Commit Graph

16 Commits (cfc1a6515c00badbf15bff8e3f2e796d3199b8e0)

Author SHA1 Message Date
Anup Gangwar 5d7a6c2976
[tosa] Support for Aten[Unsqueeze|Contiguous|Dropout|Reshape|View] ops (#700) 2022-03-25 14:15:07 -07:00
Sean Silva 84a9693006 Elide `!torch.` prefix in nested dialect types.
This leads to much more succinct types in many cases:

```
!torch.list<!torch.int>
!torch.list<int>

!torch.tuple<!torch.list<!torch.int>, !torch.list<!torch.int>>
!torch.tuple<list<int>, list<int>>

!torch.optional<!torch.list<!torch.int>>
!torch.optional<list<int>>

!torch.list<list<list<tensor>>>
!torch.list<!torch.list<!torch.list<!torch.tensor>>>
```

I would like to take this further and allow omitting the `!torch.`
prefix in all cases, but that's harder -- for example, we currently use
`FuncOp` for functions, and so I don't think we can customize the
printing there. It seems like it will be a longer road to getting that
level of customization.
2022-03-15 17:24:08 -07:00
Anup Gangwar c60468f141
[tosa] Support for Aten[Zeros|Ones|Fill_Scalar] ops (#604)
Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>

Co-authored-by: Anup Gangwar <anup.gangwar@arm.com>
2022-02-16 09:53:51 -08:00
Anup Gangwar 756b75fb2d
[tosa] Support for some ops and fix for Issue #532 (#575)
* [tosa] Support for AtenNe[Tensor|Scalar]Op, AtenLog2Op,
AtenBitwiseAndTensorOp, AtenSquareOp and AtenThresholdOp
* Fix for Issue #532 - Mixed input types for few ops and updated few
tests to use i32 instead of i64

Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>

Co-authored-by: Anup Gangwar <anup.gangwar@arm.com>
2022-02-11 12:30:02 -08:00
Anup Gangwar f9f97ea184 * [tosa] Support for AtenNativeLayerNormOp
* [tosa] Support for AtenPermuteOp

Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>
2022-02-04 14:46:31 -05:00
Anup Gangwar 454fa9d123
* [tosa] Support for AtenFlattenUsingIntsOp (#548) 2022-01-28 21:38:56 -08:00
Anup Gangwar 7a5736facd
* [tosa] Support for AtenReshapeOp (#543)
* [tosa] Support for AtenBatchNormOp

Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>

Co-authored-by: Anup Gangwar <anup.gangwar@arm.com>
2022-01-27 14:38:59 -08:00
Anup Gangwar f8080bd1c5
* [tosa] Support for AtenRsubScalarOp for scalar constants (#531)
* [tosa] Support for AtenCeilOp and AtenReciprocalOp
* [tosa] Support for comparator ops, Aten[Gt|Lt|Eq][Tensor|Scalar]Op with scalar constant
* [tosa] Support for Scalar variants of Aten[Mul|Div|Add|Sub] Ops with scalar constants

Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>

Co-authored-by: Anup Gangwar <anup.gangwar@arm.com>
2022-01-20 10:58:30 -08:00
Anup Gangwar d69d29b7a6 * [tosa] Support for AtenPowTensorScalarOp with constant Scalar as input
Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>
2022-01-11 22:55:54 -05:00
Anup Gangwar a6c3050dd0 * [tosa] Support for Maximum and Minimum
Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>
2021-12-15 11:58:19 -08:00
Anup Gangwar cce490d71d
* [tosa] Support for Rsqrt legalization (#480)
Signed-off-by: Anup Gangwar <anup.gangwar@arm.com>

Co-authored-by: Anup Gangwar <anup.gangwar@arm.com>
2021-12-14 10:03:58 -08:00
Suraj Sudhir c9c9b68d1f [tosa] Add Torch reduction operators
- Supports variants with multiple dims, one dim, all dime
- Leverages legalize_common and legalize_utils code from
TensorFlow-TOSA work

Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2021-12-03 09:01:48 -08:00
Suraj Sudhir 628a21bb13
[mlir][tosa] Refactor conversions to use templates (#416)
- Remove use of conversion construction macros
- Add mul and div op conversions
- Add corresponding tests

Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2021-11-11 16:15:58 -08:00
Suraj Sudhir 1019ddf5a0 [tosa] Add structure for eltwise ops
Add a bunch of op legalizations.

Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2021-11-11 11:03:24 -08:00
Suraj Sudhir 7e4ef74774
[tosa] Add Torch.sigmoid fp32 to TOSA (#386)
* [tosa] Add Torch.sigmoid fp32 to TOSA

Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2021-10-28 10:09:12 -07:00
Sean Silva 0c5c84d63d Add a basic TOSA E2E backend.
We lower through linalg-on-tensors and use RefBackend to run it.
This adds enough support for a "tanh" op. Adding more ops should be
fairly mechanical now that things are wired up. Run with:
```
./tools/torchscript_e2e_test.sh -c tosa
```

The backend structure is very similar to linalg-on-tensors based E2E
backends and is a nice parallel (see `tosa_backend.py`). Actually, this
forced a nice refactoring to the layering here. We removed
`torchscript-module-to-linalg-on-tensors-backend-pipeline` and instead
require separately running
```
torchscript-function-to-torch-backend-pipeline,torch-backend-to-linalg-on-tensors-backend-pipeline
```
This highlights the step that lowers to the "torch backend contract"
of cleaned up `torch` dialect ops is a critical step in the lowering.
Going forward, that is the key load-bearing contract of the torch-mlir
project, not the linalg-on-tensors backend contract.

Recommended review order:
- `TorchToTosa.cpp` / `TorchToTosa/basic.mlir`
- `python/torch_mlir_e2e_test/torchscript/configs/tosa_backend.py` and
  the new `utils.py` file there.
- `python/torch_mlir_e2e_test/tosa_backends/linalg_on_tensors.py` and
  `abc.py` in that directory for the TOSA backend e2e interface.
- other misc mechanical changes
2021-10-08 09:59:45 -07:00