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c5b9dc1f40
Summary: This is surprisingly expensive when the stack is deep. We can instead just process the specific stack frame that's relevant -- it's much faster.
Test Plan:
```
import inspect
import sys
import time
def make_deep_stack(fn, n: int = 10):
if n > 0:
return make_deep_stack(fn, n - 1)
return fn()
def full_stack():
return inspect.stack()[1][3]
def via_current_frame():
return inspect.getframeinfo(sys._getframe(1))[2]
start = time.perf_counter()
for _ in range(1000):
make_deep_stack(full_stack)
print(f"full_stack took {time.perf_counter() - start}s")
start = time.perf_counter()
for _ in range(1000):
make_deep_stack(via_current_frame)
print(f"via_current_frame took {time.perf_counter() - start}s")
> full_stack took 31.788201928138733s
> via_current_frame took 2.33455612603575s
```
Differential Revision: D47674015
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105940
Approved by: https://github.com/zou3519