feat: Add multi-GPU training and improve config/ignore

Add train_multigpu.py for distributed data parallel training.

Update train.py to save the training configuration to a JSON file.

Generalize .gitignore to exclude all *.pt checkpoint files.

Delete obsolete train_dpp.py file.

train.py

@@ -6,6 +6,7 @@ import numpy as np
 import math
 import tqdm
 import matplotlib.pyplot as plt
+import json
 
 from models import TimeAwareGPT2, CombinedLoss
 from utils import PatientEventDataset
@@ -47,6 +48,13 @@ def main():
     model_filename = f"best_model_n_embd_{config.n_embd}_n_layer_{config.n_layer}_n_head_{config.n_head}.pt"
     checkpoint_filename = f"best_model_checkpoint_n_embd_{config.n_embd}_n_layer_{config.n_layer}_n_head_{config.n_head}.pt"
 
+    # --- 0. Save Configuration ---
+    config_filename = f"config_n_embd_{config.n_embd}_n_layer_{config.n_layer}_n_head_{config.n_head}.json"
+    config_dict = {k: v for k, v in vars(config).items() if not k.startswith('__')}
+    with open(config_filename, 'w') as f:
+        json.dump(config_dict, f, indent=4)
+    print(f"Configuration saved to {config_filename}")
+
     # --- 1. Data Loading ---
     print(f"Loading data from {config.train_data_path} and {config.val_data_path}...")
     train_data_arr = np.memmap(config.train_data_path, dtype=np.uint32, mode='r').reshape(-1, 3)