Summary:
This directory is opted-in to clang-format but is not format-clean. This blocks continuous formatting from being enabled on fbcode, and causes hassle for other codemods that leave inconsistent formatting. This diff runs clang-format, which is widely used and considered safe.
If you are unhappy with the formatting of a particular block, please *accept this diff* and then in a stacked commit undo the change and wrap that code in `// clang-format off` and `// clang-format on`, or `/* clang-format off */` and `/* clang-format on */`.
drop-conflicts
Test Plan: sandcastleit
Reviewed By: jerryzh168
Differential Revision: D22311706
fbshipit-source-id: 1ca59a82e96156a4a5dfad70ba3e64d44c5e762a
Summary:
And few typos
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34791
Test Plan: CI
Differential Revision: D20524879
Pulled By: malfet
fbshipit-source-id: 58fa03bd6356979e77cd1bffb6370d41a177c409
Summary:
Breaking out of #8338
This PR is a workaround for a bug with CUDA9.2 + GCC7.
Here is the error this PR fixed:
.../pytorch/caffe2/operators/elementwise_ops.h: In constructor ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>::BinaryElementwiseWithArgsOp(const caffe2::OperatorDef&, caffe2::Workspace*)’:
.../pytorch/caffe2/operators/elementwise_ops.h:106:189: error: ‘GetSingleArgument<bool>’ is not a member of ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>’
BinaryElementwiseWithArgsOp(const OperatorDef& operator_def, Workspace* ws)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10510
Reviewed By: orionr
Differential Revision: D9319742
Pulled By: mingzhe09088
fbshipit-source-id: ce59e3db14539f071f3c20301e77ca36a6fc3f81
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9939
Pull Request resolved: https://github.com/facebookresearch/weakly-supervised-action-detection/pull/13
Pull Request resolved: https://github.com/pytorch/translate/pull/166
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9125
Closes https://github.com/pytorch/pytorch/pull/9125
Use inheritance for polymorphism, and remove template parameter
This is to change the templating in call sites, the core implementations will change later
Before Caffe2 Tensor class was compile-time fixed to bind to a particular device/context. With this change, we're making it a runtime property (stored inside the tensor), but preserve the same semantics. For example, one has to specify device type in order to create a Tensor - there are no uninitialized tensors. More specifically the changes are:
1. We added an extra argument *DeviceType* to most of the constructors of the tensor, e.g. (Tensor(DeviceType type)),
2. Semantics of constructor Tensor(const Tensor<SrcContext>& src, ContextForCopy* context); is changed, in this constructor, the second context is passed in to enable us to call the templated Copy function, it could be in a different context as source and target previously, now we'll enforce that the context should have same device type as src, if it is provided.
3. To preserve 'get-or-construct' semantics of Blob, we added specialized getter Blob::GetMutableTensor that verifies both that Blob contains a Tensor and that it's of a correct type
4. Specifically, Tensor type is not default-constructible any more (as we don't have unknown device tensors) and thus some of the code handling STL containers needs to change
Note: Some changes are postponed just to keep this diff a bit smaller. Please see `TODO`s.
Reviewed By: ezyang, houseroad
Differential Revision: D9024330
fbshipit-source-id: e0b8295d2dc6ebe2963383ded5af799ad17164ba
Summary:
Pull Request resolved: https://github.com/facebookresearch/weakly-supervised-action-detection/pull/13
Pull Request resolved: https://github.com/pytorch/translate/pull/166
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9125
Closes https://github.com/pytorch/pytorch/pull/9125
Use inheritance for polymorphism, and remove template parameter
This is to change the templating in call sites, the core implementations will change later
Before Caffe2 Tensor class was compile-time fixed to bind to a particular device/context. With this change, we're making it a runtime property (stored inside the tensor), but preserve the same semantics. For example, one has to specify device type in order to create a Tensor - there are no uninitialized tensors. More specifically the changes are:
1. We added an extra argument *DeviceType* to most of the constructors of the tensor, e.g. (Tensor(DeviceType type)),
2. Semantics of constructor Tensor(const Tensor<SrcContext>& src, ContextForCopy* context); is changed, in this constructor, the second context is passed in to enable us to call the templated Copy function, it could be in a different context as source and target previously, now we'll enforce that the context should have same device type as src, if it is provided.
3. To preserve 'get-or-construct' semantics of Blob, we added specialized getter Blob::GetMutableTensor that verifies both that Blob contains a Tensor and that it's of a correct type
4. Specifically, Tensor type is not default-constructible any more (as we don't have unknown device tensors) and thus some of the code handling STL containers needs to change
Note: Some changes are postponed just to keep this diff a bit smaller. Please see `TODO`s.
Reviewed By: xw285cornell
Differential Revision: D8121878
fbshipit-source-id: 4a5e9a677ba4ac82095df959851a054c81eccf81
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9350
Re-apply #9270
Breaking this out of #8338
This takes care of the Eigen failure we saw on Mac CUDA builds when BUILD_CAFFE2 and BUILD_ATEN were removed. Fix is to isolate Eigen from headers included by cu files and processed by nvcc. This was worked on with smessmer.
Reviewed By: mingzhe09088
Differential Revision: D8794431
fbshipit-source-id: de656334af46c697802073f8e8d9a6aeb9ca65a7
* Update elementwise ops to support numpy style boradcast
Update elementwise ops to support numpy style boradcast
* Fix sqrt_op
* Fix compare ops
* Fix gradient test
* Fix optimizer legacy broadcast
* Fix legacy broadcast for elementwise ops
* Skip flaky test
* Fix eigen simple binary op
* Fix attention test
* Fix rnn test
* Fix LSTM test
* Fix tan grad
* Fix schema check
