Add F.scaled_grouped_mm

[crcrpar]

What does this PR do?

As per title, adds https://docs.pytorch.org/docs/main/generated/torch.nn.functional.scaled_grouped_mm.html

[Copilot]

Pull Request Overview

This PR adds support for torch.nn.functional.scaled_grouped_mm, a PyTorch function for scaled grouped matrix multiplication.

Key changes:

• Implements the scaled_grouped_mm torchsymbol with input validation and shape inference
• Adds three comprehensive test cases covering 2D×2D and 2D×3D tensor combinations with different scaling types
• Registers the operation in the torch executor with appropriate availability checking

Reviewed Changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

File	Description
thunder/torch/init.py	Adds scaled_grouped_mm function with shape validation, dtype checking, and output shape computation
thunder/tests/test_ops.py	Adds test cases for tensorwise and blockwise scaling scenarios with FP8 and MXFP8 dtypes
thunder/executors/torchex.py	Registers scaled_grouped_mm operation and implements checker function for executor

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[Copilot]

Pull Request Overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

Comments suppressed due to low confidence (1)

thunder/tests/test_ops.py:1

• Both test_scaled_grouped_mm_3d2d_rowwise and test_scaled_grouped_mm_2d3d_rowwise test the same 2D @ 3D case (mat_a is 2D, mat_b after transpose is 3D). There is no test coverage for the 3D @ 2D case where mat_a would be 3D with shape (groups, m, k) and mat_b would be 2D with shape (k, n). Consider adding a test for this case or modifying one of the existing tests to cover it.

from collections.abc import Callable

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Pull Request Overview

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

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