Commit Graph

8 Commits (revert-2869-AtenSlice-folder)

Author SHA1 Message Date
Sambhav Jain 8a17c98b74
Bump stablehlo to openxla/stablehlo@fd52182f76 (#2821)
With the recent LLVM integrate and changes from
https://github.com/llvm/llvm-project/pull/78260, we hit this build error
in Stablehlo (which is quite old).
```
external/stablehlo/stablehlo/transforms/StablehloRefineShapes.cpp:1020:14: error: no member named 'startRootUpdate' in 'mlir::PatternRewriter'
    rewriter.startRootUpdate(op);
    ~~~~~~~~ ^
external/stablehlo/stablehlo/transforms/StablehloRefineShapes.cpp:1026:16: error: no member named 'finalizeRootUpdate' in 'mlir::PatternRewriter'
      rewriter.finalizeRootUpdate(op);
      ~~~~~~~~ ^
external/stablehlo/stablehlo/transforms/StablehloRefineShapes.cpp:1029:16: error: no member named 'cancelRootUpdate' in 'mlir::PatternRewriter'
      rewriter.cancelRootUpdate(op);
      ~~~~~~~~ ^
external/stablehlo/stablehlo/transforms/StablehloRefineShapes.cpp:1108:14: error: no member named 'updateRootInPlace' in 'mlir::PatternRewriter'
    rewriter.updateRootInPlace(op->getParentOp(), [&]() { return; });
    ~~~~~~~~ ^
4 errors generated.
Target @torch-mlir//:torch-mlir-opt failed to build
```

I'm still puzzled as to how this didn't fail with the CMake merge gating
CI (do we not test Stablehlo builds/tests?). In any case, bumping our
submodule to https://github.com/openxla/stablehlo/pull/1918 fixes it.

It exposes a new failing lit test in TorchToStablehlo though, that I
have looped stablehlo developers into
([here](https://discord.com/channels/999073994483433573/999074539138990131/1201235845391331419)).
```
bazel run @torch-mlir//test/Conversion:TorchToStablehlo/scatter.mlir.test 

...external/torch-mlir/test/Conversion/TorchToStablehlo/scatter.mlir
within split at <stdin>:1 offset :33:8: error: unexpected error: Expects non-empty reduction block for type inference                                                                               
  %0 = torch.aten.scatter.src %arg0, %int0, %arg1, %arg2 : !torch.vtensor<[?,?],si64>, !torch.int, !torch.vtensor<[?,?],si64>, !torch.vtensor<[?,?],si64> -> !torch.vtensor<[?,?],si64>             
       ^                                                                                                                                                                                            
LLVM ERROR: Failed to infer result type(s).               
```

Bazel CI:
https://github.com/sjain-stanford/torch-mlir/actions/runs/7732673480/job/21083102228
2024-01-31 14:21:17 -08:00
Quinn Dawkins 494089d53d
Clang format refresh (#2812)
After noticing a number of commits with unrelated formatting changes,
I think something was changed with clang-format at one point and we're
seeing a number of unrelated changes. Doing a refresh can help avoid
this.

The changes made here came from
```
find lib -iname *.h -o -iname *.cpp  | xargs clang-format -i --style=llvm
find include -iname *.h -o -iname *.cpp  | xargs clang-format -i --style=llvm
find projects -iname *.h -o -iname *.cpp  | xargs clang-format -i --style=llvm
```
2024-01-29 12:59:33 -05:00
lonely eagle e581b33f96
[Stablehlo]fix CumsumInputDtypeInt32Module_basic on stablehlo backend. (#2797)
Code used for testing.For the location of CumsumInputDtypeInt32Module in
the repo you can see
[here](311b6b0286/projects/pt1/python/torch_mlir_e2e_test/test_suite/basic.py (L4148)).
```python
import torch
import torch_mlir

class CumsumInputDtypeInt32Module(torch.nn.Module):

    def __init__(self):
        super().__init__()

    def forward(self, val):
        return torch.ops.aten.cumsum(val, 1)
module = torch_mlir.compile(CumsumInputDtypeInt32Module(), [torch.randn(2, 7, 4).to(torch.int32)], output_type="stablehlo")
print(module.operation.get_asm())
```
After fixing the bugs.
```
module attributes {torch.debug_module_name = "CumsumInputDtypeInt32Module"} {
  func.func @forward(%arg0: tensor<2x7x4xi32>) -> tensor<2x7x4xi64> {
    %0 = stablehlo.constant dense<0> : tensor<i64>
    %1 = stablehlo.convert %arg0 : (tensor<2x7x4xi32>) -> tensor<2x7x4xi64>
    %2 = "stablehlo.reduce_window"(%1, %0) ({
    ^bb0(%arg1: tensor<i64>, %arg2: tensor<i64>):
      %3 = stablehlo.add %arg1, %arg2 : tensor<i64>
      stablehlo.return %3 : tensor<i64>
    }) {padding = dense<[[0, 0], [6, 0], [0, 0]]> : tensor<3x2xi64>, window_dilations = dense<1> : tensor<3xi64>, window_dimensions = dense<[1, 7, 1]> : tensor<3xi64>, window_strides = dense<1> : tensor<3xi64>} : (tensor<2x7x4xi64>, tensor<i64>) -> tensor<2x7x4xi64>
    return %2 : tensor<2x7x4xi64>
  }
}
```
2024-01-25 10:44:08 +08:00
JianzheXiao 31ef08b63d
[Stablehlo]Add support for AvgPool1dOp (#2268)
* Add support for AvgPool1d

* Update AbstractInterpLibrary

* support avgpool1d in linalg

* refactored code

* fix nit problem
2023-07-25 14:09:53 +08:00
Yuanqiang Liu 0548e2ef3b
[Stablehlo] fix promoteType() when input doesn't have DefiningOp (#2262) 2023-06-26 00:04:17 +08:00
Yuanqiang Liu 0096ceae2f
[Stablehlo] fix reduce max init_value with -inf (#2064)
* [Stablehlo] fix reduce max init_value with -inf

* update
2023-05-06 12:05:51 -07:00
Ziheng Jiang 72bb902640
[STABLEHLO] Move utils.h to include/ (#1974) 2023-03-27 21:16:21 -07:00
Ashay Rane 711646d095
mhlo: migrate conversion to stablehlo (#1840)
This patch replaces all MHLO operations with their StableHLO
counterparts and adds a validation pass to ensure that no MHLO operations
remain before translating all Stablehlo operations to the MHLO dialect
for further lowering to the Linalg dialect.

This patch also updates all lit tests so that they refer to the
`convert-torch-to-stablehlo` pass and so that they check for StableHLO
operations.
2023-02-02 07:29:47 -06:00