Commit Graph

6 Commits (28a0f02746f4a1315d8e17d9560f7ae1c255236c)

Author SHA1 Message Date
Sean Silva 939d36906f Add support for prim::Loop op.
This is a funny one. It combines a `for` and `while` loop in one op. We
will need to write some conversions to `scf`.
2021-03-02 16:01:34 -08:00
Sean Silva 158c5c484d Implement GlobalizeObjectGraph transformation.
This required restructuring of how we model TorchScript on import. The
main difference is that now we split out a `torch.class_type` that holds
methods and declarations of the types of each slot. This is more
consistent with TorchScript (our previous representation was
"denormalized").

Recommended reading order:
1. check out the description of `torch.class_type` in `TorchOps.td` and
   look at `test/Dialect/Torch/ops.mlir` and
   `frontends/pytorch/test/module_import/` to familiarize with the new
   representation.
   - Just look at the new IR. The diff between the old names and new
     names is confusing.
2. check out `test/Dialect/Torch/globalize-object-graph*.mlir`
   and read along with the pass description in
   `include/npcomp/Dialect/Torch/Transforms/Passes.td`
3. Read the code in `GlobalizeObjectGraph.cpp` and miscellaneous changes
   in `ivalue_importer.cpp`, `TorchOps.cpp`, etc.
2021-02-18 18:18:47 -08:00
Sean Silva 689b40c7a6 Add initial TorchScript module importer
It turns out that this was easiest to structure as a general IValue
importer, since torch module are just one of the possible IValue's.

We import the IValue object graph in a braindead fashion into basicpy
ops and a new `torch.nn_module` op that is used to model the
attributes/methods of a torch::jit::Module IValue. See `Torch/ops.mlir`
for an example, and also check out the .py import tests in
`frontends/pytorch/test/module_import`.

As part of this change, a few housekeeping tasks:
- extract some helpers from graph_importer.cpp
- more helpers around the C API
- misc touchups
2021-01-28 11:55:17 -08:00
Stella Laurenzo 510f226df2 Expose signature metadata to ops and implement ATenRecognizeKernelsPass pass.
* Two op interfaces, one for querying instance metadata and one for getting static data needed to construct an op from a generic form.
* For torch.generic_kernel ops, metadata is splatted in during capture from Torch (it comes from the op registry, which will work for either device capture or graph import).
* Moved the 'add' out of the generated set so I can experiment on it. It implements the TorchBuildableKernelOpInterface interface which provides its metadata.
* The ATenRecognizeKernelsPass pass generically lowers from a torch.generic_kernel to recognized ops that implement the TorchBuildableKernelOpInterface, handling the various types of transformations that we allow at this stage.
2020-10-26 20:31:45 -07:00
Stella Laurenzo 3d74337be0 Add a torch.kernel_call op and associated predicates. 2020-09-29 15:10:38 -07:00
Stella Laurenzo 2c9ca79c89 Add boilerplate for Torch dialect. 2020-09-28 15:26:17 -07:00