Summary:
**Summary**
There is often a need to create a Tensor when writing IR by hand for JIT
optimisation pass unit tests. The only options for this today are real
Tensor creation functions like `aten::ones`. Any test that uses these functions
must also use the same default arguments as the Python/C++ API, which means
that all of the tests have to be updated when the API is updated. This commit
introduces a new primitive, `prim::MakeTestTensor` with schema `() -> Tensor` that
should be used in unit tests instead of real Tensor creation functions. This new
primitive has no public-facing API, so the maintenance burden is much lower.
**Testing**
This commit updates the alias analysis and DCE tests to use `prim::MakeTestTensor` instead of
`aten::rand`, `aten::ones`, and `aten::zeros`.
```
$ ./bin/test_jit
CUDA not available. Disabling CUDA and MultiCUDA tests
Note: Google Test filter = *-*_CUDA:*_MultiCUDA
[==========] Running 75 tests from 1 test case.
[----------] Global test environment set-up.
[----------] 75 tests from JitTest
[ RUN ] JitTest.ADFormulas
[ OK ] JitTest.ADFormulas (82 ms)
[ RUN ] JitTest.Attributes
[ OK ] JitTest.Attributes (0 ms)
...
...
...
[ RUN ] JitTest.LiteInterpreterPrim
[ OK ] JitTest.LiteInterpreterPrim (0 ms)
[ RUN ] JitTest.LiteInterpreterLoadOrigJit
[ OK ] JitTest.LiteInterpreterLoadOrigJit (2 ms)
[----------] 75 tests from JitTest (150 ms total)
[----------] Global test environment tear-down
[==========] 75 tests from 1 test case ran. (150 ms total)
[ PASSED ] 75 tests.
```
**Fixes**
This pull request fixes https://github.com/pytorch/pytorch/issues/33500.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33595
Differential Revision: D20127441
Pulled By: SplitInfinity
fbshipit-source-id: 56da4f23ac46335227254f606c6481718108f378
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32326
Now that we have type-level granularity we can improve `mayContainAlias` queries. Each new values is initialized as containing the wildcard set of each contained mutable type. Whenever a value is added to a container it is set to the wildcard set. Now, to check if any two values contain overlapping values, we can just check if the `containedMemoryLocations` of two sets overlap.
Test Plan: Imported from OSS
Differential Revision: D19563262
Pulled By: eellison
fbshipit-source-id: c6d7489749c14b2054a6d50ef75baca699ada471
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32251
Previously wildcard sets were associated by TypeKind, meaning all Lists were in one alias set, all Classes were in one alias set, etc. We can improve analysis by bucketing wildcard sets by TypePtr instead. Any two mutable types which can unify should be in the same wildcard set bucket.
This also allows us do much simpler `mayContainAlias` analysis, and also improves `analyzeConservative` analysis because now we can recurse through all contained memory locations and mark writes, instead of just recursing only level deep in contained elements.
Test Plan: Imported from OSS
Differential Revision: D19563263
Pulled By: eellison
fbshipit-source-id: 371a37d1a8596abc6c53f41c09840b6c140ea362
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31839
There are a number of improvements that can be made to `mayContainAlias`, which I would like to do in follow ups. For now, this is an easy one.
Test Plan: Imported from OSS
Differential Revision: D19439516
Pulled By: eellison
fbshipit-source-id: 0042fb7eaae6cfb4916bf95dc38280517a4bd987
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31501
We have a number of places in our code base where we should be checking if it's safe to change the alias relationship between two sets of values. This PR adds an api to Alias Db to consolidate the logic, and refactors Constant Pooling and `CSE` to use the new api. Next steps: add api usage in peephole.cpp where applicable.
Happy to bikeshed `AliasDb::safeToChangeAliasingRelationship`. Previously I suggested `AliasDb::safeToIntroduceAliasing`, however that's not quite accurate, because this API also handles when it is unsafe to remove aliasing.
Alternate suggestions: `safeToChangeAliasing`, `validToChangeAliasing`, `validToChangeAliasingRelationship`
Related: https://github.com/pytorch/pytorch/issues/28360
Test Plan: Imported from OSS
Differential Revision: D19254413
Pulled By: eellison
fbshipit-source-id: 17f7f52ad2d1526d303132767cbbb32f8189ae15
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26114
With this diff, the operator schema or name can be specified as part of the options objects:
```
static auto registry = torch::RegisterOperators()
.op(torch::RegisterOperators::options().schema("my_op").kernel(&kernel))
.op(...);
```
This does not break backwards compatibility, all old APIs are kept as shorthands.
This (a) makes the API more consistent, accumulating all options into the options objects and not treating schema special anymore, and (b) this is required for allowing the c10 dispatcher to forward registration calls to ATenDispatch for ops that are still on that dispatcher, see plan in https://github.com/pytorch/pytorch/issues/24132
ghstack-source-id: 90049402
Test Plan: unit tests
Differential Revision: D17350383
fbshipit-source-id: cbb8f33a52dccb2a4522753e7b5ac8ba35b908fd
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25425
1. Properly invalidate memory locations when we change the points-to
set.
2. Don't build a new indexToElementMap in toString(), just use
`MemoryDag::fromIndex`
3. Fix transitive wildcard assignment
Test Plan: Imported from OSS
Differential Revision: D17126402
Pulled By: suo
fbshipit-source-id: cbd99027d2e78fd333dbf030172d3b7ac4df8349
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25375
Either MSVC or the Windows headers have a PURE macro defined and will replace
any occurrences of the PURE token in code with an empty string. Replace
AliasAnalysisKind::PURE with AliasAnalysisKind::PURE_FUNCTION.
Note: this is bc breaking.
ghstack-source-id: 89202222
Test Plan: unit tests
Differential Revision: D17107743
fbshipit-source-id: 899a20651ba32d50691956b5424b351586c21cec
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/24801
This is to fix the ODR-violations in fbcode static builds, which have been broken for several months.
This PR is unfortunately quite large, but the changes are only mechanical:
1. Tests defined in header files -> tests defined in cpp files
2. Remove the `torch::jit::testing` namespace -> `torch::jit`.
3. Single `test.h` file that aggregates all tests.
4. Separate out files for gtest and python versions of the tests instead of using a build flag
5. Add a readme for how to add a new test, and explaining a bit about why the cpp tests are the way they are.
Test Plan: Imported from OSS
Differential Revision: D16878605
Pulled By: suo
fbshipit-source-id: 27b5c077dadd990a5f74e25d01731f9c1f491603
