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:
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/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/63195
This helps us to later switch from using KernelArena with raw pointers
to shared pointers without having to change all our source files at
once.
The changes are mechanical and should not affect any functionality.
With this PR, we're changing the following:
* `Add*` --> `AddPtr`
* `new Add(...)` --> `alloc<Add>(...)`
* `dynamic_cast<Add*>` --> `to<Add>`
* `static_cast<Add*>` --> `static_to<Add>`
Due to some complications with args forwarding, some places became more
verbose, e.g.:
* `new Block({})` --> `new Block(std::vector<ExprPtr>())`
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D30292779
Pulled By: ZolotukhinM
fbshipit-source-id: 150301c7d2df56b608b035827b6a9a87f5e2d9e9
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62336
This PR was generated by removing `const` for all types of nodes in NNC IR, and fixing compilation errors that were the result of this change.
This is the first step in making all NNC mutations in-place.
Test Plan: Imported from OSS
Reviewed By: iramazanli
Differential Revision: D30049829
Pulled By: navahgar
fbshipit-source-id: ed14e2d2ca0559ffc0b92ac371f405579c85dd63
Summary:
As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH`
All changes but the ones to `.clang-tidy` are generated using following script:
```
for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008
Reviewed By: driazati, r-barnes
Differential Revision: D29838584
Pulled By: malfet
fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os
def get_compiled_files_list():
import json
with open("build/compile_commands.json") as f:
data = json.load(f)
files = [os.path.relpath(node['file']) for node in data]
for idx, fname in enumerate(files):
if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
return files
def run_clang_tidy(fname):
check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
changes = check_output(["git", "ls-files", "-m"])
if len(changes) == 0:
return
check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])
def main():
git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
compiled_files = get_compiled_files_list()
for idx, fname in enumerate(git_files):
if fname not in compiled_files:
continue
if fname.startswith("caffe2/contrib/aten/"):
continue
print(f"[{idx}/{len(git_files)}] Processing {fname}")
run_clang_tidy(fname)
if __name__ == "__main__":
main()
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892
Reviewed By: H-Huang
Differential Revision: D27991944
Pulled By: malfet
fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55825
The mask has never been used (in vectorization we generate an explicit
`IfThenElse` construct when we need to mask out some elements). The PR
removes it and cleans up all its traces from tests.
Differential Revision: D27717776
Test Plan: Imported from OSS
Reviewed By: navahgar
Pulled By: ZolotukhinM
fbshipit-source-id: 41d1feeea4322da75b3999d661801c2a7f82b9db
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52901
This PR implements IR Verifier and adds a call to it in `LoopNest`
constructors. Checks that were in expr/stmt constructors before are now
moved to the corresponding `::make` functions or to the verifier. They
didn't really help from the constructors anyway since an exception
thrown from there led to a segfault due to the fact our memory
management works (object was not fully created but was registered in the
kernel arena for destruction anyway).
Fixes#52778.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D26682928
Pulled By: ZolotukhinM
fbshipit-source-id: c56524015cdffb1ed8bce4394509961a4071dcfa
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49697
Mostly mechanical move. This refactoring helps to hide unnecessary
details from the SimpleIREval interface and make it more similar to a
pure 'codegen'.
Test Plan: Imported from OSS
Reviewed By: nickgg
Differential Revision: D25668696
Pulled By: ZolotukhinM
fbshipit-source-id: 423247bfcdfa88403e8ec92152f00110bb9da19c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49357
This is a follow-up fix for PR #48679, where the previous PR
adds support for integer inputs to aten::abs by promoting integers to
float and then demote the result back to integers. This PR supports
integer inputs to aten::abs more efficiently in the SimpleIREvaluator
by allowing implementing integer inputs for kAbs (renamed from kFabs).
- Rename kFabs to kAbs
- Add support for integer input to kAbs in SimpleIREvalator (note that:
llvm_codegen and cuda_codegen already supports integer inputs to kAbs)
Test Plan:
- `PYTORCH_TENSOREXPR_DONT_USE_LLVM=1 python test/test_jit_fuser_te.py
TestTEFuser.test_unary_ops`
- `python test/test_jit_fuser_te.py TestTEFuser.test_unary_ops`
Imported from OSS
Reviewed By: eellison
Differential Revision: D25545791
fbshipit-source-id: e52f51a352d149f66ce8341fb3beb479be08a230
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48160
We no longer use the custom c++ test infra anyways, so move to pure
gtest.
Fixes#45703
ghstack-source-id: 116977283
Test Plan: `buck test //caffe2/test/cpp/tensorexpr`
Reviewed By: navahgar, nickgg
Differential Revision: D25046618
fbshipit-source-id: da34183d87465f410379048148c28e1623618553
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45520
With this change `Load`s and `Store`s no longer accept `Placeholder`s in
their constructor and `::make` functions and can only be built with
`Buf`.
`Placeholder` gets its own `store`, `load`, `storeWithMask`, and
`loadWithMask` method for more convenient construction.
Test Plan: Imported from OSS
Reviewed By: glaringlee
Differential Revision: D23998789
Pulled By: ZolotukhinM
fbshipit-source-id: 3fe018e00c1529a563553b2b215f403b34aea912
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45388
Classes defined in these files are closely related, so it is reasonable
to have them all in one file. The change is purely a code move.
Differential Revision: D23952867
Test Plan: Imported from OSS
Reviewed By: nickgg
Pulled By: ZolotukhinM
fbshipit-source-id: 12cfaa968bdfc4dff00509e34310a497c7b59155
Summary:
Arithmetic operations on Bool aren't fully supported in the evaluator. Moreover,
such semantics can be implemented by the client code through insertion of
explicit casts to widen and narrow to the desired types.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44677
Test Plan:
test_tensorexpr --gtest_filter=TensorExprTest.ExprDisallowBoolArithmetic
python test/test_jit_fuser_te.py
Reviewed By: agolynski
Differential Revision: D23801412
Pulled By: asuhan
fbshipit-source-id: fff5284e3a216655dbf5a9a64d1cb1efda271a36
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44861
We were redefining things like ASSERT_EQ to take a _VA_ARGS_ parameter, so compiling these files with gtest (instead of pytorch's custom python-based cpp test infra) fails.
Test Plan: buck build //caffe2/test/cpp/tensorexpr
Reviewed By: asuhan
Differential Revision: D23711293
fbshipit-source-id: 8af14fa7c1f1e8169d14bb64515771f7bc3089e5
Summary:
Awhile back when commonizing the Let and LetStmt nodes, I ended up removing both and adding a separate VarBinding section the Block. At the time I couldn't find a counter example, but I found it today: Local Vars and Allocations dependencies may go in either direction and so we need to support interleaving of those statements.
So, I've removed all the VarBinding logic and reimplemented Let statements. ZolotukhinM I think you get to say "I told you so". No new tests, existing tests should cover this.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42634
Reviewed By: mruberry
Differential Revision: D22969771
Pulled By: nickgg
fbshipit-source-id: a46c5193357902d0f59bf30ab103fe123b1503f1
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42494
Note that we're currently assuming that dtypes of all the arguments and
the return value is the same.
Test Plan: Imported from OSS
Reviewed By: nickgg
Differential Revision: D22910755
Pulled By: ZolotukhinM
fbshipit-source-id: 7f899692065428fbf2ad05d22b4ca39cab788ae5
Summary:
Implementation of the less popular proposal for eliminating overlap between LetStmt and Let: removing both and storing a mapping between Var and value Expr in the Block.
This complicates some tests but simplifies the IR by restricting where variable binding can occur.
I used the unit tests & python integration tests to verify this is correct but I'm unsure of coverage, particularly around the dependency checker in loopnest - ZolotukhinM your review would be useful there.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37606
Differential Revision: D21467483
Pulled By: nickgg
fbshipit-source-id: b402d3fce4cacf35d75f300f0a7dca32a43b6688
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/36611
Currently Buf represents underlying storage but it didn't have dtype.
That resulted in specifying dtypes in different places and there was no
mechanism to enforce its consistency: e.g. one could've created a kFloat
expression and use a kInt buffer to store its result. Now we're
centralizing where the logic regarding the storage is located and we can
start enforcing semantics rules.
Follow-ups: we can merge Buffer and BufHandle classes as the former is
now a mere wrapper over the latter.
Test Plan: Imported from OSS
Differential Revision: D21027356
Pulled By: ZolotukhinM
fbshipit-source-id: c06aa2c4077fdcde3bb4ca622d324aece79b5a9c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35800
This PR includes the following changes:
* Introduce a new `Expr` type `Buf`: it plays a similar to `Var` role, but also has dimensions.
* Use the new `Buf` class in `Store` and `Load` instead of `Var` for specifying where to store to or load from. `Buf` contains the dimensions info of the buffer we're loading/storing to and hence we are able to keep N-d indexes without flattening them into a 1-d index ([x,y] vs [x+y*W]).
* Flattening of the indexes is now a separate pass that is executed in `LoopNest::prepareForCodegen` - backends still expect indexes to be flattened, and this PR preserves that.
* `Tensor` now contains a `Buf` instead of `Var`, and thus Tensor now has the dimensions info (previously it was a property of a `Function`, not a `Tensor`). This brings us closer to Tensor being a combination of Buffer + Function, where Buffer specifies iteration domain and the Function defines a computation.
TODOs:
* Consider merging `Buffer` with `Buf` or `BufHandle`. It seems that we don't need all of them.
* Harden the logic of how we create buffers in fuser pass. Currently it seems that sometimes we don't set dimensions.
* Use `Buf` in `Allocate` and `Free`.
* Make it clearer that `Function` doesn't "own" dimensions info and that dimensions are a property of a Tensor, not a Function.
Differential Revision: D20789005
Test Plan: Imported from OSS
Reviewed By: zheng-xq
Pulled By: ZolotukhinM
fbshipit-source-id: e04188d1d297f195f1c46669c614557d6bb6cde4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34842
This PR (hopefully the last one of such kind) is merging changes from a
side branch where tensor expessions based fuser work has been done so
far. This PR is is a squashed version of changes in the side branch,
which is available here: https://github.com/bertmaher/pytorch
Differential Revision: D20478208
Test Plan: Imported from OSS
Pulled By: ZolotukhinM
fbshipit-source-id: 21556e009f1fd88099944732edba72ac40e9b9c0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34224
Our development has been happening on a side branch `pytorch_fusion` in
`bertmaher/pytorch` fork. This PR moves changes to the core classes
representing expressions and transformations on them.
At this moment, the tensor expressions are only used in tests.
Subsequent PRs add LLVM and CUDA codegen for tensor expressions and
implement fuser on top of these.
This PR is huge as it is a squashed version of changes in the side
branch. It is not practical to pull changes one by one from the branch,
so here is the squashed version. If you're interested in seeing the
history of changes, please refer to https://github.com/bertmaher/pytorch
Differential Revision: D20251835
Test Plan: Imported from OSS
Pulled By: ZolotukhinM
fbshipit-source-id: 1a871acc09cf3c6f7fb4af40d408cdbb82dc7dab
