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[executorch][cuda] Run CudaExecutor steps from prepared embeddings - #24063
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/24063
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…ckends Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * #24076 * #24107 * #24075 * #24074 * #24073 * #24072 * #24066 * #24065 * #24064 * #24063 * __->__ #24062 Move the MLX executor's EngineEmbeddings (vision encoder + embed_text + MuseGlimmerMaterializer) into runtime/model_embeddings so the CUDA batching executors can materialize prepared image inputs the same way. MLX behavior is unchanged; it now holds a MuseGlimmerModelEmbeddings. Differential Revision: D125987290 Pull Request resolved: #24062
Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * #24076 * #24107 * #24075 * #24074 * #24073 * #24072 * #24066 * #24065 * __->__ #24064 * #24063 * #24062 export_cuda_batching optionally adds vision_encoder, embed_text and a dynamic forward_from_embeddings over the same off-graph KV contract, and writes pos_embed.bin next to the program. Differential Revision: D125987292 Pull Request resolved: #24064
Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * #24076 * #24107 * #24075 * #24074 * #24073 * #24072 * #24066 * __->__ #24065 * #24064 * #24063 * #24062 The CUDA backend factory builds the image preparation spec from the shared embeddings engine, and serve_batching passes --pos-embed-path through, so image requests are served on regular CUDA batching. Differential Revision: D125987293 Pull Request resolved: #24065
Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * #24076 * #24107 * #24075 * #24074 * #24073 * #24072 * __->__ #24066 * #24065 * #24064 * #24063 * #24062 The CUDA DFlash executor accepts prepared image inputs on admission; image steps run the target from embeddings, then hidden taps and drafting proceed as for tokens. Differential Revision: D125987295 Pull Request resolved: #24066
…24653) This PR was created by the merge bot to help merge the original PR into the main branch. ghstack PR number: #24063 by @Gasoonjia ^ Please use this as the source of truth for the PR details, comments, and reviews ghstack PR base: https://github.com/pytorch/executorch/tree/gh/Gasoonjia/86/base ghstack PR head: https://github.com/pytorch/executorch/tree/gh/Gasoonjia/86/head Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/Gasoonjia/85/orig Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/Gasoonjia/86/orig Differential Revision: [D125987291](https://our.internmc.facebook.com/intern/diff/D125987291/) @diff-train-skip-merge Co-authored-by: gasoonjia <gasoonjia@icloud.com>
Stack from ghstack (oldest at bottom):
Steps that carry a prepared (image) input run forward_from_embeddings with the
materialized rows; token-only steps keep the static forward_{N} methods and
their CUDA graphs. SessionTable packs prepared rows as placeholders so the
cache still plans their positions.
Differential Revision: D125987291