encountered here as same, and can be safely used. If it fails and
   evaluates to False, TorchDynamo identifies the code in the cache
   as not valid, and can be thrown out in favor of a new entry,
   through recompilation or a graph break.
Python Frame Evaluation and PEP 523
The functionality of TorchDynamo is based on PEP 523.
TorchDynamo installs a frame evaluation function on Python by using
_PyInterpreterState_SetEvalFrameFunc. TorchDynamo has a hook where
Python can hand control back to us during evaluation.
The function we have installed is "convert_frame" or
"convert_frame_assert" in the "nopython=True" case, but glossing over
that nuance for now, letâs take a look at "convert_frame_assert", as
"convert_frame" proxies to it.
We can find it on line 20 of convert_frame.py, with a signature as
follows:
def  convert_frame_assert(compiler_fn: Callable, one_graph=True):
This function wraps the entry point of where Python invokes