Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/
Codegen changes include:
* codegen improvement:
i. allow non-root trivial reductions, allow empty/no-op fusion
ii. fixes vectorization checks and size calculation
iii. bank conflict handle improvement
iv. enables transpose scheduler
* misc:
i. CI tests failure fixes
ii. cpp tests file clean up
iii. trivial forwarding supports added in codegen runtime
iv. added factory methods support in codegen
Commits that's in this PR from the devel branch:
```
7117a7e37ebec372d9e802fdfb8abb7786960f4a patching nvfuser conv cudnn test numerics mismatch (#2048)
65af1a4e7013f070df1ba33701f2d524de79d096 Inserting sync for redundant parallel types is already done at the (#2023)
6ac74d181689c8f135f60bfc1ec139d88941c98c Fix sync map (#2047)
f5bca333355e2c0033523f3402de5b8aac602c00 Bank conflict checker improvements (#2032)
d2ca7e3fd203537946be3f7b435303c60fa7f51e Minor update on cp.async code generation. (#1901)
d36cf61f5570c9c992a748126287c4e7432228e0 Test file cleanup (#2040)
0b8e83f49c2ea9f04a4aad5061c1e7f4268474c6 Allow non-root trivial reductions (#2037)
a2dfe40b27cd3f5c04207596f0a1818fbd5e5439 Fix vectorize size calculation (#2035)
e040676a317fe34ea5875276270c7be88f6eaa56 Use withPredicate to replace setPredicate to maintain Exprs immutable (#2025)
197221b847ad5eb347d7ec1cf2706733aacbf97c removing ci workflow (#2034)
40e2703d00795526e7855860aa00b9ab7160755f Reduction rand like patch (#2031)
bc772661cbdb3b711d8e9854ae9b8b7052e3e4a3 Add utility for checking bank conflict of shared memory (#2029)
ddd1cf7695f3fb172a0e4bcb8e4004573617a037 Add back FusionReductionWithTrivialReduction_CUDA (#2030)
fbd97e5ef15fa0f7573800e6fbb5743463fd9e57 Revert "Cleanup trivial reduction workarounds (#2006)" (#2024)
bca20c1dfb8aa8d881fc7973e7579ce82bc6a894 Cleanup trivial reduction workarounds (#2006)
e4b65850eee1d70084105bb6e1f290651adde23e Trivial forwarding (#1995)
1a0e355b5027ed0df501989194ee8f2be3fdd37a Fix contiguity analysis of predicates to match updated contiguity. (#1991)
a4effa6a5f7066647519dc56e854f4c8a2efd2a7 Enable output allocation cache (#2010)
35440b7953ed8da164a5fb28f87d7fd760ac5e00 Patching bn inference (#2016)
0f9f0b4060dc8ca18dc65779cfd7e0776b6b38e8 Add matmul benchmark (#2007)
45045cd05ea268f510587321dbcc8d7c2977cdab Enable tests previously disabled due to an aliasing bug (#2005)
967aa77d2c8e360c7c01587522eec1c1d377c87e Contiguous indexing for View operations (#1990)
a43cb20f48943595894e345865bc1eabf58a5b48 Make inlining even more modular (#2004)
dc458358c0ac91dfaf4e6655a9b3fc206fc0c897 Test util cleanup (#2003)
3ca21ebe4d213f0070ffdfa4ae5d7f6cb0b8e870 More strict validation (#2000)
a7a7d573310c4707a9f381831d3114210461af01 Fix build problem (#1999)
fc235b064e27921fa9d6dbb9dc7055e5bae1c222 Just fixes comments (#1998)
482386c0509fee6edb2964c5ae72074791f3e43a cleanup (#1997)
4cbe0db6558a82c3097d281eec9c85ad2ea0893a Improve divisible split detection (#1970)
42ccc52bdc18bab0330f4b93ed1399164e2980c9 Minor build fix. (#1996)
fcf8c091f72d46f3055975a35afd06263324ede6 Cleanup of lower_utils.cpp: Isolate out GpuLower usage (#1989)
15f2f6dba8cbf408ec93c344767c1862c30f7ecc Move ConcretizedBroadcastDomains to shared_ptr in GpuLower. (#1988)
8f1c7f52679a3ad6acfd419d28a2f4be4a7d89e2 Minor cleanup lower_unroll.cpp (#1994)
1d9858c80319ca7f0037db7de5f04e47f540d76c Minor cleanup (#1992)
f262d9cab59f41c669f53799c6d4a6b9fc4267eb Add support for uniform RNG (#1986)
eb1dad10c73f855eb1ecb20a8b1f7b6edb0c9ea3 Remove non-const functions, remove GpuLower instance on build, pass in ca_map. (#1987)
634820c5e3586c0fe44132c51179b3155be18072 Add support for some empty fusion (#1981)
eabe8d844ad765ee4973faa4821d451ef71b83c3 Segment self mapping fusions (#1954)
e96aacfd9cf9b3c6d08f120282762489bdf540c8 Enable Transpose operation (#1882)
425dce2777420248e9f08893765b5402644f4161 Add a null scheduler that helps segmenting away no-op schedules (#1835)
306d4a68f127dd1b854b749855e48ba23444ba60 Fix canScheduleCompileTime check of transpose scheduler (#1969)
b1bd32cc1b2ae7bbd44701477bddbcfa6642a9be Minor fix (#1967)
bd93578143c1763c1e00ba613a017f8130a6b989 Enable transpose scheduler (#1927)
b7a206e93b4ac823c791c87f12859cf7af264a4c Move scheduler vectorize utilities into their own file (#1959)
d9420e4ca090489bf210e68e9912bb059b895baf View scheduling (#1928)
c668e13aea0cf21d40f95b48e0163b812712cdf2 Upstream push ci fixes (#1965)
c40202bb40ce955955bb97b12762ef3b6b612997 Fix dump effective bandwidth (#1962)
93505bcbb90a7849bd67090fe5708d867e8909e4 WAR on index mapping when exact and permissive maps differ (#1960)
45e95fd1d3c773ee9b2a21d79624c279d269da9f Allow splitting inner-most ID to create virtual innermost ID in transpose scheduler (#1930)
a3ecb339442131f87842eb56955e4f17c544e99f Improve the comments at the beginning of index_compute.h (#1946)
f7bc3417cc2923a635042cc6cc361b2f344248d6 Remove unused variables (#1955)
df3393adbb5cb0309d091f358cfa98706bd4d313 Some cleanup (#1957)
7d1d7c8724ab5a226fad0f5a80feeac04975a496 TVDomainGuard factory (#1953)
357ba224c0fb41ed3e4e8594d95599c973f4a0ca Fill allocation with nan on tests (#1956)
8eafc54685d406f5ac527bcbacc475fda4492d7a Fix detection of unmappable root domains (#1952)
90a51f282601ba8ebd4c84b9334efd7762a234bc Some indexing cleanups, Add eye support (#1940)
ddc01e4e16428aec92f9c84d698f959b6436a971 Exclude unsupported data types (#1951)
992e17c0688fe690c51b50e81a75803621b7e6aa test the groups the same order as they are merged (#1949)
208262b75d1fed0597a0329d61d57bc8bcd7ff14 Move detection of self mapping IDs to IterDomainGraph from (#1941)
ac4de38c6ee53b366e85fdfe408c3642d32b57df Merge pull request #1945 from csarofeen/master_merge_0828
631094891a96f715d8c9925fb73d41013ca7f2e3 Add full, full_like, zeros, zeros_like, ones, ones_like (#1943)
aab10bce4541204c46b91ff0f0ed9878aec1bfc4 Merge remote-tracking branch 'upstream/viable/strict' into HEAD
4c254c063bb55887b45677e3812357556a7aa80d Fix arange when step is negative (#1942)
89330aa23aa804340b2406ab58899d816e3dc3d2 Tensor factories must set the output shape as its input (#1939)
```
RUN_TORCHBENCH: nvfuser
Differential Revision: [D40869846](https://our.internmc.facebook.com/intern/diff/D40869846)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87779
Approved by: https://github.com/davidberard98
Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/
Codegen changes include:
- codegen improvement:
i. improved view support on pointwise and transpose scheduler
ii. grouped grid welford added for better outer-norm grid persistence in normalization
- misc:
i. new composite ops added: variance_mean , arange,
ii. fixes misaligned address for transpose scheduler
iii. refactor on separation of compilation API from execution API to prepare us for async compilation
iv. double type support on expression evaluator
v. PYTORCH_NVFUSER_DUMP refactor to save PTX and CUBIN
Commits that's in this PR from the devel branch:
```
89330aa23aa804340b2406ab58899d816e3dc3d2 Tensor factories must set the output shape as its input (#1939)
b2fd01ea9346712c6d6f623ca6addbc4888d008e arange support (#1933)
56c00fd3922dad7dfc57351ad7d780f0f2f8e4ed Double support on all expression evaluators (#1937)
371f28223e57fe3f6b5e50a0a45177e6a5c0785c Improve trivial reduction merge support (#1931)
1d0c26790e5647920b40d419d26815bbe310b3a6 Test `rand` in a fusion with zero tensor input (#1932)
0dab160fb2177d178eef3148c6a529e0855009e9 Fix softmax bwd sizes. (#1890)
ef98f360f6d3e3e1cc662ecb65202d88150f128d Fix a bug (#1936)
63132a0c56508c550084b07fb76a3df865102d00 Propagate permissive mapping information into indexing pass (#1929)
b4ac2c88d78078ee4d8b21c4fc51645b5710a282 Map IterationDomains through view operations. (#1919)
c0a187a7619d7cf9dc920294e15461791e8d6d4d do not use deprecated functions (#1935)
88de85e758c5e4afb7b6e746573c0d9a53b4cea7 Upstream cherry pick fixes 0811 (#1934)
b247dcf7c57dc6ac3f7a799b0a6beb7770536a74 Separate kernel compilation API from kernel execution API (#1914)
b34e3b93ee1a8030730c14af3995dd95665af07d Fix `ir_utils::hasBlockSync` + misc fixes in transpose scheduler (#1924)
14a53e6707f43bf760494c238a46386d69830822 Nullary RNGOp (#1892)
3c3c89e638f5172cafb0761f22bacd1fd695eec3 Misc fixes/tuning for transpose scheduler (#1912)
20cf109c8b44d48f61977e35bae94368985144ac Grouped grid welford (#1921)
6cf7eb024c9e53c358cbe56597e117bad56efefd Transpose scheduler small dim sizes better support (#1910)
9341ea9a5bf42f9b14ccad0c94edbc79fc5bb552 Disabled ViewPersistentShmoo sizes that results in NAN (#1922)
057237f66deeea816bb943d802a97c1b7e4414ab Fix CUDA driver error: misaligned address for transpose scheduler (#1918)
3fb3d80339e4f794767a53eb8fdd61e64cf404a2 Add variance_mean function using Welford (#1907)
98febf6aa3b8c6fe4fdfb2864cda9e5d30089262 Remove DisableOption::UnrollWithRng (#1913)
ee8ef33a5591b534cf587d347af11e48ba7a15d4 Minor fix for the debug interface of using PTX directly (#1917)
6e8f953351f9dabfd1f991d8431cecb6c2ce684d Add PYTORCH_NVFUSER_DUMP options to save PTX and CUBIN (#1916)
5eefa9a72385f6a4b145680a9dcc52d7e8293763 dopt is only available since nvrtc 11.7 (#1915)
2ec8fc711eafc72451eebf0f5e2a98a38bf3f6ef Kill computeAtBetween (#1911)
d0d106a1d9af118d71673173674e875be35d259d Improve view support on pointwise and transpose scheduler (#1906)
e71e1ecefe67219846070590bbed54bbc7416b79 Fix name clash of RNG with shared memory (#1904)
3381793a253689abf224febc73fd3fe2a0dbc921 Fix mutator and sameAs for expanded IterDomain (#1902)
```
RUN_TORCHBENCH: nvfuser
Differential Revision: [D39324552](https://our.internmc.facebook.com/intern/diff/D39324552)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84626
Approved by: https://github.com/malfet
And use it throughout the CMakeLists and rectify `IF(APPLE)`/`IF(GNU_CXX_VERSION VERSION_GREATER A.B)` and so on
Also, add `target_compile_options_if_supported` and use it in `Dependencies.cmake` as well as in test's `CMakeListst.txt`
Delete `-Wno-unknown-warning-option` to test that conditions indeed working as expected
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82883
Approved by: https://github.com/seemethere
And use it throughout the CMakeLists and rectify `IF(APPLE)`/`IF(GNU_CXX_VERSION VERSION_GREATER A.B)` and so on
Also, add `target_compile_options_if_supported` and use it in `Dependencies.cmake` as well as in test's `CMakeListst.txt`
Delete `-Wno-unknown-warning-option` to test that conditions indeed working as expected
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82883
Approved by: https://github.com/seemethere
Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/
Bug fixes and minor refactor
Squashed commits to WAR github API
Commits that's actually in this PR from the devel branch:
```
4c60e7dff22a494632370e5df55c011007340d06 Add examples infrastructure for using nvFuser in a standalone program (#1725)
02a05d98334ffa580d73ccb28fdb8c577ad296fe Fix issue #1751 (#1753)
8a69aa320bd7629e1709fe5ceb7104d2c88ec84c Refactor NvFuser transpose API to match eager mode behavior (#1746)
ffdf6b7709048170d768217fcd7083fc8387f932 Remove BroadcastWithoutStride. (#1738)
02bab16035e70734450c02124f5cdaa95cf5749d Fix flipping of a boolean flag (#1745)
465d66890c8242e811224359cbdb1c2915490741 cleanup (#1744)
26d354e68720bc7dd2d3b1338ac01b707a230b6a fixing noncontig broadcast (#1742)
856b6b2f9073662dd98ca22ba6c3540e20eb1cdd Add IterDomainBuilder (#1736)
1fd974f912cd4c1e21cbd16e2abb23598d66a02f fixing warning for gcc7 (#1732)
de2740a43a869f8272c2648e091d7b8235097db9 disabling complex in python tests for #1730 (#1733)
fbbbe0a2e7c7a63e0e2719b8bfccb759b714221a fixing MSVC build (#1728)
b5feee5e2b28be688dbddc766f3c0220389c8175 Fix the fused reduction runtime kernel (#1729)
5247682dff5980bb66edf8d3aac25dea2ef2ced5 Re-entrant GroupedGridReduction (#1727)
```
RUN_TORCHBENCH: nvfuser
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79147
Approved by: https://github.com/davidberard98
Summary:
Things changed in this PR that requires review:
test/forward_backward_compatibility/check_forward_backward_compatibility.py
Our previous function overload extension names were wrong and has been updated in this PR, hence the compatibility list updated.
nvfuser code updates with bug fixes towards failures we encountered in OpInfoTests as well as failures reported by AOTAutograd team.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73627
Reviewed By: Chillee
Differential Revision: D34765458
Pulled By: davidberard98
fbshipit-source-id: c81f3d6a1b723fb3a8ba419b7f82227f70440ca7
(cherry picked from commit b6a2c362c37051e44fac31687b2fe272f776551e)
Summary:
Things changed in this PR that requires review:
1. aten/src/ATen/core/interned_strings.h
2. torch/csrc/jit/ir/alias_analysis.h : exposing createValue to allow efficient mutation
3. torch/csrc/jit/runtime/symbolic_shape_registry.cpp : added gelu/tanh/erf in registry
4. torch/jit/_script.py : throws scripting model sees autocast as decorator since it's not supported
nvfuser code update:
1. codegen improvements and performance tuning
2. integration bug fixes for shape expression logic
3. kernel segmentation update to address perf regression from horizontal fusion
4. scalar cpu tensor promotion to support inter-device operation between cpu scalar tensor and cuda tensor
Things reverted from local changes:
aten::gelu with approximation (tracked in PR: https://github.com/pytorch/pytorch/pull/61439)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72127
Reviewed By: HamidShojanazeri
Differential Revision: D34113233
Pulled By: jbschlosser
fbshipit-source-id: b82cde32b71e324eca0ea57cb8c9f9647278ca74
(cherry picked from commit e009bc5c4e)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72390
This class didn't add much value and only caused more boilerplate code.
This change removes the class and updates all the use cases with
uses of `ExprHandle`.
A side effect of this change is different names in loop variables, which
caused massive mechanical changes in our tests.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D34030296
Pulled By: ZolotukhinM
fbshipit-source-id: 2ba4e313506a43ab129a10d99e72b638b7d40108
(cherry picked from commit c2ec46a058)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66746
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
Test Plan: Sandcastle
Reviewed By: malfet
Differential Revision: D31705361
fbshipit-source-id: 33fd22eb03086d114e2c98e56703e8ec84460268
Summary:
nvfuser code update:
1. Tuning heuristics on schedulers for reduction/normalization kernels;
2. bfloat16 on IO tensor support;
3. Refactored memory format support, now we can support dimension collapsing with non-coherent input tensors with different memory format. e.g. channels last tensor input to batch normalization. Note that we are currently limiting memory format to only Contiguous and Channels last;
4. Refactored nvfuser graph partitioning in `graph_fuser.cpp`, separated node merge and profile node API. Updated `profiling_record.cpp`.
Things that are reverted from our local branch:
1. changes on some entries in autodiff
2. aten::gelu with approximation
3. native_dropout(_backward)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67943
Reviewed By: ngimel
Differential Revision: D32288709
Pulled By: dzhulgakov
fbshipit-source-id: fc9491182ea7e0158bc112c66f096823c588eaf1
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66234
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
bypass_size_limit
allow-large-files
Test Plan: Sandcastle
Reviewed By: ngimel
Differential Revision: D30652629
fbshipit-source-id: 0ae6c4bbbb554bad42e372792a6430e1acf15e3e
Summary:
Delete `-Wno-unused-variable` from top level `CMakeLists.txt`
Still suppress those warnings for tests and `torch_python`
Delete number of unused variables from caffe2 code
Use `(void)var;` to suppress unused variable in range loops
Use `C10_UNUSED` for global constructors and use `constexpr` instead of `static` for global constants
Do not delete `caffe2::OperatorBase::Output` calls as they have side effects
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66041
Reviewed By: ngimel
Differential Revision: D31360142
Pulled By: malfet
fbshipit-source-id: 6fdfb9f91efdc49ca984a2f2a17ee377d28210c8
Summary:
Delete `-Wno-unused-variable` from top level `CMakeLists.txt`
Still suppress those warnings for tests and `torch_python`
Delete number of unused variables from caffe2 code
Use `(void)var;` to suppress unused variable in range loops
Use `C10_UNUSED` for global constructors and use `constexpr` instead of `static` for global constants
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65954
Reviewed By: ngimel
Differential Revision: D31326599
Pulled By: malfet
fbshipit-source-id: 924155f1257a2ba1896c50512f615e45ca1f61f3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65551
Previously we had a big switch on Op kind to decide how to lower a given
JIT operator to NNC. This PR changes this switch to a hash table lookup.
Why? This helps us with at least two things:
1) With this approach we can easily check if we know how to handle a
given node in advance - i.e. we can inspect the entire graph and tell
whether it's possible to compile it or not without actually trying to do
that and dying in the middle. This would allow us to, say, provide
user-friendly error messages in AOT workflow.
2) We can switch to use schema instead of op kind to determine correct
lowering. Unlike op schema, op kind might be ambigous (see e.g. #64963)
and using it instead of schema can lead to bugs.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D31148926
Pulled By: ZolotukhinM
fbshipit-source-id: ac12684e2126c899426ef5e4cc1e3f70fa01f704
Summary:
Syncing nvfuser code base from devel branch, Listing a few of our development since last sync:
- Extends support to normalization and reduction kernels.
- Multiple kernel launch for single `CudaFusionGroup`. Hierarchical caching system has been updated to cache graph segmentation.
- profile_ivalue is enabled to convert dynamic scalar into compile time constants, which are required by the codegen. (e.g. reduction axes).
To keep this PR simple and relatively review-free. We stripped most external changes and submitted them as separate PRs, so this gigantic PR is easier to handle.
internal updates are files located in:
1. updates in nvfuser codegen `torch/csrc/jit/coddgen/cuda`
2. added nvfuser specific benchmarks `benchmarks/cpp/nvfuser`
3. nvfuser jit cpp tests `test/cpp/jit/test_gpu.cpp` `test/cpp/jit/test_gpu_shift.cpp` `test/cpp/jit/test_gpu_validator.h`
updates affecting integration:
1. profile_ivalue enabled for nvfuser. related changes are in `torch/csrc/jit/runtime/*`,
2. exposed a few more symbols `aten/src/ATen/core/*` used by codegen
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63745
Reviewed By: saketh-are
Differential Revision: D30752939
Pulled By: malfet
fbshipit-source-id: ce122e80f01bcd3865f5bd3c4dfde660665fd84c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64887
BufHandle has exactly the same functionality and should be used instead.
Differential Revision:
D30889483
D30889483
Test Plan: Imported from OSS
Reviewed By: navahgar
Pulled By: ZolotukhinM
fbshipit-source-id: 365fe8e396731b88920535a3de96bd3301aaa3f3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64205
The log_vml version of the micro-bench is over **2x** faster than the log1p version. Here are the perf numbers:
```
---------------------------------------------------------------------------------------------
Benchmark Time CPU Iterations UserCounters...
---------------------------------------------------------------------------------------------
SignedLog1pBench/ATen/10/1467 45915 ns 45908 ns 14506 GB/s=2.5564G/s
SignedLog1pBench/NNC/10/1467 40469 ns 40466 ns 17367 GB/s=2.9002G/s
SignedLog1pBench/NNCLogVml/10/1467 19560 ns 19559 ns 35902 GB/s=6.00016G/s
```
Thanks to bertmaher for pointing this out.
Test Plan: Imported from OSS
Reviewed By: bertmaher
Differential Revision: D30644716
Pulled By: navahgar
fbshipit-source-id: ba2b32c79d4265cd48a2886b0c62d0e89ff69c19
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63587
Now that there is no classes using KernelArena for memory management we
can remove it.
Differential Revision:
D30429115
D30429115
Test Plan: Imported from OSS
Reviewed By: navahgar
Pulled By: ZolotukhinM
fbshipit-source-id: 375f6f9294d27790645eeb7cb5a8e87047a57544
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63586
This is another commit in transition from KernelArena memory management.
Tensor is essentially just a pair of <BufPtr, StmtPtr> and we don't need
to dynamically allocate it at all - it's cheap to pass it by value, and
that's what we're switching to in this commit.
After this change nothing uses KernelScope/KernelArena and they can be
safely removed.
Differential Revision:
D30429114
D30429114
Test Plan: Imported from OSS
Reviewed By: navahgar
Pulled By: ZolotukhinM
fbshipit-source-id: f90b859cfe863692b7beffbe9bd0e4143df1e819
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63778
This is a preparation for a switch from raw pointers to shared pointers
as a memory model for TE expressions and statements.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D30487425
Pulled By: ZolotukhinM
fbshipit-source-id: 9cbe817b7d4e5fc2f150b29bb9b3bf578868f20c
