Summary:
This should have been fixed in newest ROCm version.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19436
Reviewed By: ezyang
Differential Revision: D15004685
Pulled By: bddppq
fbshipit-source-id: 19fd4cca94c914dc54aabfbb4e62b328aa348a35
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19273
Some of the CIs are failing if the protobuf is not installed. Protobuf is imported as part of the `caffe2.python.core`, and this adds a skip decorator to avoid running tests that depend on `caffe2.python.core`
Reviewed By: jianyuh
Differential Revision: D14936387
fbshipit-source-id: e508a1858727bbd52c951d3018e2328e14f126be
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18165
ghimport-source-id: 55cb3fb63a25c2faab1725b4ec14c688bf45bd38
Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18166 Bool Tensor for CUDA
* **#18165 Resolved comments from Bool Tensor for CPU PR**
-------
------------
This is a follow up PR that resolves some additional feedback on one the of previous Bool Tensor PRs.
gchanan, here is a list of almost all the comments from the original PR with respective fixes and replies:
**[utils/python_scalars.h]** why is this converting from uint8_t and not bool? (comment?)
When i was adding this, i was testing by creating a tensor and then calling its .tolist(). it worked for bool and uint8_t equally good so i left uint8_t as thought it makes more sense as we are calling PyBool_FromLong. �Changing it to bool.
**[ATen/Dispatch.h]**better name?.
fixed.
**[test/test_torch.py]** what about other factories, such as full? (and more).
There is a test that goes through the factory methods - test_tensor_factories_empty. i added some bool cases above it and added a comment that once CUDA will be done, i will unite them and it will iterate not just between CUDA and CPU but also all types. ��Adding all bool cases now. Will unite in CUDA PR.
**[generic/THTensorMath.h]** any changes in this file actually needed?
Bad merge. Fixed.
**[TH/THTensor.h]** this generates code for random, clampedRandom, and cappedRandom -- do we have tests for all of these with bool?
Added
**[c10/core/ScalarType.h]** I'm not very confident about the lack of Bool here -- can you look at the call sites and see what makes sense to do here?
Added bool to the macro and created a similar one without for a single case which fails the build with errors:
_./torch/csrc/jit/symbolic_variable.h:79:20: error: ambiguous overload for ‘operator*’ (operand types are ‘const torch::jit::SymbolicVariable’ and ‘torch::jit::Value*’)
return (*this) * insertConstant(rhs);_
Differential Revision: D14605105
fbshipit-source-id: abf82d50e8f8c50b386545ac068268651b28496d
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18231
ghimport-source-id: 78c230f60c41877fe91b89c8c979b160f36f856b
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18231 Add a decorator for marking slow tests.**
The general strategy:
- It's a normal skip decorator, which triggers a skip if
PYTORCH_TEST_WITH_SLOW is not set.
- It also annotates the method in question that says it's
slow. We use this to implement a catch-all skipper in
setUp that skips all non-slow tests when
PYTORCH_TEST_SKIP_FAST is set.
I added a little smoketest to test_torch and showed that I get:
```
Ran 432 tests in 0.017s
OK (skipped=431)
```
when running with PYTORCH_TEST_WITH_SLOW=1 and PYTORCH_TEST_SKIP_FAST=1
CI integration coming in later patch, as well as nontrivial uses of
this decorator.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision: D14544441
fbshipit-source-id: 54435ce4ec827193e019887178c09ebeae3ae2c9
Summary:
gchanan pointed out in https://github.com/pytorch/pytorch/pull/16389 that `allow_inf` is treating `-inf` and `inf` as equal. This fixes it.
Also fixing #16448 since it's near and 2.1 has released.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16959
Differential Revision: D14025297
Pulled By: gchanan
fbshipit-source-id: 95348309492e7ab65aa4d7aabb5a1800de66c5d6
Summary:
cdist is used for calculating distances between collections of observations.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16168
Differential Revision: D13739147
Pulled By: ifedan
fbshipit-source-id: 9419c2c166891ac7db40672c72f17848f0b446f9
Summary:
1) Reverts https://github.com/pytorch/pytorch/pull/12302 which added support for batched pdist. Except I kept the (non-batched) test improvements that came with that PR, because they are nice to have. Motivation: https://github.com/pytorch/pytorch/issues/15511
2) For the non-batched pdist, improved the existing kernel by forcing fp64 math and properly checking cuda launch errors
3) Added a 'large tensor' test that at least on my machine, fails on the batch pdist implementation.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15901
Reviewed By: ezyang
Differential Revision: D13616730
Pulled By: gchanan
fbshipit-source-id: 620d3f9b9acd492dc131bad9d2ff618d69fc2954
Summary:
Use case:
Some data loader tests rely on `psutil` (a third party lib). So they are guarded by `skipIf`. But we want to always test them on CI envs. With `IS_PYTORCH_CI`, we can raise if `psutil` is not found.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16006
Reviewed By: ezyang
Differential Revision: D13673957
Pulled By: yf225
fbshipit-source-id: c63a7138093f45333c0b371fed0bcc88b67f2a22
Summary:
Changes originally in this PR:
1. Move Variable::Impl data members into TensorImpl as `AutogradMeta` struct
2. Change Variable::Impl functions to use data members in `AutogradMeta` struct
3. Add `shallow_copy_and_detach()` function to each subclass of TensorImpl
4. Do shallow copy when the user calls `make_variable(tensor)` / `make_variable_view(tensor)` / `variable.set_data(tensor)` / `variable.detach()`
Changes moved from https://github.com/pytorch/pytorch/pull/13645:
1. Add a flag to Variable to disallow size/stride/storage_ptr changes from in-place operations such as `resize_` / `resize_as_` / `set_` / `transpose_`, and set this flag to true when people call `tensor.data` in Python.
2. Write text in the docs to actively discourage changing the shape or storage of `tensor_detached` and expecting `tensor` to also be updated.
This is the 1st+2nd PR mentioned in https://github.com/pytorch/pytorch/issues/13638.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13827
Differential Revision: D13507173
Pulled By: yf225
fbshipit-source-id: b177b08438d534a8197e34e1ad4a837e2db0ed6a
Summary:
This updates pdist to work for batched inputs, and updates the
documentation to reflect issues raised.
closes#9406
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12302
Reviewed By: ezyang
Differential Revision: D13528485
Pulled By: erikbrinkman
fbshipit-source-id: 63d93a6e1cc95b483fb58e9ff021758b341cd4de
Summary:
- This is a straightforward PR, building up on the batch inverse PR, except for one change:
- The GENERATE_LINALG_HELPER_n_ARGS macro has been removed, since it is not very general and the resulting code is actually not very copy-pasty.
Billing of changes:
- Add batching for `potrs`
- Add relevant tests
- Modify doc string
Minor changes:
- Remove `_gesv_single`, `_getri_single` from `aten_interned_strings.h`.
- Add test for CUDA `potrs` (2D Tensor op)
- Move the batched shape checking to `LinearAlgebraUtils.h`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13453
Reviewed By: soumith
Differential Revision: D12942039
Pulled By: zou3519
fbshipit-source-id: 1b8007f00218e61593fc415865b51c1dac0b6a35
Summary:
- fixes weights-contiguous requirement for THCUNN Convolutions
- Add tests that conv backward pass works for non-contiguous weights
- fix RNN tests / error messages to be consistent and pass
- relax weight grad precision for fp16 for a particular test
- fix regression of CMAKE_PREFIX_PATH not passing through
- add missing skipIfNoLapack annotations where needed
Differential Revision: D12918456
Pulled By: soumith
fbshipit-source-id: 8642d36bffcc6f2957800d6afa1e10bef2a91d05
Summary:
Fixes#13326
Also now you can use `run_test.py` with `pytest`. E.g.,
```
python run_test.py -vci distributed -pt
```
Yes it works with `distributed` and `cpp_extension`.
cc zou3519 vishwakftw
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13416
Differential Revision: D12895622
Pulled By: SsnL
fbshipit-source-id: 2d18106f3a118d642a666bfb1318f41c859c3df7
Summary:
1. Refactors `TestTorch` into `TestTorchMixin` (subclass of `object`) and `TestTorch` (subclass of `TestCase`, MRO `(TestCase, TestTorchMixin)`, only defined if `__name__ == '__main__'`). So other scripts won't accidentally run it.
2. Adds an assertion in `load_tests` that each script only runs cases defined in itself.
cc yf225 ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13250
Differential Revision: D12823734
Pulled By: SsnL
fbshipit-source-id: 7a169f35fe0794ce76e310d8a137d9a3265c012b
Summary:
expecttest and test_expecttest are the implementation and tests
for this functionality. I wired it up to the --accept flag,
but there's also a new environment variable EXPECTTEST_ACCEPT
which may be more convenient to trigger. Haven't tested if this
works in fbcode.
There may be a few expect tests which will benefit from inline
treatment, but I just did one to show it works.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12825
Reviewed By: teng-li
Differential Revision: D10448630
Pulled By: ezyang
fbshipit-source-id: 3d339f82e2d00891309620a60e13039fa1ed8b46
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12794
common.py is used in base_module for almost all tests in test/. The
name of this file is so common that can easily conflict with other dependencies
if they happen to have another common.py in the base module. Rename the file to
avoid conflict.
Reviewed By: orionr
Differential Revision: D10438204
fbshipit-source-id: 6a996c14980722330be0a9fd3a54c20af4b3d380
