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[FRONTEND] force quantile tensors to be float; prevents accidents (#1741)

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In particular, sometimes this was failing with:

```
RuntimeError: quantile() input tensor must be either float or double dtype
```

Fixes https://github.com/pytorch/pytorch/issues/103054

Signed-off-by: Edward Z. Yang <ezyang@meta.com>

---------

Signed-off-by: Edward Z. Yang <ezyang@meta.com>
This commit is contained in:
Edward Z. Yang
2023-06-05 23:55:40 -04:00
committed by GitHub
parent 1eedef3596
commit f294a18864
1 changed files with 2 additions and 2 deletions
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python/triton/testing.py
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@@ -86,9 +86,9 @@ def do_bench(fn, warmup=25, rep=100, grad_to_none=None,
end_event[i].record()
# Record clocks
torch.cuda.synchronize()
times = torch.tensor([s.elapsed_time(e) for s, e in zip(start_event, end_event)])
times = torch.tensor([s.elapsed_time(e) for s, e in zip(start_event, end_event)], dtype=torch.float)
if quantiles is not None:
ret = torch.quantile(times, torch.tensor(quantiles)).tolist()
ret = torch.quantile(times, torch.tensor(quantiles, dtype=torch.float)).tolist()
if len(ret) == 1:
ret = ret[0]
return ret