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fix: use max_memory_reserved for accurate VRAM peak tracking

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Adrien Toupet
2025-12-03 11:51:30 -05:00
parent ffba05907d
commit 71ac9ffe54
1 changed files with 3 additions and 3 deletions
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src/optimization/memory_manager.py
+3 -3
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@@ -138,7 +138,7 @@ def get_vram_usage(device: Optional[torch.device] = None, debug: Optional['Debug
debug: Optional debug instance for logging
Returns:
tuple: (allocated_gb, reserved_gb, max_allocated_gb)
tuple: (allocated_gb, reserved_gb, max_reserved_gb)
Returns (0, 0, 0) if no GPU available
"""
try:
@@ -149,8 +149,8 @@ def get_vram_usage(device: Optional[torch.device] = None, debug: Optional['Debug
device = torch.device(device)
allocated = torch.cuda.memory_allocated(device) / (1024**3)
reserved = torch.cuda.memory_reserved(device) / (1024**3)
max_allocated = torch.cuda.max_memory_allocated(device) / (1024**3)
return allocated, reserved, max_allocated
max_reserved = torch.cuda.max_memory_reserved(device) / (1024**3)
return allocated, reserved, max_reserved
elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
# MPS doesn't support per-device queries - uses global memory tracking
allocated = torch.mps.current_allocated_memory() / (1024**3)