Summary: The controller you requested could not be found. Original commit changeset: 2ea17724e223
Differential Revision:
D10026321
Ninja: stable broken
fbshipit-source-id: faf87cb7cc0f78c2c10d4aa6fceea279cd27acd6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11923
This is pre-work to allow moving Blob to ATen/core, which cannot depend on caffe2 anymore.
(1) Removing the Blob -> Tensor dependency allows us to move Blob to ATen/core and use it inside IValue without having to wait for the Tensor merge to be complete.
(2) In the final Blob design, we want it to be a very small class that doesn't have any special treatment for Tensor (or to be more correct, doesn't allow storing Tensor anymore), so this is anyhow the direction we want to go.
This changes call sites that will have to be moved to IValue later, but they cannot be moved to IValue directly, because for that, IValue first needs to be able to store Blob, which in turn first needs this diff and some other changes coming up in future diffs.
Codemods:
$ codemod --extensions h,hpp,c,cpp,cc "([a-zA-Z0-9_]+)\\.IsTensorType\\(" "BlobIsTensorType(\\1, "
$ codemod --extensions h,hpp,c,cpp,cc "([a-zA-Z0-9_]+)->IsTensorType\\(" "BlobIsTensorType(*\\1, "
$ codemod --extensions h,hpp,c,cpp,cc "([a-zA-Z0-9_]+)\\.GetMutableTensor\\(" "BlobGetMutableTensor(\\1, "
$ codemod --extensions h,hpp,c,cpp,cc "([a-zA-Z0-9_]+)->GetMutableTensor\\(" "BlobGetMutableTensor(*\\1, "
It is, however, not only these codemods because regex based refactoring was only able to match a small amount of the call sites. To catch more, I wouldn've needed a AST aware tool like clangr, which I didn't figure out how to use.
Reviewed By: ezyang
Differential Revision: D9979976
fbshipit-source-id: 2ea17724e223b5b73b44f99362727759ca689e61
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11817
Blob::Serialize() and Blob::Deserialize() are now free functions SerializeBlob(), DeserializeBlob() instead.
This takes away access to Blob internals from them and makes future refactorings easier.
Reviewed By: ezyang
Differential Revision: D9882726
fbshipit-source-id: 3251ebd4b53fc12f5e6924a6e4a8db3846ab3729
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11875
Seems like the refactor to predictor_config dropped some functionality that is now blocking other teams
rFBS2b30208263c14ce7039f27c618a3b232bf11ee33 is the change that was missed
hoping to land this quickly :)
Reviewed By: jonmorton
Differential Revision: D9948324
fbshipit-source-id: 1628f7c51c06319fa7ca5dc9d59799135bb82c5f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11779
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11731
This Predictor provides threadsafe interface and also
cleans-up activations after each run. So in multi-model setup
activation space doesn't explode
Reviewed By: highker
Differential Revision: D9842374
fbshipit-source-id: bfe253ae5fc813e73a347c5147ff6b58d50781ea
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11167
Narrow the Blob API as preparation for merging Blob/IValue
- get rid of templated IsType and Operator::InputIsType / OutputIsType
- Use 'using' instead of 'typedef' for DestroyCall (just for readability)
Reviewed By: ezyang
Differential Revision: D9623916
fbshipit-source-id: 952f0b0cf5a525094b02e8d2798dd57a56a9e1d8
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11052
Delete the test case for Predictor with constructing by MetaNetDef since the constructor
actually has been deprecated. The broken PR is for construcing predictor from DB instance.
Reviewed By: highker
Differential Revision: D9566935
fbshipit-source-id: 5511883953a2d3f6eb0a4f1c5518a1bc4b3ffbdc
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10920
Update the black box predictor and the related code to use the
constructor with PredictorConfig.
Reviewed By: highker
Differential Revision: D9516972
fbshipit-source-id: fbd7ece934d527e17dc6bcc740b4e67e778afa1d
Summary: Update all the caller for the new interface
Reviewed By: highker
Differential Revision: D9323167
fbshipit-source-id: a39335ceb402db0719f5f2314085ba9a81380308
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10835
The last diff of constructor cause performance regression in cold run.
This one tried to fix this.
Reviewed By: highker
Differential Revision: D9489617
fbshipit-source-id: a77c2e2c903a73e2ad9806b4f9c209cdb751442f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9483
The interface is updated to accept the config to construct the predictor.
Reviewed By: highker
Differential Revision: D8872999
fbshipit-source-id: 3ca54d644970823fc33c0ade9a005e12f52e2b24
Summary:
Properly annotated all apis for cpu front. Checked with cmake using
cmake -DUSE_ATEN=ON -DUSE_CUDA=OFF -DBUILD_ATEN=ON
and resulting libcaffe2.so has about 11k symbols.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10504
Reviewed By: ezyang
Differential Revision: D9316491
Pulled By: Yangqing
fbshipit-source-id: 215659abf350af7032e9a4b0f28a856babab2454
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
