[Vulkan] Keep reductions the reduce shaders cannot handle on CPU - #23206
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The general reduce implementation handles one or two reduced dims, but the partitioner accepted empty dim lists and full sum/mean reductions over N-D inputs, which then failed to build or computed the wrong reduction. Texture storage also folds batch into channels, so 4D reductions over dim 0, or over dim 1 with batch above 1, cannot be computed. These cases now stay on CPU. Authored with OpenAI Codex; split planned with Claude Code.
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/23206
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Superseded by #23245, part 6/15 of the ghstack replacement series. The current integration PR is #23254. This PR is closed in favor of the replacement; its previous description and review history are retained.
The general reduce implementation handles one or two reduced dims, but the partitioner accepted empty dim lists and full sum/mean reductions over N-D inputs, which then failed to build or computed the wrong reduction. Texture storage also folds batch into channels, so 4D reductions over dim 0, or over dim 1 with batch above 1, cannot be computed. These cases now stay on CPU.
Part 6/15 of the Vulkan transformer and operator-conformance stack. Depends on #23205; review against the selected base branch. Integration PR: #23162.
Validation: 2 passed, 2 warnings in 70.88s (0:01:10). Lintrunner and git diff --check pass. Native tests use MoltenVK with portable CPU kernels; hardware and SwiftShader CI are pending.
Authored with OpenAI Codex; split planned with Claude Code.
cc @SS-JIA @manuelcandales @digantdesai @cbilgin