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328cfd50e7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72607
since python isn't available from libtorch, most of lazy tensor
code can't depend on python.
separate python_util into libtorch_python library
make debug_util and IR dump work with or without python by providing
a default function for 'maybe getting python stacktrace' that returns
an empty stacktrace
use a registration mechanism on libtorch_python library load to update
the 'maybe' function to use the real python stacktrace getter
Test Plan:
OSS build tests:
- test_ptltc by itself works
- LTC_SAVE_TENSORS_FILE=log test_ptltc works, and log contains
empty stacktrces
- python examply.py by itself works
- LTC_SAVE_TENSORS_FILE=log test_ptltc works, and log contains
real stacktraces
fbcode build: rely on CI to run test/lazy
Reviewed By: desertfire
Differential Revision: D34115046
fbshipit-source-id: 8d6222963c146da36b3c1b5ff8a638bbc3f1442e
(cherry picked from commit 3717688ade)
592 B
592 B
Lazy Tensor Python Code
Lazy Tensor Core is part of libtorch, which can not depend on python.
Parts of lazy tensor core use python for 2 purposes A) py bindings let python programs call into lazy tensor c++ code B) lazy tensor core calls into python to use it (e.g. for grabbing stack traces)
(A) is trivial since the python bindings only depend on libtorch; (B) requires making libtorch_python register a function with libtorch if loaded, and having a default (no-op) function otherwise. Any functionality that strictly needs to depend on python should be part of the 'python' folder.