Commit Graph

5 Commits (d35b6b412aa7252eb377967f4feb2a753ec1a7fb)

Author SHA1 Message Date
Stella Laurenzo 6961f0a247
Re-organize project structure to separate PyTorch dependencies from core project. (#2542)
This is a first step towards the structure we discussed here:
https://gist.github.com/stellaraccident/931b068aaf7fa56f34069426740ebf20

There are two primary goals:

1. Separate the core project (C++ dialects and conversions) from the
hard PyTorch dependencies. We move all such things into projects/pt1 as
a starting point since they are presently entangled with PT1-era APIs.
Additional work can be done to disentangle components from that
(specifically LTC is identified as likely ultimately living in a
`projects/ltc`).
2. Create space for native PyTorch2 Dynamo-based infra to be upstreamed
without needing to co-exist with the original TorchScript path.

Very little changes in this path with respect to build layering or
options. These can be updated in a followup without commingling
directory structure changes.

This also takes steps toward a couple of other layering enhancements:

* Removes the llvm-external-projects/torch-mlir-dialects sub-project,
collapsing it into the main tree.
* Audits and fixes up the core C++ build to account for issues found
while moving things. This is just an opportunistic pass through but
roughly ~halves the number of build actions for the project from the
high 4000's to the low 2000's.

It deviates from the discussed plan by having a `projects/` tree instead
of `compat/`. As I was thinking about it, this will better accommodate
the follow-on code movement.

Once things are roughly in place and the CI passing, followups will
focus on more in-situ fixes and cleanups.
2023-11-02 19:45:55 -07:00
Ashay Rane b0b2b3a199
build: add missing dependency on MLIRTorchTypesIncGen (#1405) 2022-09-23 08:08:16 -05:00
Sean Silva 4fad753073 Move external/torch-mlir to the root of the repo. 2021-09-27 17:11:08 -07:00
Sean Silva a99cbeeb7e Move TorchConversion dialect and TorchTo* into torch-mlir 2021-09-23 21:39:31 -07:00
Sean Silva cab8d922ec Add TorchToIREE and factor out TorchConversion dialect.
This converts a basic list op (torch.prim.ListConstruct) to the IREE
dialect.

```
    def forward(self, x: float):
            return [x, x]
```

turns into:

```
builtin.func @forward(%arg0: !torch.float) -> !torch.list<!torch.float> {
  %0 = torch.prim.ListConstruct %arg0, %arg0 : (!torch.float, !torch.float) -> !torch.list<!torch.float>
  return %0 : !torch.list<!torch.float>
}
```

which turns into:

```
builtin.func @forward(%arg0: f64) -> !iree.list<f64> {
  %c1 = constant 1 : index
  %c0 = constant 0 : index
  %c2 = constant 2 : index
  %0 = iree.list.create %c2 : !iree.list<f64>
  iree.list.set %0[%c0], %arg0 : !iree.list<f64>, f64
  iree.list.set %0[%c1], %arg0 : !iree.list<f64>, f64
  return %0 : !iree.list<f64>
}
```

As part of doing this, I realized that it was time to formalize the IR
form that we reach right before running TorchTo{Linalg,Std,...}. We now
call it the "Torch backend contract". We then lower the "Torch backend
contract" to the "npcomp backend contract", which involves the new
TorchConversion (`torch_c`) dialect, which holds ops that need to
operate on both the npcomp backend types (e.g. builtin tensors, i1, IREE
list, etc.) and the `!torch` types.

This made more sense, as I realized that if I didn't factor out
`torch_c` then the Torch dialect would have a dependency on IREE
dialect (we previously didn't notice this was an issue because we only
depended on `builtin` types), which seemed wrong to me.

Recommended review order:
- TorchToIREE.cpp / `TorchToIREE/basic.mlir`
- Look at the new structure of createTorchScriptToNpcompBackendPipeline.
  It now lives in TorchConversion/Transforms/Passes.cpp and cleanly
  calls into `Torch::createTorchScriptToTorchBackendPipeline` for the
  frontend lowering to the Torch backend contract.
- Mechanical change extracting
  `torch_c.{to,from}_{i1,i64,f64,builtin_tensor,iree_list}` into a new
  TorchConversion dialect, and a few passes specific to the lowering
  from the Torch backend contract to the npcomp backend contract.
- Minor fixes to TorchToLinalg.cpp to use unconverted operands (now that
  we convert lists as part of operand materialization, we need to use
  the original operands). Also added test for AtenMaxPool2dOp and fixed
  m_TorchConstantIntList.
- TmpDeleteDeadIREELists pass. Temporary pass for deleting dead IREE lists that
  are created as part of operand materialization for conv/max pool/avg pool ops
  in TorchToLinalg.
2021-08-16 15:01:58 -07:00