Commit Graph

89 Commits (main)

Author SHA1 Message Date
Yevhenii Havrylko 64b0d4aed3
Add missing dependency to TorchMLIRRefBackend target (#3107)
Discovered in https://github.com/llvm/torch-mlir/issues/3104
Most likely when building with stablehlo, while waiting for it missing
dependency was generated to location shared with another dependency.
2024-08-14 23:41:51 +08:00
Rob Suderman afca88a058
[NFC] Change to *cast instead of .*cast variants (#3405)
Member casts have been deprecated. Changing over a bunch of the member
cast calls to the global templated variants to remove deprecation
warnings.
2024-05-30 23:45:13 -07:00
penguin_wwy 6679728c56
Fix deprecated uses of cast/dyn_cast/dyn_cast_or_null/isa (#3243)
Like #3130, gradually replace the deprecated code

https://github.com/llvm/mlir-www/blob/main/website/content/deprecation/_index.md#deprecated
2024-04-27 14:00:56 -07:00
penguin_wwy d4a30b7e67
Fix deprecated uses of cast/dyn_cast/dyn_cast_or_null/isa (#3130)
We should prefer functional style as the method style is deprecated
https://github.com/llvm/mlir-www/blob/main/website/content/deprecation/_index.md#deprecated
(https://mlir.llvm.org/deprecation/)
2024-04-11 06:47:35 -07:00
Quinn Dawkins 030b0140d4
[TorchToLinalg] Lower aten.cat to tensor.concat (#2650)
This replaces the lowering of aten.cat with tensor.concat, allowing more
efficient handling of concatenations in downstream flows. The refbackend
populates concat decomposition patterns that can be used to recover the
previous lowering.
2023-12-15 15:45:32 -05:00
Chi_Liu 14a4da923b
Update llvm-project to b44b3494f60296db6aca38a14cab061d9b747a0a (#2511)
The main purpose is to bring in the new mesh dialect change.
https://github.com/llvm/llvm-project/pull/68007
2023-10-16 19:29:48 -07:00
Ramiro Leal-Cavazos ab694dfbc1 Add complex dtype support on refbackend 2023-05-11 21:29:07 +05:30
Ramiro Leal-Cavazos 6c86bec04f
build: update llvm tag to 9acc2f37 (#1828)
This commit makes the following changes:

- Update dialects to use fold API `kEmitFoldAdaptorFolder` and update
signature of `fold` methods (see PSA
https://discourse.llvm.org/t/psa-new-improved-fold-method-signature-has-landed-please-update-your-downstream-projects/67618)
- Replace `makeArrayRef` with `ArrayRef` (see
https://reviews.llvm.org/D140896)
- Remove `TypeRange{}` arg from `b.create<scf::IfOp>` since builder no
longer takes that argument
- Make `func`s in `Torch/invalid.mlir` private, since symbol
declarations cannot be public. (see https://discourse.llvm.org/t/rfc-symbol-definition-declaration-x-visibility-checks/2140)
2023-01-25 01:29:42 +00:00
Prashant Kumar 564403e3a1 Add float16 support in the refbackend.
This will require https://reviews.llvm.org/D139121 patch to go through.
2022-12-15 21:19:52 +05:30
Ashay Rane f63bb9f86c
build: update llvm tag to 3a020527 (#1717)
Summary of changes:

 - Replace `llvm::None` with `std::nullopt`, since the former is deprecated
   (https://reviews.llvm.org/D139763)

 - Use setter for symbol visibility instead of passing string attribute when
   creating FuncOp
2022-12-14 02:06:39 -06:00
Vivek Khandelwal f416953600 [MLIR][TORCH] Add TorchConversionToMLProgram and MLProgramBufferize pass
This commit changes the `InsertRngGlobalsPass` to `TorchConversionToMLProgram`
pass. This commit also adds the `MLProgramBufferize` pass for the
bufferization of ml_program dialect ops to run on refbackend.

Signed-Off By: Vivek Khandelwal<vivek@nod-labs.com>
2022-12-02 13:20:46 +05:30
Ramiro Leal-Cavazos 0983a7f93a
Fix modulus calculation in LCG algorithm of refbackend (#1658)
The current implementation sets the `nextSeed` value to `temp & 127`,
which is wrong. The last step of the LCG algorithm for the multiplier
and increment chosen should be `temp % 2^{64} = temp & (1 <<
63)`. However, because we are dealing with i64 values, the modulus
operation happens automatically, so it is not needed.

See Donald Knuth's values for LCG here:
https://en.wikipedia.org/wiki/Linear_congruential_generator
2022-11-30 08:46:52 -08:00
Sean Silva 39de4d6265 [cleanup] Make diagnostics better
Also remove some unused imports.
2022-11-17 02:09:54 -08:00
Gaurav Shukla 0d209998d1
llvm: update tag to e864ac6945 (#1600)
Summary of changes:
1. Replace `string` iterator types by `IteratorType` enum.
(e6598b053d)
2. Update `includes` wrt new directory layout of MLIR HLO codebase.
(9fd8d251a8)
3. Update tags
   llvm: e864ac694540342d5e59f59c525c5082f2594fb8
   MHLO: eab364ba2a66bd0613efb94f8a738c1c97aaee92

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>

Signed-off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-11-16 14:40:36 -08:00
Ashay Rane faa9a78e38
build: update llvm tag to 6f46ff37 (#1448)
Summary of changes:
 - Updated references to the Arith dialect
   (https://reviews.llvm.org/D134762)
 - Switched to prefixed accessors for MemRef dialect
   (https://reviews.llvm.org/D134995)
 - Fixed warnings about signed/unsigned comparisons, ignored return
   values, and unused variables
2022-10-05 08:28:06 -05:00
AmosLewis 940959589b [MLIR][TORCH] Add Byte and Char Dtype support 2022-09-30 13:19:31 +05:30
Ashay Rane b0b2b3a199
build: add missing dependency on MLIRTorchTypesIncGen (#1405) 2022-09-23 08:08:16 -05:00
Ashay Rane 9208bf0eb6
llvm: bump tag to e1318078 (#781)
The updated LLVM code includes a patch to create bfloat16 array
attributes, thus enabling a different patch to torch-mlir to flesh out
support for the bfloat16 type.
2022-04-26 12:27:51 -07:00
Prashant Kumar 33c9d256ea [REFBACKEND] Add support for returning multiple different return types.
Added the dynamic registration of return function to the execution
engine. This makes sure that  different/multiple return types are supported.
Also, updated the .style.yapf indentation to 4.
2022-04-21 09:02:30 +05:30
Vigilans 63fb1e5aad Bump LLVM at 8361c5da30588d3d4a48eae648f53be1feb5cfad 2022-03-18 13:16:14 -04:00
Nirvedh f8cb32faf0 LLVM bump
Major changes: opTrait changed to Trait, selectOp moved to arith dialect
assertOp moved to cf dialect
2022-02-16 15:28:13 -05:00
Gaurav Shukla f00d1686c8 [LINALG] Add E2E support for `aten.[Bool.Tensor|Float.Tensor]` op
- This commit adds lowering of `aten.Bool.Tensor` and
  `aten.Float.Tensor` op as a part of `convert-torch-to-linalg` pass.
- It also adds support for returning bool types.
- It also fixes lowering of the `aten.Int.Tensor` op for non-zero rank
  input tensors.
- If a scalar number is converted to a 0-d tensor and passed on to the
  `aten.Float.Tensor` op, it folds to the scalar number.

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
2022-02-14 23:09:20 +05:30
Yi Zhang 0cb216a1ad [Torch][Linalg] Add basic support for RNG
This PR include the following pieces:
- Add torch `Generator` type. `Generator` type is converted to i64 in
refbackend type converter.
- Add seed managment support for the default global generator.
`torch_c.getNextSeed` op is used to get the seed. On refbackend, the
`torch_c.getNextSeed` is lowered to load/store from [0] of global
variable `default_generator` memref<i64> in `InsertRngGlobals` pass.
- Add `aten.uniform_` and testing as an example op for RNG ops. Add
`torch.pseudo.aten.uniform` op. It has the same operands and return as
the `aten.uniform_` from the op registry except for value semantics.
2022-01-31 18:56:42 -05:00
Vivek Khandelwal 35cf8d18f7 Add support for two return values
This commit adds support for two return values of type
memref f32 and i64.

Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com>
2022-01-11 11:07:10 +05:30
Prashant Kumar c598e01529 Add support for passing & returning memref of bool types
Support for passing memref of bool types as a function argument
and return is added in ref-backend.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-12-09 00:23:38 +05:30
Yi Zhang 0fe70994e5 Add support for multiple return values
This change is to unblock the work of some backprop ops returning more
than one tensors. We will need to think of a more scalable approach
in the future if more flexible return types combinations are needed.
2021-11-16 21:07:45 -05:00
Yi Zhang 53733933a4 Update llvm upstream to 0b17336f793108a7b10c3fa913039144ef1d0f61
Update AsmPrinter/Parser and MatchAndRewrite
2021-11-16 13:04:51 -05:00
Yi Zhang 05c4dd8e39 Add convertScalarToDtype helper.
This is to facilitate scalar type conversion in the TorchToLinalg. As
part of adding the helper, this PR also:
- Updated `AtenAddTensorOp`, `AtenSubTensorOp` to use the helpers to
support more type variants.
- Added e2e type promotion testing.
- Added i32 memref return/arg type to support e2e testing.
2021-11-08 17:50:52 -05:00
Prashant Kumar fd505db2c6 Adding support for returning elemental types.
Support for returning elemental types. Previously, only
memref types as returning types was supported. All the hacky ways
to write tests which return elemental types should be taken care of.

Signed-off-by: Prashant Kumar <prashant@nod-labs.com>
2021-11-08 22:20:48 +05:30
Boian Petkantchin e276dbbaa6
Add aten::gelu lowering (#374)
* Print more exception info on error during test execution

* Fix formatting

* Add aten::gelu lowering

Co-authored-by: Boian Petkantchin <boian@nod-labs.com>
2021-10-25 16:16:01 -07:00
Yi Zhang a459e09ab7 E2e support for aten.softmax.int and aten.embedding
- Added a DecomposeComplexOps pass to decompose complex torchOps.
- Refactored `visitAtenArgmaxOp` and `visitAtenAnyDimOp` to
`visitReductionAlongDimIntOp`.
- Moved some helper functions into
torch-mlir/Dialect/Torch/Utils/Utils.h to be shared by multiple files.
- Added support for f64 tensor as argument and return types.
2021-10-18 17:57:45 -04:00
Yi Zhang 0902438882 Update llvm-project to a54f4eae0e1d0ef5adccdcf9f6c2b518dc1101aa
This brings in https://reviews.llvm.org/D110797. PRs that are in
progress will need to use scripts provided by
https://llvm.discourse.group/t/psa-removed-arithmetic-ops-from-standard/4455.
2021-10-18 13:36:42 -04:00
dan 2e1498ad11 add i64 support to refbackend 2021-10-05 15:12:44 -04:00
Sean Silva 5b6902e31c Dual license the torch-mlir project.
This commit (with approval from all contributors) dual licenses
the torch-mlir project under both the standard LLVM license and the
standard PyTorch license. This will facilitate moving code between
torch-mlir and the two upstream projects.

The standard file comment is now:

```
// This file is licensed under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// Also available under a BSD-style license. See LICENSE.
```

See `LICENSE` in the project root for the terms of both licenses.
2021-10-01 10:46:08 -07:00
Sean Silva 4fad753073 Move external/torch-mlir to the root of the repo. 2021-09-27 17:11:08 -07:00
Sean Silva a25163fbfa Remove old RefBackend
It is superceded by the new one.
2021-09-22 15:33:28 -07:00
Sean Silva a7252f9a06 Add basic support for lists.
This plumbs through a vertical slice of support for lists.

The main chunk of new code here is AnnotateABIPass which captures the
program signature at the Torch backend contract layer, right before we
start `TorchConversion`. The `TorchConversion` lowering process is lossy
w.r.t. types, so it's necessary to do this for all targets in general.
Like using `!iree.list` directly, we use IREE's ABI annotation
representation for this, although there is nothing very IREE-specific
about it (see
https://github.com/google/iree/blob/main/docs/developers/design_docs/function_abi.md)

We change `ListLiteralModule_basic` to use `!torch.int` because IREE
doesn't support f64 yet (and we don't yet have a way for users to say
that they want `!torch.float` to lower as f32).

Recommended review order:
- AnnotateABIPass and tests
- Arg marshaling in npcomp_backend.py and `iree.py`
- Updates to `list_programs.py` / `xfail_sets.py`
- Moving DeleteDeadIREEListsPass to Backend/Common, so that backends
  that don't support lists can use it. RefBackend uses that pass, for
  example.
2021-09-09 20:48:55 -07:00
Sean Silva 1dec561cfd Update llvm-project to 830c0b9023cd0cf91955900e0d96283e7a8c3711
- builder.getSymbolRefAttr is gone.
- OpAsmOpInterface's getAsmResultNames method needs explicit override
- a bunch of churn for builtin.func needing to be made explicit (and
  sometimes implicit?)
- operation printers no longer need to print the operation name
  themselves.
- snuck in beneficial trivial addition to TmpDeleteDeadIREEListsPass to
  test a particular upstream change e2e with my local patchset.
2021-09-03 14:16:38 -07:00
Sean Silva 29e1b2fe89 Delete RestrictedCanonicalizer
It doesn't work properly with the new dialect registration framework.
This was latent and only was exposed when running through npcomp-opt.
Not worth investing the brainpower to fix now.
2021-08-27 19:09:29 +00:00
Stella Laurenzo 80ff744c56 Add a few missing deps exposed by stricter linking with BFD. 2021-08-22 11:56:48 -07:00
Sean Silva f168cacd6d Remove TCF and TCP.
These were legacy concepts that are now superceded by direct Torch to
linalg-on-tensors lowering. These were based on some very early thinking
related to the layering of frontends vs codegen, which is now obsolete
because:
- We expected a lot more centralization at the frontend (TCF) level. It
  turns out that frontend needs really vary a lot, and there is no grand
  unifying TCF dialect plausible. The additional layer isn't worth it.
- Linalg-on-tensors obsoletes the primary need for TCP. There are still
  a few things not representable with linalg-on-tensors, but the support
  is growing and the whole "not included in linalg-on-tensors" direction
  needs to be rethought. Our TCP dialect didn't cover any of the
  actually important things in this space (such as sort, FFT, top-k,
  etc.).

See historical [slides](https://drive.google.com/file/d/1iljcpTQ5NPaMfGpoPDFml1XkYxjK_6A4/view) / [recording](https://drive.google.com/file/d/1jSPa8TwPKUt0WuLquGc8OgSUVYJHMvWZ/view)
for more details on the origin story here.

Their presence was confusing users too
[bug](https://github.com/llvm/mlir-npcomp/issues/248).

Also,
- Trim down npcomp-run-mlir testing. It was testing TCF to TCP
  lowering for the most part. The essential stuff is retained and
  rephrased with linalg-on-tensors. (we should probably rename it
  "refback-run" or something, as it is just a way to invoke RefBackend)
- test/Python/Backend/RefJIT/simple_invoke_numpy.py is XFAIL'ed. Our
  "anti-framework" direction seems to be the likely future path.
2021-08-02 12:08:39 -07:00
Stella Laurenzo ec611c1e6f
Misc fixes for MacOS. (#255)
* Change aligned_alloc -> malloc. It can fail (and does on MacOS) and is a bit over-aggressive optimization for a reference backend.
* Fixed a fragile test that prints -0.0 on MacOS.
* Fail the test (not the framework) on failure to trace (Torch on MacOS is missing features).
* Fix .so -> .dylib for compiler runtime.
2021-07-27 17:48:47 -07:00
Stella Laurenzo 2dbab50444
Rework the python build to a static assembly of MLIR+NPCOMP (#251)
* Adapt to python build system updates.

* Bump llvm to 310c9496d80961188e8d8f8ad306cdf44bd7541f (includes python build updates)
* Adds refback C-API.
* Re-layers all python builds.
* Rework CI.
2021-07-27 16:10:10 -07:00
Stella Laurenzo 2ecbcbf8c7
Bump llvm-project to a085c23aa3c8f91866d7f4588d4f683407dc775d. (#250)
* Added additional *ToLLVM conversion patterns (they were disaggregated from standard).
* Misc renames.
* Spelling change on ConvNCHW op, and it now expects strides and dilations attributes.
2021-07-23 14:13:19 -07:00
Sean Silva 79928cd2dd Generalize support for elementwise ops.
We plumb through e2e a fair number of interesting cases:
- unary, binary, ternary elementwise ops
- ops like `torch.aten.add.Tensor` that also take a scalar parameter
- static size-1 broadcasting

We allow the static size-1 broadcasting case, but emit a runtime error
in the case of dynamic size-1 broadcasting. This seems like a sweet spot
subset of things that can be lowered directly to linalg, while not being
overly constraining to users. This is consistent with what IREE is doing
for CHLO->Linalg lowering as well
([code](50bf7a87e4/iree/compiler/InputConversion/MHLO/BroadcastingToLinalgPatterns.cpp (L1))).

To test the static size-1 case, we added support for the
`torch.aten.unsqueeze` op and lowering for it through
`linalg.tensor_expand_shape`. This involved a generalization of
`MaximizeValueSemantics` able to handle it (the solution there also
works for `torch.aten.flatten.using_ints` which we need for ResNet
anyway)

Also, a few minor additional changes:
- Add `VerifyInvariantsBeforeBackendLowering` pass, which catches a
  large class of errors before we get to backend lowering (now that we
  are doing dialect conversion, the errors are way nicer if we just emit
  them up front rather than in the guts of a random pattern).
- Minor change to RefBackend to allow `linalg.tensor_expand_shape`.

Recommended review order:
- e2e tests in elementwise.py
- `ConvertElementwiseOp` in TorchToLinalg.cpp + elementwise.mlir test
- `ConvertAtenUnsqueezeOp` in TorchToLinalg.cpp + unsqueeze.mlir test
- RefineTypes.cpp + tests
- MaximizeValueSemantics changes + test
- VerifyInvariantsBeforeBackendLowering pass + test
2021-06-28 13:28:38 -07:00
Sean Silva 544cb4ef54 Bump llvm-project to 484b6648fdd4b104eaf7a2504dd07b60af2c9f8d
- add_mlir_doc arg order
- fix some dependent dialects on passes that were now causing errors
- "encoding" attribute on mlirRankedTensorTypeGetChecked
2021-04-22 18:12:55 -07:00
Sean Silva 464feacba9 Bump llvm-project to 223dcdcfbe23affdf17ada7f023ee1872fd76160
- ModuleOp no longer has a terminator.
2021-04-05 17:56:35 -07:00
Sean Silva 641098be54 Clean up some compiler warnings on my machine. 2021-03-23 14:29:05 -07:00
Sean Silva 99178a167d Bump llvm-project to 0524a09cc7e1a0797982feacf505825231efbee7
- renames of OwningRewritePatternList -> RewritePatternSet
  - also `insert` to `add`
- RewritePatternSet holds a context now
- memref dialect split from std
2021-03-23 14:29:05 -07:00
Bryce Arden 4591884d06 [refbackrt] Scalar arg support
* Adds f32 scalar argument support across the ABI boundary.
* Adds support for passing input type / shape information
  across the ABI boundary
* Adds support for parsing / creating input FloatAttr's in
  `npcomp-run-mlir`
2021-03-23 13:16:44 -07:00