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[easy][PTE] Reduce unnecessary ref count bumps in callstack debug (#72547)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72547 toTuple() returns a new intrusive pointer that bumps its underlying ref count. Whereas, toTupeRef returns a reference. We can save an unnecessary ref count bump. Based on https://fb.workplace.com/groups/pytorch.edge.team/permalink/1021780808376658/ similar to D34047666 (85d7e73a8a) ghstack-source-id: 148665193 Test Plan: ``` > Executing task: buck: buck test //xplat/caffe2:test_lite_interpreter --config client.id=nuclide < Executing in directory: /data/users/pavithran/fbsource buck test //xplat/caffe2:test_lite_interpreter --config client.id=nuclide clang-9: warning: argument unused during compilation: '-pthread' [-Wunused-command-line-argument] Parsing buck files: finished in 2.1 sec Creating action graph: finished in 0.5 sec [RE] Metadata: Session ID=[reSessionID-66858379-0761-4966-a933-bc7f0d0add95] [RE] Waiting on 0 remote actions. Completed 523 actions remotely, action cache hit rate: 0.00%. Downloaded 3947/5089 artifacts, 20.92 Mbytes, 12.5% cache miss (for updated rules) Building: finished in 01:04.0 min (100%) 5438/5438 jobs, 5192/5438 updated Total time: 01:06.6 min Testing: finished in 06:53.7 min (71 PASS/0 FAIL) BUILD SUCCEEDED RESULTS FOR //xplat/caffe2:test_lite_interpreter PASS 406.0s 71 Passed 0 Skipped 0 Failed //xplat/caffe2:test_lite_interpreter TESTS PASSED Terminal will be reused by tasks, press any key to close it. ``` Reviewed By: kimishpatel Differential Revision: D34082609 fbshipit-source-id: 4bcbdb2d11dd4c3bc392010487dccd2270278222 (cherry picked from commitdd64eb386d)
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@ -222,7 +222,7 @@ ska::flat_hash_map<int64_t, DebugInfoTuple> CallStackDebugInfoUnpickler::
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{},
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{},
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c10::parseType);
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c10::parseType);
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ska::flat_hash_map<int64_t, DebugInfoTuple> callstack_ptrs;
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ska::flat_hash_map<int64_t, DebugInfoTuple> callstack_ptrs;
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auto ivalues = std::move(*std::move(ival).toTuple()).elements();
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const auto& ivalues = ival.toTupleRef().elements();
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for (auto& val : ivalues) {
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for (auto& val : ivalues) {
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const auto& tup_elems = val.toTupleRef().elements();
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const auto& tup_elems = val.toTupleRef().elements();
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TORCH_CHECK(
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TORCH_CHECK(
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