Commit Graph

212 Commits (d2bc70f18855e672f91942b19259a5938d6d3cf4)

Author SHA1 Message Date
Rob Suderman 61888690bb
[onnx] Add support for `onnx.sinh` (#2643)
Adds a lowering from `onnx.sinh` to `aten.sinh`. This includes adding
the `aten.sinh` operator.
2023-12-15 21:23:51 -08:00
Rob Suderman 705ea958ae
[onnx] Lowerings from `onnx.transpose` (#2641)
Lowerings for `transpose` from ONNX to `aten`. Implementation depends on
making multiple `aten.transpose` operations swapping pairs of dimensions.
As `onnx.transpose` can swap around any dimensions it may require
constructing multiple `aten.transpose`.
2023-12-15 15:30:05 -08:00
Rob Suderman 061af696ce
[onnx] Lowering for `onnx.shape` to `torch` and `tensor` (#2648)
Includes the lowering from the `aten` equivalent to `tensor` operations.
2023-12-15 11:37:49 -08:00
Gaurav Shukla eb9249e601
[ONNX][MLIR] Add support for LeakyRelu and GatherElements op (#2655)
This commit adds support for `LeakyRelu and GatherElements` op in the
onnx pipeline.

Signed-off-by: Gaurav Shukla <gaurav@nod-labs.com>
2023-12-15 11:18:28 -08:00
saienduri f59c01fd2f
[MLIR][ONNX] Add OnnxToTorch support for q-z ops (specific ops in description) (#2601)
This commit adds the OnnxToTorch support for Reciprocal, Round,
ScatterElements, Sigmoid, Sin, Tanh, Sqrt, Sub, Sum, Where, Xor,
Squeeze, Unsqueeze ops.
For reviewers, the ops that weren't trivial and probably require extra
review are Sum, Squeeze, and Unsqueeze.
2023-12-15 09:36:18 -08:00
Andreas Falkenberg 4ec8b9fc02
[onnx] add support for onnx.LessOrEqual (#2639)
Added the less or equal operation to OnnxToTorch. 
onnx.LessOrEqual

---------

Co-authored-by: root <andreas.falkenberg@amd.com>
2023-12-14 22:23:23 -05:00
Rob Suderman 4857606ffe
[onnx] Lowerings from `onnx.selu` (#2634)
Lowerings for `selu` lowerings for ONNX to the corresponding torch
implementations. Torch's `selu` implementation has fewer features so
we use the a generalized `elu` with the input scale set to `1.0`.
2023-12-14 08:53:47 -08:00
John Wu 42392bc845
[MLIR][ONNX] Add OnnxToTorch support for matmul ops (#2629)
This commit adds the OnnxToTorch support for Matmul.
2023-12-13 09:35:32 -08:00
Frederik Harwath b656c674ee Implement e2e support for aten.acos op
This depends on a change in the LLVM core repository which adds acos
support to the MLIR Math dialect.
2023-12-12 10:52:02 +01:00
Vivek Khandelwal 0b4422a253 [MLIR][ONNX] Add OnnxToTorch support for bitwise and math ops
This commit adds the OnnxToTorch support for BitwiseXor, BitwiseOr, Div, Equal, Cast,
Ceil, Floor, Cos, and Clip op.
This commit also adds the TorchToLinalg support for aten.clamp.Tensor and aten.clamp_min.Tensor op.

Signed-Off By: vivekkhandelwal1424@gmail.com
2023-12-11 19:36:01 +05:30
Vivek Khandelwal dc9ea08db5 [MLIR][ONNX] Add OnnxToTorch support for atan and bitwise ops
This commit adds the OnnxToTorch support for Atan, Bitshift, BitwiseAnd,
and BitwiseNot op.
This commit also adds the TorchToLinalg support for AtenBitwiseLeftShiftTensorOp.

Signed-Off By: vivekkhandelwal@nod-labs.com
2023-11-28 17:19:07 +05:30
Stella Laurenzo e06efc5136
Initial TorchOnnxToTorch conversion pipeline. (#2585)
Adds a pipeline to convert custom ops and metadata represented as
`torch.operator` custom ops to corresponding `torch` ops where possible.

This is part of a multi-part approach for building ONNX import in as a
regular feature of torch-mlir. It is focused on the conversions vs the
infra. We will end up maintaining a [pure-python
importer](https://github.com/nod-ai/SHARK-Turbine/blob/main/python/shark_turbine/importers/onnx_importer.py)
to go with this in torch-mlir, and we will also maintain test case
generation utilities derived from it.

I have left substantial documentation in the README of the conversion
directory, including the recommended approach that we will take to keep
building this out.

(note that this organizes the code to coincide with the refactoring in
#2442 versus the current flat arrangement)
2023-11-21 21:02:55 -08:00