Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67000
See the [related issue](https://github.com/pytorch/pytorch/issues/66654) for context.
This new JIT optimization transforms patterns like this:
```
%inputs.1 : Tensor[] = prim::ListConstruct(%a, %b, %c)
%concat.1 : Tensor = aten::cat(%inputs, %dim)
%inputs.2 : Tensor[] = prim::ListConstruct(%x, %concat.1, %y)
%concat.2 : Tensor = aten::cat(%inputs.2, %dim)
```
into this:
```
%inputs.2 : Tensor[] = prim::ListConstruct(%x, %a, %b, %c, %y)
%concat.2 : Tensor = aten::cat(%inputs.2, %dim)
```
(it can do this for chains of `aten::cat` longer than 2 as well)
A few conditions have to hold:
1. The `dim`s have to match.
2. `inputs.1` and `inputs.2` cannot be mutated
Test Plan: `buck test caffe2/test/cpp/jit:jit -- ConcatOpt`
Reviewed By: d1jang
Differential Revision: D31819491
fbshipit-source-id: 9f1a501d52099eb1a630b5dd906df4c38c3817ba
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63577
Since other variadic ops will have an almost identical implementation, we can generalize the `UseVariadicCat` implementation and put it in a common folder.
Also moved some test utilities that other variadic op tests will likely need.
Test Plan: `buck test caffe2/test/cpp/jit:jit -- ConcatOptTest`
Reviewed By: navahgar
Differential Revision: D30409937
fbshipit-source-id: 925c11c27b58ce98cb8368d2a205e26ba66d3db9
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61983
Trial #2. The previous PR (https://github.com/pytorch/pytorch/pull/61498) was reverted because this caused a failure in `pytorch_linux_backward_compatibility_check_test`. Fixed that now by adding to the exception list in `check_backward_compatibility.py`.
Test Plan: Imported from OSS
Reviewed By: eellison
Differential Revision: D29828830
Pulled By: navahgar
fbshipit-source-id: 947a7b1622ff6e3e575c051b8f34a789e105bcee
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59881
This pass is not included in the JIT flow or anywhere else at this point. The idea is, once this lands, everyone can use this to test their workflow with this transformation and once we are convinced this is useful and/or improves performance, we can include it in the appropriate workflow.
Test Plan: Imported from OSS
Reviewed By: mrshenli
Differential Revision: D29277876
Pulled By: navahgar
fbshipit-source-id: b5be7bdcc98dced59295bd7b8f6627619cb58d41
Summary:
This PR adds a new pass in JIT that optimizes `aten::cat` ops.
Specifically, here are optimizations performed:
* Eliminate redundant in `cat` inputs by performing cse on the list of inputs.
- This includes eliminating fully redundant `cat` ops when all the inputs are the same as well the case when "all but one" of the inputs have already been concatenated.
* Expand `cat` into multiple copies and eliminate redundancies.
- This also includes eliminating redundancies in the underlying buffers used for `cat`.
These optimizations are not enabled in any compilation flow at this point.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55474
Reviewed By: albanD
Differential Revision: D27624511
Pulled By: navahgar
fbshipit-source-id: d509289fafc23e73b02f64a90219148896817339
