Fixed: Training of baseline models

Author: Vishal-sys-code

results/all_runs/dt_CartPole-v1/training.log

@@ -41,3 +41,41 @@
 2025-11-05 09:19:55,306 [INFO] Dataset found at D:\Github\neuromorphic_decision_transformer\data\CartPole-v1\dataset.npz.
 2025-11-05 09:19:55,307 [INFO] Starting training...
 2025-11-05 09:19:55,445 [INFO] DataLoader created with num_workers=1.
+2025-11-05 10:40:41,355 [INFO] Checking for dataset...
+2025-11-05 10:40:41,375 [INFO] Dataset found at D:\Github\neuromorphic_decision_transformer\data\CartPole-v1\dataset.npz.
+2025-11-05 10:40:41,375 [INFO] Starting training...
+2025-11-05 10:40:41,510 [INFO] Dataset size: 1000 clips
+2025-11-05 10:40:41,516 [INFO] DataLoader created with num_workers=1 and pin_memory=False.
+2025-11-05 10:40:54,189 [INFO] Starting training loop...
+2025-11-05 12:47:08,817 [INFO] Checking for dataset...
+2025-11-05 12:47:08,825 [INFO] Dataset found at D:\Github\neuromorphic_decision_transformer\data\CartPole-v1\dataset.npz.
+2025-11-05 12:47:08,826 [INFO] Starting training...
+2025-11-05 12:47:08,970 [INFO] Dataset size: 1000 clips
+2025-11-05 12:47:08,975 [INFO] DataLoader created with num_workers=1 and pin_memory=False.
+2025-11-05 12:47:20,769 [INFO] Starting training loop...
+2025-11-05 13:09:19,915 [INFO] Checking for dataset...
+2025-11-05 13:09:19,917 [INFO] Dataset found at D:\Github\neuromorphic_decision_transformer\data\CartPole-v1\dataset.npz.
+2025-11-05 13:09:19,918 [INFO] Starting training...
+2025-11-05 13:09:20,034 [INFO] Dataset size: 1000 clips
+2025-11-05 13:09:20,039 [INFO] DataLoader created with num_workers=0 and pin_memory=False.
+2025-11-05 13:09:31,624 [INFO] Starting training loop...
+2025-11-05 13:24:22,013 [INFO] Checking for dataset...
+2025-11-05 13:24:22,027 [INFO] Dataset found at D:\Github\neuromorphic_decision_transformer\data\CartPole-v1\dataset.npz.
+2025-11-05 13:24:22,028 [INFO] Starting training...
+2025-11-05 13:24:22,238 [INFO] Dataset size: 1000 clips
+2025-11-05 13:24:22,244 [INFO] DataLoader created with num_workers=0 and pin_memory=False.
+2025-11-05 13:24:42,828 [INFO] Starting training loop...
+2025-11-05 13:24:42,862 [INFO] Epoch 1, Batch 1
+2025-11-05 13:25:08,877 [INFO] Epoch 1, Batch 2
+2025-11-05 13:25:30,430 [INFO] Epoch 1, Batch 3
+2025-11-05 13:25:55,037 [INFO] Epoch 1, Batch 4
+2025-11-05 13:26:17,308 [INFO] Epoch 1, Batch 5
+2025-11-05 13:26:34,649 [INFO] Epoch 1, Batch 6
+2025-11-05 13:26:53,128 [INFO] Epoch 1, Batch 7
+2025-11-05 13:27:15,121 [INFO] Epoch 1, Batch 8
+2025-11-05 13:27:33,624 [INFO] Epoch 1, Batch 9
+2025-11-05 13:27:47,284 [INFO] Epoch 1, Batch 10
+2025-11-05 13:28:04,851 [INFO] Epoch 1, Batch 11
+2025-11-05 13:28:17,372 [INFO] Epoch 1, Batch 12
+2025-11-05 13:28:33,096 [INFO] Epoch 1, Batch 13
+2025-11-05 13:28:49,192 [INFO] Epoch 1, Batch 14

snn-dt/scripts/train.py

@@ -120,7 +120,7 @@ def train(cfg, logger):
     cfg.dataset.max_timesteps = metadata["max_timesteps"]
 
     # OS-aware num_workers
-    num_workers = cfg.training.get("num_workers", 1 if os.name == "nt" else 4)
+    num_workers = 0
     from torch.utils.data import DataLoader
     train_loader = DataLoader(
         dataset,
@@ -152,6 +152,7 @@ def train(cfg, logger):
         start_time = time.time()
         epoch_losses = []
         for i, batch in enumerate(train_loader):
+            logger.info(f"Epoch {epoch+1}, Batch {i+1}")
             if i >= cfg.training.batches_per_epoch:
                 break
 
@@ -267,6 +268,7 @@ def main():
     cfg = {
         "model": {
             "name": args.model,
+            "seq_len": cfg_raw.get("seq_len"),
             "d_model": cfg_raw.get("hidden_dim", 128),
             "n_heads": cfg_raw.get("n_heads", 4),
             "n_layers": cfg_raw.get("n_layers", 4),