6cba93b16e
[ONNX][TorchToLinalg] Add support for dynamic dims in Interpolate lowering ( #3351 )
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Addresses [Shark-Turbine
#196 ](https://github.com/nod-ai/SHARK-TestSuite/issues/196 )
Related tracker [Shark-Turbine
#566 ](https://github.com/nod-ai/SHARK-Turbine/issues/566 )
Related onnx.Resize issues [Shark-Turbine
#616 ](https://github.com/nod-ai/SHARK-Turbine/issues/616 )
2024-05-17 12:18:57 -07:00
cba91a9b96
[ONNX][TOSA] Adds ONNX to TOSA e2e tests ( #3358 )
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- Refactors OnnxBackend to be generic and consume any Torch backend.
---------
Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2024-05-16 21:44:26 -07:00
7faba75696
[Torch] Decompose AtenMaskedScatterOp ( #3353 )
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Co-authored-by: Yuanqiang Liu <liuyuanqiang.yqliu@bytedance.com>
2024-05-16 15:27:25 +08:00
0ca88028cd
[FxImporter][TOSA] Enable FxImporter to TOSA e2e tests ( #3349 )
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Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2024-05-15 14:37:30 -07:00
1d4859699b
MaxPool1d lowering to linalg ( #3295 )
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Co-authored-by: root <root@i32b01216.sqa.eu95>
2024-05-10 22:05:26 +05:30
10db310460
build: manually update PyTorch version ( #3291 )
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Set PyTorch and TorchVision version to nightly release 2024-05-05.
Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-05-10 21:45:06 +05:30
afe87d62b4
[Linalg] [Stablehlo] Promote type for compare scalar op ( #3306 )
2024-05-10 02:20:06 +08:00
346a536c9f
[Torch Dialect] decompose all index_put-like op to aten.index_put.hacked_twin for stricter semantics ( #3071 )
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This PR decomposes all index_put-like op to aten.index_put.hacked_twin for stricter semantics, i.e., no None index in indices argument.
2024-05-08 22:44:57 +08:00
abef114c0c
[torch] emit aten.Softshrink and aten.Hardshrink ( #3248 )
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as title
2024-05-08 15:20:45 +08:00
9be6877c22
Temporarily remove QuantizedMLP_basic ( #3301 )
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See issue #3298
2024-05-07 14:32:13 -07:00
17c3c15131
[ONNX] Add OnnxToTorch lowering for SoftmaxCrossEntropyLoss op ( #3278 )
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Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-05-06 17:26:32 +05:30
11cd7cd9e7
Folder and Canonicalizer for PrimsConvertElementTypeOp and AtenMaxPool2dWithIndicesOp ( #3272 )
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While playing with TorchDynamo on ResNet18. I notice following issues:
- `prims.convert_element_type` can’t be canonicalized even if the input
and the output share the same type
- `aten.max_pool2d_with_indices` is always used instead of
`aten.max_pool2d`, even if the second returned output (indices) has no
user
This PR fixes above issues by adding a folder to the
PrimsConvertElementTypeOp and a canonicalizer to the
AtenMaxPool2dWithIndicesOp
Lit test:
`cmake --build build --target check-torch-mlir-all`
---------
Co-authored-by: Ze Zhang <ze.zhang@getcruise.com>
2024-05-02 00:03:41 -07:00
8c48135a42
[linalg] Fix bug for conversion of complex dtype ( #3269 )
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The conversion of complex type wasn't supported or checked; the support
and required tests were added.
Fixes:
https://github.com/iree-org/iree/issues/17226#issuecomment-2087779158
2024-05-01 12:06:53 +05:30
33eef15e42
Support onnx.If ( #2825 )
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This is probably a decent PR for learning about blocks and regions.
If you're here to learn about that, consider also looking at
lib/Conversion/TorchToSCF/TorchToSCF.cpp
While this doesn't include an e2e test, it is tested downstream in
https://github.com/nod-ai/SHARK-TestSuite/blob/main/e2eshark/onnx/operators/If/model.py
---------
Co-authored-by: Xida Ren <xida.ren.dev@gmail.com>
2024-04-30 18:36:40 +00:00
72349f7522
[TorchToLinalg] Adds Quantization Support for ConvTranspose ( #3240 )
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I spent a little while debugging numerics issues with some tests similar
to the ones in quantized_models.py, only to find that pytorch's
quantized conv transpose is catastrophically inaccurate. I'll upstream
the issue and only leave the tests here which are of the form quantize
-> dequantize -> op.
2024-04-30 09:23:09 -07:00
f32ada993d
[Stablehlo] Improve the lowering of pool op in stablehlo ( #3259 )
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1. Handle case stride == None
2. add avgpool3d maxpool1d maxpool3d lowering
2024-05-01 00:06:13 +08:00
0a5ff68d9d
[stablehlo] Support PrimsCollapseOp and PrimsSplitDimOp in stablehlo ( #3230 )
2024-04-29 17:40:30 +08:00
b1e2241479
[ONNX] Fix Onnx.Selu lowering and canonicalizer for IntImplicit op ( #3221 )
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Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-04-29 04:00:01 +00:00
5684dc0441
[Torch] emit aten.celu and decompose it ( #3247 )
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CELU(x)=max(0,x)+min(0,α∗(exp(x/α)−1))
2024-04-28 17:23:40 +08:00
46c0f3cad0
[Torch] emit aten.log_sigmoid and decompose it to log(sigmoid) ( #3246 )
2024-04-28 11:47:43 +08:00
6877302504
[NFC reformat] Applies pre-commit formatting to Python files. ( #3244 )
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This is a large change because prior to this point, Python files in the
project were not consistently formatted. This reformats them all with
black defaults.
Based on experience with prior projects, if you have a dev/long-term
branch with Python patches, you can minimize merge conflicts prior to
rebasing to include this commit by running `black` on your modified
Python files, squashing, and then rebasing/merging.
2024-04-27 14:16:31 -07:00
4fbe77a051
[dynamo] Verify the default value is passed by kwargs ( #2998 )
2024-04-28 02:18:33 +08:00
9a12a093a6
[onnx] Support `onnx.OneHot` lowering to `torch` ( #3196 )
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[onnx] Support `onnx.OneHot` lowering to `torch`
Leverage the `aten.onehot` implementation along with `aten.transpose`
and `aten.where.scalar`.
2024-04-26 12:08:15 -07:00
ac85338491
[Stablehlo] Support AtenPowScalarOp, AtenTanOp, AtenAsinhOp, AtenAcoshOp, AtenAtanhOp, Atan2Op ( #3233 )
2024-04-26 15:47:44 +08:00
122eb69a98
[stablehlo] add aten left/right shift op conversion support ( #3234 )
2024-04-26 09:20:49 +08:00
7030eacb76
[stablehlo] Support aten.any and aten.all lowering ( #3217 )
2024-04-25 11:15:52 +08:00
fab2696489
[Torch] support aten.trunc ( #3219 )
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decompose `trunc(x)` to `sign(x) * floor(abs(x))`
2024-04-24 14:32:33 +08:00
e18bf42d0e
[stablehlo] Support ConstantPadNdOp in stablehlo ( #3211 )
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as title
2024-04-24 14:15:11 +08:00
42b9eccdb3
[Stablehlo] Fix AtenSumDimIntListOp when dim==None ( #3216 )
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as titile
2024-04-24 11:25:46 +08:00
4da3d714cc
[Torch] Support AtenProdOp on linalg and stablehlo ( #3215 )
2024-04-24 11:14:04 +08:00
a8ba865fca
[torch] Adds Quantization Support for `aten.relu` ( #3177 )
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A choice was made to quantize the return type of Relu with a scale and
zero point copied from the input's quantization scheme. With this
choice, the torch-to-linalg conversion of quantized Relu essentially
computes max(input, zeroPoint) in the elementwise payload.
2024-04-23 11:01:36 -07:00
db3842f2e8
[Stablehlo] support lowering sinh & cosh to stablehlo ( #3213 )
2024-04-23 19:54:58 +08:00
c1967b607f
[Stablehlo] add AtenLog10Op, AtenLog2Op lowering to stablehlo ( #3208 )
2024-04-23 19:06:55 +08:00
1f8123b5f0
[Stablehlo] support unary ops which promote to floating point ( #3209 )
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* promote input to output element-type when lowering to stablehlo, so
that it could satisfy stablehlo's type constraints.
* split promote-to-fp unary ops from fp-only unary ops.
2024-04-23 17:57:12 +08:00
797e4cd395
[Stablehlo] lowering asin, acos, atan ( #3207 )
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* lowering asin, acos and atan to chlo ops.
2024-04-23 16:24:53 +08:00
cff2f084d4
[torch] Add OnnxToTorch lowering for `onnx.ReduceL2` ( #3175 )
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Adds OnnxToTorch lowering for the ReduceL2 op.
2024-04-23 02:03:05 -04:00
3c252cdd44
[onnx] Add `onnx-to-torch` lowering for random ops ( #3193 )
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This commit adds the OnnxToTorch lowering for Onnx's RandomNormal, RandomNormalLike, RandomUniform, and RandomUniformLike op.
2024-04-22 22:28:07 +05:30
6abc7371c8
[MLIR][TORCH] Fix OnnxToLinalg lowering issue for Squeeze and Unsqueeze op ( #2991 )
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This commit also cleans up the OnnxToTorch lowering for the Squeeze and
Unsqueeze op and adds the support for handling edge cases.
Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-04-22 08:52:42 +00:00
e5bdd71baf
[Torch] Emit and decompose prims.iota op ( #3132 )
2024-04-21 19:45:01 -07:00
a60e84e5ee
[stablehlo] add aten.expm1 op conversion support ( #3199 )
2024-04-21 19:20:49 -07:00
8222637159
[onnx] Extend op version number of `onnx.ScatterElements` ( #3195 )
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Version number was set too high. Lowered to support more cases allows
more tests to pass.
Co-authored-by: Robert Suderman <rsuderman@Roberts-MacBook-Pro.local>
2024-04-21 12:32:18 -04:00
733cace1df
[onnx] Fix `onnx.split` by directly handling slicing ( #3194 )
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Previous implementation erroneously mixed up num_outputs with
slice_size. New version correctly computs the slice size and directly
performs slicing rather than leveraging `aten.split.tensor`. This is due
to `onnx` supporting a fixed number of splits making the size
computation more easily computeable when lowering to `aten` rather than
deferring to `aten.split.tensor`.
---------
Co-authored-by: Robert Suderman <rsuderman@Roberts-MacBook-Pro.local>
2024-04-21 12:31:56 -04:00
b6b01602d3
[stablehlo] add aten.fmod.Tensor op conversion support ( #3198 )
2024-04-21 08:39:36 +08:00
ea0ecb67be
[stablehlo] add aten.remainder.Tensor op conversion support ( #3197 )
2024-04-21 00:03:37 +08:00
b01245c0e8
[onnx] Fix `onnx.Not` for non-bool inputs ( #3187 )
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Need to perform a bool cast to support `onnx.Not` on non-bool inputs.
2024-04-19 11:32:24 -07:00
790a697245
[Torch] Add folder for AtenIntOp, AtenFloatOp ( #3189 )
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See unit test below:
```
// CHECK-LABEL: func.func @torch.aten.tensor.float(
// CHECK-NEXT: torch.vtensor.literal(dense<1.000000e+01> : tensor<f32>) : !torch.vtensor<[],f32>
func.func @torch.aten.tensor.float() -> !torch.vtensor<[],f32> {
%none = torch.constant.none
%false = torch.constant.bool false
%float1.000000e01 = torch.constant.float 1.000000e+01
%67 = torch.aten.tensor.float %float1.000000e01, %none, %none, %false : !torch.float, !torch.none, !torch.none, !torch.bool -> !torch.vtensor<[],f32>
return %67 : !torch.vtensor<[],f32>
}
// CHECK-LABEL: func.func @torch.aten.tensor.int(
// CHECK-NEXT: torch.vtensor.literal(dense<45> : tensor<si32>) : !torch.vtensor<[],si32>
func.func @torch.aten.tensor.int() -> !torch.vtensor<[],si32> {
%none = torch.constant.none
%false = torch.constant.bool false
%int45 = torch.constant.int 45
%67 = torch.aten.tensor.int %int45, %none, %none, %false : !torch.int, !torch.none, !torch.none, !torch.bool -> !torch.vtensor<[],si32>
return %67 : !torch.vtensor<[],si32>
}
```
2024-04-19 22:17:06 +08:00
5a98c72c7f
[StableHLO] Fix aten.clamp.Tensor in FxImporter2StableHLO ( #3190 )
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The FX importer will pass static shapes to the Torch dialect, so it
needs to generate a StableHLO that satisfies shape inference.
2024-04-19 17:08:29 +08:00
0a6073414d
[FxImporter] Add fx importer to stablehlo e2e test config ( #3183 )
2024-04-18 21:29:17 -07:00
6c4f7deebb
[stablehlo] add aten.clamp.Tensor op conversion support ( #3185 )
2024-04-19 10:55:27 +08:00
be742a937d
[onnx] Update the failure triage for onnx ( #3186 )
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Reclassifying what the source of failures are for various bugs so we can
reprioritize what failures are common.
2024-04-18 14:58:13 -07:00
zjgarvey
Suraj Sudhir
Xinyu Yang
NeverRaR
Vivek Khandelwal
penguin_wwy
Jiawei Wu
Ze Zhang
Prashant Kumar
Xida Ren (Cedar)
Yuanqiang Liu
Stella Laurenzo
Rob Suderman
Vinayak Dev