[executorch][vulkan] Add payload-bounded constant sharding - #21467
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Pull Request resolved: #21404 **Enable deterministic payload-bounded Vulkan constant sharding** **Problem** Large Vulkan exports can make inline PTE named data exceed downstream artifact limits, but `NamedDataStore` cannot externalize that data into bounded groups. **Solution** - **Before:** Vulkan constants remain inline with no payload-bounded externalization option. - **After:** an opt-in `uint64` raw-data cap externalizes constants after graph construction into deterministic shards. **Implementation** - `NamedDataStore.externalize_pte_data` groups aliases by backing buffer, preserves existing tags, and rejects oversize buffers or collisions atomically. - `parse_compile_options` and `parse_compile_spec` transport `external_constants_max_data_bytes` as a strict positive `uint64`. - `VulkanBackend.preprocess` applies sharding only when the option is present. **Constraints** The default path is unchanged; buffers are not copied or split. The cap bounds unique raw buffer bytes per external tag, not final `FlatTensor` file size including alignment and header overhead. Co-authored-with: Claude Code. ghstack-source-id: 407350478 @exported-using-ghexport Differential Revision: [D113608555](https://our.internmc.facebook.com/intern/diff/D113608555/)
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Pull Request resolved: #21405 **Dynamic Q4 embedding reuse now preserves the complete packing configuration.** A resize used to rebuild the uniform field by field, which dropped `is_linear_weight`. The resize hook now captures the fully initialized `EmbeddingParams` and rewrites only `num_indices` and `total_blocks`. Key changes: - `EmbeddingQ4gsw.cpp` — pass a 32-byte base parameter struct by value through the resize callback. - Resize recomputation updates only dynamic counts, so current and future invariant fields are preserved by construction. - Mirrors Vulkan `EmbeddingQ4gsw.cpp`, which retains `is_linear_weight` in push-constant state across resize. Static and nonlinear embedding behavior is unchanged. Co-authored-with: Claude Code. ghstack-source-id: 407350572 @exported-using-ghexport Differential Revision: [D113627870](https://our.internmc.facebook.com/intern/diff/D113627870/)
Pull Request resolved: #21406 **Dynamic-shape coverage now locks linear-packed Q4 embedding reuse.** The fixture exports a discriminating linear-packed model and reuses one loaded graph across N=16,8,1,16, covering the resize transition that previously reset nibble order. Key changes: - `test_dynamic_shape_export.py` — export deterministic true-packing artifacts and torch goldens for N=16,8,1. - `test_dynamic_shape.cpp` — add one-graph linear-packed reuse coverage while preserving the nonlinear control. The explicit true-vs-false output guard prevents a non-discriminating fixture. Co-authored-with: Claude Code. ghstack-source-id: 407350695 @exported-using-ghexport Differential Revision: [D113627869](https://our.internmc.facebook.com/intern/diff/D113627869/)
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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #21404 by @JCNTH
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ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/194/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/194/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/main
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/194/orig
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cc @SS-JIA @manuelcandales @digantdesai @cbilgin