Tot Alloc and Tot Freed shows the memory size of total allocations and freed memory during the current script execution.
E.g. in this code snippet I’m recreating a single tensor, which gets deleted once the script returns from f():
def f():
    x = torch.randn(1024, device='cuda')

print(torch.cuda.memory_summary())
for _ in range(1000):
    f()
print(torch.cuda.memory_summary())

|===========================================================================|
|                  PyTorch CUDA memory summary, device ID 0                 |
|---------------------------------------------------------------------------|
|            CUDA OOMs: 0            |        cudaMalloc retries: 0         |
|===========================================================================|
|        Metric         | Cur Usage  | Peak Usage | Tot Alloc  | Tot Freed  |
|---------------------------------------------------------------------------|
| Allocated memory      |       0 B  |    4096 B  |    4000 KB |    4000 KB |
|       from large pool |       0 B  |       0 B  |       0 KB |       0 KB |
|       from small pool |       0 B  |    4096 B  |    4000 KB |    4000 KB |
|---------------------------------------------------------------------------|

As you can see, no memory is currently used and the Tot counters show the 1000 * 4KB allocations and deletions.