Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15316
This starts cleaning up the files in c10 according to the module structure we decided on.
Move to c10/util:
- Half.h, Half-inl.h, Half.cpp, bitcasts.h
Move to c10/core:
- Device.h, Device.cpp
- DeviceType.h, DeviceType.cpp
i-am-not-moving-c2-to-c10
Reviewed By: dzhulgakov
Differential Revision: D13498493
fbshipit-source-id: dfcf1c490474a12ab950c72ca686b8ad86428f63
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13689
Now that typeid.h lives in c10/util, the include paths should reflect that.
Reviewed By: ezyang
Differential Revision: D12912237
fbshipit-source-id: e54225f049f690de77cb6d5f417994b211a6e1fb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11587
To help debug the issue in T33295362, we add some checks in the function.
Possible crashing site in `GetTensorInfo`
1. tc is nullptr, which is checked.
2. tc->capacity_nbytes() hits nullptr, this is unlikely because storage is not a pointer and compute of capacity_nbytes doesn't involve pointers. It's numel * itermsize().
3. tc->ExtractDeviceOption hits nullpt. One possibility raw_data() is nullptr because tc->ExtractDeviceOption will use that. This is checked.
4. Tensor itself which is not a reference. This is also checked.
Reviewed By: salexspb
Differential Revision: D9793484
fbshipit-source-id: 3fc72746fc310a23ae45553bbe0d269a4b9edb72
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11254
Previously we use DeviceType in caffe2.proto directly, but it's an `enum` and have implicit conversion to int, which does not have type safety, e.g. we have to explicitly check for a device type is valid in event.h:
```
template <int d>
struct EventCreateFunctionRegisterer {
explicit EventCreateFunctionRegisterer(EventCreateFunction f) {
static_assert(d < MaxDeviceTypes, "");
Event::event_creator_[d] = f;
}
};
```
at::DeviceType is an `enum class`, and it does not have implicit conversion to int, and provides better type safety guarantees. In this diff we have done the following refactor(taking CPU as an example):
1. caffe2::DeviceType → caffe2::DeviceTypeProto
2. caffe2::CPU → caffe2::PROTO_CPU
3. caffe2::DeviceType = at::DeviceType
4. caffe2::CPU = at::DeviceType::CPU
codemod -d caffe2/caffe2 --extensions h,cc,cpp 'device_type\(\), ' 'device_type(), PROTO_'
+ some manual changes
In short, after this diff, in c++, caffe2::CPU refers to the at::DeviceType::CPU and the old proto caffe2::CPU will be caffe2::PROTO_CPU.
In python side, we have a temporary workaround that alias `caffe2_pb2.CPU = caffe2_pb2.PROOT_CPU` to make the change easier to review and this will be removed later.
Reviewed By: ezyang
Differential Revision: D9545704
fbshipit-source-id: 461a28a4ca74e616d3ee183a607078a717fd38a7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10804
Make ShareData and ShareExternalPointer to create new storage when the old one is used by multiple tensors.
When we need to modify the field of storage, we'll create a new storage instead.
Reviewed By: ezyang
Differential Revision: D9350686
fbshipit-source-id: 68d2b6b886b0367b0fc4fabfd55b9a480e7388ca
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10053
Tensor in Pytorch 1.0 will have
Tensor -> TensorImpl -> Storage -> StorageImpl
In this diff we split Storage from Tensor in order to align with this design.
We'll have Tensor -> Storage -> StorageImpl after this diff
Reviewed By: ezyang
Differential Revision: D9384781
fbshipit-source-id: 40ded2437715a3a2cc888ef28cbca9a25b1d5350
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10053
Tensor in Pytorch 1.0 will have
Tensor -> TensorImpl -> Storage -> StorageImpl
In this diff we split Storage from Tensor in order to align with this design.
We'll have Tensor -> Storage -> StorageImpl after this diff
Reviewed By: dzhulgakov
Differential Revision: D9076734
fbshipit-source-id: ea9e1094ecf8c6eaeaa642413c56c6a95fb3d14e
