Commit Graph

6 Commits

Author SHA1 Message Date
Ansley Ussery
5072728d88 Fix stride printing/parsing formatting (#45156)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/45156

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D24078695

Pulled By: ansley

fbshipit-source-id: dab993277d43b31105c38d12098c37653747b42a
2020-10-06 15:06:46 -07:00
Michael Suo
22401b850b port all JIT tests to gtest (#45264)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45264

Context for why we are porting to gtest in: https://github.com/pytorch/pytorch/pull/45018.

This PR completes the process of porting and removes unused files/macros.

Test Plan: Imported from OSS

Reviewed By: ZolotukhinM

Differential Revision: D23901392

Pulled By: suo

fbshipit-source-id: 89526890e1a49462f3f77718f4ee273c5bc578ba
2020-09-25 11:37:43 -07:00
Michael Suo
42af2c7923 [jit] gtest-ify test_alias_analysis.cpp (#45018)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45018

Now that https://github.com/pytorch/pytorch/pull/44795 has landed, we
can convert the bulk of our cpp tests to use gtest APIs. Eventually
we'll want to get rid of our weird harness for cpp tests entirely in
favor of using regular gtest everywhere. This PR demonstrates some of
the benefits of this approach:
1. You don't need to register your test twice (once to define it, once
in tests.h).
2. Consequently, it's easier to have many individual test cases.
Failures can be reported independently (rather than having huge
functions to test entire modules.
3. Some nicer testing APIs, notably test fixtures.

Test Plan: Imported from OSS

Reviewed By: ZolotukhinM

Differential Revision: D23802297

Pulled By: suo

fbshipit-source-id: 774255da7716294ac573747dcd5e106e5fe3ac8f
2020-09-21 12:19:37 -07:00
Zino Benaissa
40c77f926c Add prim::TypeCheck operation (#43026)
Summary:
TypeCheck is a new operation to check the shape of tensors against
 expectd shapes. TypeCheck is a variadic operation. An example,

 %t0 : Tensor = ...
 %t1 : Tensor = ...
 %2 : FLOAT(20, 20), %3 : FLOAT(30, 30), %1 : bool =
 prim::TypeCheck(%t1, %t2)
 prim::If(%1)

Fixes #{issue number}

Pull Request resolved: https://github.com/pytorch/pytorch/pull/43026

Reviewed By: ZolotukhinM

Differential Revision: D23115830

Pulled By: bzinodev

fbshipit-source-id: fbf142126002173d2d865cf4b932dea3864466b4
2020-08-21 20:03:24 -07:00
Zachary DeVito
358450e02b improved TorchScript traceback (#33834)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33834

This changes how we report Tracebacks to make them more clear when
there are both serialized and non-serialized ranges. It now looks like:

```
Traceback (most recent call last):
  File "foo.py", line 25, in <module>
    s2(a, b)
  File "/scratch/zdevito/pytorch/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
RuntimeError: The following operation failed in the TorchScript interpreter.
Traceback of TorchScript, serialized code (most recent call last):
  File "code/__torch__.py", line 7, in forward
    x: Tensor,
    y: Tensor) -> Tensor:
    return (self).bar(x, y, )
            ~~~~~~~~~ <--- HERE
  def bar(self: __torch__.Moo,
    x: Tensor,
  File "code/__torch__.py", line 11, in bar
    x: Tensor,
    y: Tensor) -> Tensor:
    _0 = (self).baz(x, y, )
          ~~~~~~~~~ <--- HERE
    _1 = torch.ones([3], dtype=None, layout=None, device=None, pin_memory=None)
    return torch.add(_0, _1, alpha=1)
  File "code/__torch__.py", line 17, in baz
    x: Tensor,
    y: Tensor) -> Tensor:
    return torch.add(x, y, alpha=1)
           ~~~~~~~~~ <--- HERE

Traceback of TorchScript, original code (most recent call last):
  File "foo.py", line 11, in forward
    def forward(self, x, y):
        return self.bar(x, y)
               ~~~~~~~~ <--- HERE
  File "foo.py", line 9, in bar
    def bar(self, x, y):
        return self.baz(x, y) + torch.ones(3)
               ~~~~~~~~ <--- HERE
  File "foo.py", line 7, in baz
    def baz(self, x, y):
        return x + y
               ~~~~~ <--- HERE
RuntimeError: The size of tensor a (4) must match the size of tensor b (5) at non-singleton dimension 1
```

It follows Python convension of having the most important information last
and reading from the bottom up.

Changes:
* Moved the error message to the end, to copy Python
* Report original traceback separate from serialized traceback
* Make sure root functions have names in the interpreter trace.

Test Plan: Imported from OSS

Differential Revision: D20126136

Pulled By: zdevito

fbshipit-source-id: fd01f9985e5d74e04c4d064c02e8bc320f4fac13
2020-03-03 12:27:38 -08:00
Michael Suo
dfdb86a595 big cpp test reorg (#24801)
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
2019-08-18 16:49:56 -07:00