mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
a2a75be0f8
Requested by Simon on a different PR Pull Request resolved: https://github.com/pytorch/pytorch/pull/156128 Approved by: https://github.com/xmfan
50 lines
1.2 KiB
Python
50 lines
1.2 KiB
Python
import os
|
|
import timeit
|
|
|
|
import torch.fx
|
|
from torch._dynamo.utils import counters
|
|
from torch._inductor.utils import clear_caches, fresh_cache
|
|
|
|
|
|
N = 10000
|
|
K = 100
|
|
|
|
|
|
def huge_graph(x):
|
|
for _ in range(N):
|
|
x = x.sin()
|
|
return x
|
|
|
|
|
|
def main():
|
|
torch._inductor.config.fx_graph_cache = True
|
|
torch._inductor.config.fx_graph_remote_cache = False
|
|
|
|
with fresh_cache():
|
|
a = torch.randn(4).cuda()
|
|
compiled_fn = torch.compile(huge_graph, backend="inductor")
|
|
|
|
# write to cache
|
|
compiled_fn(a)
|
|
assert counters["inductor"]["fxgraph_cache_miss"] == 1
|
|
|
|
def setup():
|
|
torch._dynamo.reset()
|
|
clear_caches()
|
|
for m in torch._inductor.codecache.PyCodeCache.cache.values():
|
|
os.remove(m.__file__)
|
|
counters.clear()
|
|
|
|
def fn():
|
|
result = compiled_fn(a)
|
|
assert counters["inductor"]["fxgraph_cache_miss"] == 0
|
|
assert counters["inductor"]["fxgraph_cache_hit"] == 1
|
|
return result
|
|
|
|
t = min(timeit.repeat(fn, setup=setup, number=K, repeat=3))
|
|
print(f"took {t:.1f}s")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|