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Add targeted_ops to core ExportPass passes for fast-copy optimization (#21702) - #21702

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Add targeted_ops to core ExportPass passes for fast-copy optimization (#21702)#21702
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@apullin apullin commented Aug 9, 2026

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Summary:

Annotate four core ExportPass subclasses across three files with targeted_ops so they participate in the cold-node fast-copy path introduced by parent D97528110.

When fast-copy remains safe, D975 copies eligible non-targeted call_function nodes with existing val metadata instead of replaying them through FakeTensor dispatch. This diff does not add generic pass skipping: every pass still enters replay, and hot nodes continue through each existing call_operator implementation.

Each set exactly mirrors the rewrite guard already present in its pass:

  • MemoryFormatOpsPass targets DimOrderOpsMap keys.
  • DimOrderOpsRevertPass targets MemoryFormatOpsMap keys.
  • NormalizeTransposePass targets aten.t.default.
  • RemoveMixedTypeOperators targets add.Tensor, mul.Tensor, sub.Tensor, both tensor div overloads, and minimum.default.

The diff is now stacked directly on D97528110, which owns the consumer infrastructure. Its previous D109215317 parent left these attributes inert.

Direct raw-graph regressions prove that transpose normalization and mixed-type rewriting still dispatch hot operators while eligible unrelated operators bypass call_operator; the mixed-type test also verifies inserted promotion casts and output dtypes.

A/B against D97528110 on the same host, with each revision run twice:

  • Synthetic add/conv/fc/mul U55 suite: 79.000s / 79.516s here versus 81.238s / 82.371s in D975. Mean speedup 3.1%; warmed speedup 3.5%.
  • CombinedControl U55 LOWERING: 145.801s / 145.888s here versus 148.465s / 149.726s in D975. Mean speedup 2.2%; warmed speedup 2.6%.

Differential Revision: D96247716

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21702

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

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@meta-cla meta-cla Bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Aug 9, 2026
@github-actions github-actions Bot added ciflow/trunk module: arm Issues related to arm backend labels Aug 9, 2026
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@apullin has exported this pull request. If you are a Meta employee, you can view the originating Diff in D96247716.

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This PR needs a release notes: label

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@meta-codesync meta-codesync Bot changed the title Add targeted_ops to core ExportPass passes for fast-copy optimization Add targeted_ops to core ExportPass passes for fast-copy optimization (#21702) Aug 10, 2026
apullin added a commit to apullin/executorch that referenced this pull request Aug 10, 2026
…pytorch#21702)

Summary:

Annotate four core `ExportPass` subclasses across three files with `targeted_ops` so they participate in the cold-node fast-copy path introduced by parent D97528110.

When fast-copy remains safe, D975 copies eligible non-targeted `call_function` nodes with existing `val` metadata instead of replaying them through FakeTensor dispatch. This diff does not add generic pass skipping: every pass still enters replay, and hot nodes continue through each existing `call_operator` implementation.

Each set exactly mirrors the rewrite guard already present in its pass:

- `MemoryFormatOpsPass` targets `DimOrderOpsMap` keys.
- `DimOrderOpsRevertPass` targets `MemoryFormatOpsMap` keys.
- `NormalizeTransposePass` targets `aten.t.default`.
- `RemoveMixedTypeOperators` targets `add.Tensor`, `mul.Tensor`, `sub.Tensor`, both tensor `div` overloads, and `minimum.default`.

The diff is now stacked directly on D97528110, which owns the consumer infrastructure. Its previous D109215317 parent left these attributes inert.

Direct raw-graph regressions prove that transpose normalization and mixed-type rewriting still dispatch hot operators while eligible unrelated operators bypass `call_operator`; the mixed-type test also verifies inserted promotion casts and output dtypes.

A/B against D97528110 on the same host, with each revision run twice:

- Synthetic add/conv/fc/mul U55 suite: 79.000s / 79.516s here versus 81.238s / 82.371s in D975. Mean speedup 3.1%; warmed speedup 3.5%.
- CombinedControl U55 LOWERING: 145.801s / 145.888s here versus 148.465s / 149.726s in D975. Mean speedup 2.2%; warmed speedup 2.6%.

Differential Revision: D96247716
apullin added 2 commits August 9, 2026 17:28
Summary:
After ARM pass-skipping and targeted-op ownership landed separately in D106781989, this diff optimizes the remaining `ExportPass` replay cost for passes that declare `target_ops` or `targeted_ops`.

Cold operator nodes are copied with `graph.node_copy` instead of being re-dispatched through FakeTensor. Old-to-new node remapping preserves dependencies and `get_attr` values. Fast-copy is disabled when `call()` is overridden, for exact convolution or linear targets, or after a hot node changes nested tensor metadata.

The fast path preflights every input before mutating the new graph or module tree, so a remapping fallback cannot leave orphaned nodes, attributes, or remap entries. An explicitly empty `targeted_ops` remains authoritative instead of falling back to legacy `target_ops`.

Nested ARM control-flow submodules use the established `ArmPass.should_run_pass()` contract. This diff does not duplicate pass auto-discovery or generic skipping logic owned by D106781989.

Per review from `jrstevens`, the process-global FakeTensor cache extension is now isolated in child D115374097 so its monkeypatching design and incremental performance can be reviewed independently.

A/B benchmark against the parent revision on the same host, each side run twice:
- CombinedControl U55 lowering: 148.465s / 149.726s with fast-copy vs 165.886s / 171.181s before it. Warm speedup: 12.5%; two-run mean speedup: 11.5%.
- Synthetic U55 suite: 81.238s / 82.371s vs 83.816s / 80.802s. The difference is within run-to-run noise; the large model is the representative workload.

Differential Revision: D97528110
…pytorch#21702)

Summary:

Annotate four core `ExportPass` subclasses across three files with `targeted_ops` so they participate in the cold-node fast-copy path introduced by parent D97528110.

When fast-copy remains safe, D975 copies eligible non-targeted `call_function` nodes with existing `val` metadata instead of replaying them through FakeTensor dispatch. This diff does not add generic pass skipping: every pass still enters replay, and hot nodes continue through each existing `call_operator` implementation.

Each set exactly mirrors the rewrite guard already present in its pass:

- `MemoryFormatOpsPass` targets `DimOrderOpsMap` keys.
- `DimOrderOpsRevertPass` targets `MemoryFormatOpsMap` keys.
- `NormalizeTransposePass` targets `aten.t.default`.
- `RemoveMixedTypeOperators` targets `add.Tensor`, `mul.Tensor`, `sub.Tensor`, both tensor `div` overloads, and `minimum.default`.

The diff is now stacked directly on D97528110, which owns the consumer infrastructure. Its previous D109215317 parent left these attributes inert.

Direct raw-graph regressions prove that transpose normalization and mixed-type rewriting still dispatch hot operators while eligible unrelated operators bypass `call_operator`; the mixed-type test also verifies inserted promotion casts and output dtypes.

A/B against D97528110 on the same host, with each revision run twice:

- Synthetic add/conv/fc/mul U55 suite: 79.000s / 79.516s here versus 81.238s / 82.371s in D975. Mean speedup 3.1%; warmed speedup 3.5%.
- CombinedControl U55 LOWERING: 145.801s / 145.888s here versus 148.465s / 149.726s in D975. Mean speedup 2.2%; warmed speedup 2.6%.

Differential Revision: D96247716
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