input_dim, d_model, num_heads, num_layers, d_ff, dropout)
+
+    optimizer = optim.AdamW(model.parameters(), lr=1e-4, weight_decay=1e-5)
+
+    # Define loss functions
+    criterion_candle = nn.MSELoss()
+    criterion_volume = nn.MSELoss()  # Consider a different loss for volume if needed
+    criterion_ticks = nn.MSELoss()
+
+    # Check for CUDA availability and set device
+    if torch.cuda.is_available():
+        device = torch.device('cuda')
+        print("Using CUDA")
+    else:
+        device = torch.device('cpu')
+        print("Using CPU")
+    try:
+        await train(model, data_manager, optimizer, criterion_candle, criterion_volume, criterion_ticks, num_epochs=10, device=device)
+    except KeyboardInterrupt:
+        print("Training stopped manually.")
+    finally:
+        await data_manager.close()
+if __name__ == '__main__':
+    asyncio.run(main())