Add converter for `aten::_grouped_mm.default` by Sid-V5 · Pull Request #2805 · microsoft/onnxscript

Sid (Sid-V5) · 2026-02-12T20:50:54Z

Implemented the converter for aten::_grouped_mm.default to address #2795.

Changes

Added aten_grouped_mm function in onnxscript/function_libs/torch_lib/ops/core.py

Implementation Details

The aten::_grouped_mm operator performs grouped matrix multiplication. This implementation handles the batch/dense mode (when offs is None), where groups are implicit in the batch dimension:

self: (G, M, K), mat2: (G, K, N) → result: (G, M, N)
Uses op.MatMul for the core computation
Supports optional bias addition via op.Add
Supports optional out_dtype casting via op.Cast

The offset-based mode (when offs is provided) raises NotImplementedError, as it requires segment-level matrix multiplications that are not directly expressible with standard ONNX operators.

Testing

The function follows the same patterns as other converters in core.py (e.g., aten_bmm, aten_mm) and uses the @torch_op decorator for automatic registration.

Fixes #2795

Sid (Sid-V5) · 2026-02-12T20:54:38Z

@microsoft-github-policy-service agree

codecov · 2026-02-16T18:23:52Z

Codecov Report

❌ Patch coverage is 20.00000% with 8 lines in your changes missing coverage. Please review.
✅ Project coverage is 72.66%. Comparing base (b4c10fa) to head (59f7576).

Files with missing lines	Patch %	Lines
onnxscript/function_libs/torch_lib/ops/core.py	20.00%	8 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2805      +/-   ##
==========================================
- Coverage   72.68%   72.66%   -0.02%     
==========================================
  Files         265      265              
  Lines       32284    32294      +10     
  Branches     3053     3056       +3     
==========================================
+ Hits        23466    23468       +2     
- Misses       7782     7790       +8     
  Partials     1036     1036

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Copilot

Pull request overview

Adds an ONNXScript converter for PyTorch’s aten::_grouped_mm (dense/batched mode) and wires it into the TorchLib op test infrastructure to address missing dispatch for aten._grouped_mm.default (#2795).

Changes:

Implemented aten_grouped_mm converter using MatMul, optional Add (bias), and optional Cast (out_dtype).
Registered the new op in TorchLib’s tested op list.
Added OpInfo + sample inputs scaffolding for _grouped_mm in the extra op database.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 4 comments.

File	Description
onnxscript/function_libs/torch_lib/ops/core.py	Adds the `aten::_grouped_mm` converter implementation.
tests/function_libs/torch_lib/ops_test_data.py	Enables testing by adding a `TorchLibOpInfo` entry for `ops.aten._grouped_mm`.
tests/function_libs/torch_lib/extra_opinfo.py	Adds OpInfo registration and sample input generation for `_grouped_mm`.

Justin Chu (justinchuby) · 2026-06-19T17:59:40Z

Two items. (1) The CONFLICTING flag is trivial — a git merge-tree against main resolves cleanly (insertions into non-overlapping regions), so a rebase clears it. (2) Real correctness issue: the offs argument is silently ignored — the code has only a # TODO and falls through to MatMul (~core.py L4515-4523), but the PR description says offset mode "raises NotImplementedError." With offs provided (the ragged/MoE case) this emits silently-incorrect results instead of failing fast; please add an explicit if offs is not None: raise NotImplementedError(...). Also, the OpInfo currently compares against a hand-written torch.matmul-based mock rather than the real torch._grouped_mm, so it's near-tautological — worth strengthening toward real-op parity and covering bias / out_dtype.

Justin Chu (justinchuby) · 2026-07-08T16:41:05Z

Sid (@Sid-V5) would you like to update this PR?

Implements the converter for aten::_grouped_mm.default to address issue microsoft#2795. Handles the batch/dense mode where groups are implicit in the batch dimension using MatMul, with optional bias addition and dtype casting.

…t cases

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

Sid (Sid-V5) · 2026-07-08T17:43:48Z

Justin Chu (@justinchuby)
Rebased onto main to resolve the conflict.
updated core.py to raise NotImplementedError if offs is not None, and updated the OpInfo tests to cover bias/out_dtype and use the real torch._grouped_mm when available

Copilot

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 4 comments.

- Changed out_dtype default from Optional[int]=None to int=-1, matching the sentinel convention used throughout core.py (e.g. aten_sum). Guards for both None and -1 to prevent invalid op.Cast(..., to=-1). - Pass offs, bias, out_dtype as keyword arguments in SampleInput and in the native torch.ops.aten._grouped_mm call, since they are keyword-only in the aten schema (after *). This prevents the try: path from silently failing with TypeError. Addresses Copilot review comments and RUFF/RUF059 lint feedback.

Justin Chu (justinchuby) · 2026-07-23T14:35:13Z

Could you fix lint?

Copilot

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated no new comments.

Copilot

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated no new comments.

Copilot

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated no new comments.

Suppressed comments (1)

onnxscript/function_libs/torch_lib/ops/core.py:4603

out_dtype handling should follow the existing pattern used elsewhere (e.g., quantized_decomposed.py:62-66): treat -1 and None as “not set”, and assert that any provided dtype id is valid (>0) before passing it to op.Cast. This avoids accidentally emitting an invalid ONNX Cast(to=0) if a caller ever forwards an unset/unknown dtype value.

    if out_dtype is not None and out_dtype != -1:
        res = op.Cast(res, to=out_dtype)
    return res

Justin Chu (justinchuby) · 2026-08-01T02:54:06Z

Sid (@Sid-V5) just my inline reviews and it should be ready to merge after that

Justin Chu (justinchuby)

Nit as commented

… unavailable - Update OpInfo in extra_opinfo.py to reference torch.ops.aten._grouped_mm directly instead of _mock_grouped_mm. - Remove _mock_grouped_mm reference helper. - Add .skip(enabled_if=not hasattr(torch.ops.aten, '_grouped_mm')) to TorchLibOpInfo in ops_test_data.py to cleanly skip on PyTorch versions without _grouped_mm support.

Justin Chu (justinchuby) · 2026-09-03T04:26:04Z

Could you fix lint? Thanks

github-project-automation Bot added this to ONNX Script Review Board Feb 12, 2026

github-project-automation Bot moved this to Todo in ONNX Script Review Board Feb 12, 2026

Justin Chu (justinchuby) assigned Xavier Dupré (xadupre) Feb 13, 2026

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Sid (Sid-V5) and others added 3 commits July 8, 2026 23:03

Add aten::_grouped_mm converter implementation

dc1281d

Implements the converter for aten::_grouped_mm.default to address issue microsoft#2795. Handles the batch/dense mode where groups are implicit in the batch dimension using MatMul, with optional bias addition and dtype casting.

Fix grouped_mm: Handle optional arguments correctly and add basic tes…

d61ccf7

…t cases

Potential fix for pull request finding

df7fe91

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

Sid (Sid-V5) force-pushed the add-grouped-mm-2795 branch from d73b04f to 1501909 Compare July 8, 2026 17:42

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Comment thread tests/function_libs/torch_lib/extra_opinfo.py Fixed

Comment thread tests/function_libs/torch_lib/extra_opinfo.py Fixed

Address review comments on grouped_mm

0fa4617

Sid (Sid-V5) force-pushed the add-grouped-mm-2795 branch from 1501909 to 0fa4617 Compare July 9, 2026 08:13

Merge branch 'main' into add-grouped-mm-2795

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Sid (Sid-V5) and others added 2 commits July 16, 2026 10:38

Merge branch 'main' into add-grouped-mm-2795

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Merge branch 'main' into add-grouped-mm-2795

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Merge branch 'main' into add-grouped-mm-2795

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Sid (Sid-V5) added 2 commits August 20, 2026 09:21

Merge branch 'main' into add-grouped-mm-2795

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Merge branch 'main' into add-grouped-mm-2795

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Merge branch 'main' into add-grouped-mm-2795

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Sid (Sid-V5) and others added 2 commits September 3, 2026 10:54

Merge branch 'main' into add-grouped-mm-2795

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style: fix formatting and blank lines in extra_opinfo.py

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Justin Chu (justinchuby) merged commit 9709f8a into microsoft:main Sep 3, 2026
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