Update and rename 1 to __init__.py

Author: JayDS22

src/utils/1

@@ -0,0 +1,66 @@
+
+"""
+Utility functions and helper modules
+
+This module contains utility functions used across the framework.
+"""
+
+# Placeholder for future utility functions
+# Example utilities that could be added:
+# - Data preprocessing helpers
+# - Metric computation utilities
+# - Visualization helpers
+# - File I/O utilities
+
+__all__ = []
+
+def get_device(local_rank=0):
+    """Get PyTorch device for given local rank"""
+    import torch
+    if torch.cuda.is_available():
+        return torch.device(f'cuda:{local_rank}')
+    return torch.device('cpu')
+
+def set_seed(seed=42):
+    """Set random seed for reproducibility"""
+    import torch
+    import numpy as np
+    import random
+    
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)
+    
+def count_parameters(model):
+    """Count trainable parameters in model"""
+    return sum(p.numel() for p in model.parameters() if p.requires_grad)
+
+def format_time(seconds):
+    """Format seconds to human readable time"""
+    hours = int(seconds // 3600)
+    minutes = int((seconds % 3600) // 60)
+    secs = int(seconds % 60)
+    return f"{hours:02d}:{minutes:02d}:{secs:02d}"
+
+def get_gpu_memory_usage():
+    """Get current GPU memory usage"""
+    import torch
+    if torch.cuda.is_available():
+        allocated = torch.cuda.memory_allocated() / 1024**3  # GB
+        reserved = torch.cuda.memory_reserved() / 1024**3
+        return {
+            'allocated_gb': allocated,
+            'reserved_gb': reserved,
+            'free_gb': torch.cuda.get_device_properties(0).total_memory / 1024**3 - allocated
+        }
+    return None
+
+__all__.extend([
+    'get_device',
+    'set_seed',
+    'count_parameters',
+    'format_time',
+    'get_gpu_memory_usage',
+])