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[MPS] Implement hardshrink metal kernel #155304

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manuelcandales
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@manuelcandales manuelcandales commented Jun 6, 2025

Stack from ghstack (oldest at bottom):

Implements the forward and backward hardshrink operators as Metal kernels.
In order to support the lambda parameter, we extend the exec_unary_kernel and exec_binary_kernel methods. Now they take an optional Scalar and an optional ScalarType argument. When the optional ScalarType is provided, it overrides the type of the Scalar.
We add a new REGISTER_UNARY_ALPHA_OP macro, and modify the existing REGISTER_BINARY_ALPHA_OP to support the new feature.

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pytorch-bot bot commented Jun 6, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/155304

Note: Links to docs will display an error until the docs builds have been completed.

⏳ 1 Pending, 9 Unrelated Failures

As of commit 525ae01 with merge base d4d0ede (image):

FLAKY - The following job failed but was likely due to flakiness present on trunk:

BROKEN TRUNK - The following jobs failed but was present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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@pytorch-bot pytorch-bot bot added ciflow/mps Run MPS tests (subset of trunk) release notes: mps Release notes category labels Jun 6, 2025
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github-actions bot commented Jun 6, 2025

Attention! native_functions.yaml was changed

If you are adding a new function or defaulted argument to native_functions.yaml, you cannot use it from pre-existing Python frontend code until our FC window passes (two weeks). Split your PR into two PRs, one which adds the new C++ functionality, and one that makes use of it from Python, and land them two weeks apart. See https://github.com/pytorch/pytorch/wiki/PyTorch's-Python-Frontend-Backward-and-Forward-Compatibility-Policy#forwards-compatibility-fc for more info.


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@manuelcandales manuelcandales marked this pull request as draft June 6, 2025 04:53
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@malfet malfet left a comment

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type API looks a bit fragile, consider using std::pair and encode extra dtype in shader name

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Comment on lines +140 to +141
const std::optional<c10::Scalar> alpha = std::nullopt,
const std::optional<c10::ScalarType> scalar_arg_type = std::nullopt);
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This API looks wrong, it should be something like

Suggested change
const std::optional<c10::Scalar> alpha = std::nullopt,
const std::optional<c10::ScalarType> scalar_arg_type = std::nullopt);
const std::optional<std::pair<c10::Scalar, c10::ScalarType>> alpha = std::nullopt,

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Thank you for working on the change

@malfet malfet added the topic: improvements topic category label Jun 10, 2025
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malfet commented Jun 10, 2025

@pytorchbot merge -f "Lint + MPS are green, will submit some cleanups later on"

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Your change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use -f as last resort and instead consider -i/--ignore-current to continue the merge ignoring current failures. This will allow currently pending tests to finish and report signal before the merge.

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pytorchmergebot pushed a commit that referenced this pull request Jun 11, 2025
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@github-actions github-actions bot deleted the gh/manuelcandales/2/head branch July 13, 2025 02:22
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