Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23810
A previous diff removed the special casing for aten:: and prim:: ops in alias analysis and implements alias analysis purely
based on the AliasAnalysisKind. To be sure it doesn't break our existing code base, it added asserts that make sure that
our existing aten:: and prim:: ops set the correct AliasAnalysisKind.
However, we don't need that restriction for future ops. Since we are now certain all existing cases are set up correctly,
we can remove these assertions.
ghstack-source-id: 87733626
Differential Revision: D15996322
fbshipit-source-id: df27ed95397bbe58a76b6b2c2e9808fcfde35294
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22175
- Rename AliasAnalysisKind::DEFAULT to AliasAnalysisKind::CONSERVATIVE
- Introduce AliasAnalysisKind::FROM_SCHEMA that means the alias annotations of the schema should be honored
- Introduce AliasAnalysisKind::INTERNAL_SPECIAL_CASE to be able to run assertions that internal special cased ops are treated correctly
- aten:: and prim:: ops are not treated as special cases anymore, but just use AliasAnalysisKind::FROM_SCHEMA
- There's a set of assertions to ensure that aten:: and prim:: ops are all correctly set up to use AliasAnalysisKind::FROM_SCHEMA. Once this PR lands and passes all tests, we will remove those assertions and open up for the possibility of different AliasAnalysisKind settings for aten:: and prim:: ops
Differential Revision: D15929595
fbshipit-source-id: 7c6a9d4d29e13b8c9a856062cd6fb3f8a46a2e0d
Summary:
The error for `test_error_stack_module`:
```
Traceback (most recent call last):
File "../test.py", line 35, in <module>
scripted = torch.jit.script(M())
File "/home/davidriazati/other/pytorch/torch/jit/__init__.py", line 1119, in script
return _convert_to_script_module(obj)
File "/home/davidriazati/other/pytorch/torch/jit/__init__.py", line 1825, in _convert_to_script_module
raise e
RuntimeError:
d(int x) -> int:
Expected a value of type 'int' for argument 'x' but instead found type 'str'.
:
at ../test.py:11:12
def c(x):
return d("hello") + d(x)
~ <--- HERE
'c' is being compiled since it was called from 'b'
at ../test.py:14:12
def b(x):
return c(x)
~~~ <--- HERE
'b' is being compiled since it was called from 'forward'
at ../test.py:22:16
def forward(self, x):
return b(x)
~~~ <--- HERE
'forward' is being compiled since it was called from 'forward'
at ../test.py:31:20
def forward(self, x):
return x + self.submodule(x)
~~~~~~~~~~~~~~~~ <--- HERE
```
This also unifies our error reporting in the front end with `ErrorReport`
TODO
* Include module names in message, #22207 should make this easy
](https://our.intern.facebook.com/intern/diff/16060781/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22280
Pulled By: driazati
Differential Revision: D16060781
fbshipit-source-id: c42968b53aaddb774ac69d5abbf7e60c23df8eed
Summary:
Replaces https://github.com/pytorch/pytorch/pull/21501 because ghimport had errors when i tried to import the stack that i couldn't figure out :'(
has the two commits that were previously accepted and the merge commit
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22561
Differential Revision: D16135743
Pulled By: eellison
fbshipit-source-id: f0a98842ccb334c7ceab04d1437e09dc76be0eb1
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22084
For DictPtr/ListPtr, default construction was disallowed because it was ambigious if it's supposed to create an empty list or a nullptr.
But since we renamed them to Dict/List, we can now allow default construction without ambiguity.
Differential Revision: D15948098
fbshipit-source-id: 942a9235b51608d1870ee4a2f2f0a5d0d45ec6e6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21937
This changes call sites to use the new naming scheme
Reviewed By: zdevito
Differential Revision: D15892404
fbshipit-source-id: 8d32aa90a0ead1066688166478f299fde9c2c133
Summary:
This refactors pybind_utils so we can have all our type-inferring stuff in
1 place (e.g. for #21379)
There is some follow up work to make the error messages better, but I think that's fine to save for another PR.
](https://our.intern.facebook.com/intern/diff/15727002/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21550
Pulled By: driazati
Differential Revision: D15727002
fbshipit-source-id: a6974f2e1e5879f0503a18efc138da31cda7afa2
Summary:
Resolves https://github.com/pytorch/lockdown/issues/18
This implements NamedTuple by taking advantage of the existing `names` field in `TupleType`.
TODO: This currently doesn't retain the NamedTuple-ness through serialization. Discussed with suo offline, we can probably make a way to define an anonymous NamedTuple in script (e.g. `NamedTuple('Foo', [('a', int), ('b', float), ('c', List[float])])` and serialize that
TODO: implement support for calling the constructor with kwargs
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21428
Differential Revision: D15741564
Pulled By: jamesr66a
fbshipit-source-id: c077cbcea1880675ca6deb340a9ec78f824a136c
Summary:
This renames the CMake `caffe2` target to `torch`, as well as renaming `caffe2_gpu` to `torch_gpu` (and likewise for other gpu target variants). Many intermediate variables that don't manifest as artifacts of the build remain for now with the "caffe2" name; a complete purge of `caffe2` from CMake variable names is beyond the scope of this PR.
The shell `libtorch` library that had been introduced as a stopgap in https://github.com/pytorch/pytorch/issues/17783 is again flattened in this PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20774
Differential Revision: D15769965
Pulled By: kostmo
fbshipit-source-id: b86e8c410099f90be0468e30176207d3ad40c821
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21177
- Integrate c10::ListPtr into IValue and the c10 dispatcher.
- Streamline conversion to/from IValue. Before, we had IValue::to<> and kernel_functor.h had its own ivalue_to_arg_type and return_type_to_ivalue. They are now unified. Also, this means that nested types like Dicts of Lists of Optional of Dict of ... do work as expected now
Differential Revision: D15476433
fbshipit-source-id: bde9df80df20091aa8e6ae17ba7e90abd149b954
Summary:
This changes our compiler so it first emits Loads & Stores, and then transforms the graph to SSA in a follow up pass. When a variable is set, we emit a prim::Store, and when a variable is referenced, we emit a prim::Load.
```
a = 1
print(a)
```
becomes:
```
%a.1 : int = prim::Constant[value=1]()
prim::Store[name="a"](%a.1)
%a : int = prim::Load[name="a"]()
prim::Print(%a)
```
In the follow up pass, convertToSSA, the values are turned into SSA form with the Loads & Stores removed. This change will enable breaks and continues because you can transform the graph with the variable naming information still intact.
There are still some remaining jitter and edge cases issues that I have to look through, but I think is still ready for eview.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21101
Differential Revision: D15723353
Pulled By: eellison
fbshipit-source-id: 3269934d4bc24ddaf3a87fdd20620b0f954d83d0
Summary:
This makes file-line reporting also work for things loaded using `torch.jit.load()` as well as the string frontend (via `CompilationUnit`)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21217
Differential Revision: D15590838
Pulled By: jamesr66a
fbshipit-source-id: 6b6a12574bf9eca0b83f24f0b50535fda5863243
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21085
Now that torch::jit::RegisterOperators() always passes through to torch::RegisterOperators() (see diffs stacked below this), we can remove the old custom op implementation.
Reviewed By: dzhulgakov
Differential Revision: D15542261
fbshipit-source-id: ef437e6c71950e58fdd237d6abd035826753c2e4
