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add mm embedding service.
add mm embedding worker.
add tensor serialization and deserialization in shared memory manager.

@dongxianzhe dongxianzhe changed the title feat: add mm_embed worker and service. feat: add mm embed worker and service. Dec 11, 2025
// if raw_output.outputs.size() value is 0,
// this means all sequences are in prefill stage status.
const int64_t num_seqs = raw_output.outputs.size();
int64_t num_seqs;
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还是需要加上MMBatch的子类,不能改变现有Batch逻辑。

@dongxianzhe dongxianzhe force-pushed the feat/mm_embed_service branch from d642170 to a103d80 Compare December 12, 2025 12:30
@DragonFive DragonFive self-requested a review December 17, 2025 12:30
MMBatchData(const std::vector<MMData>& datas);
MMBatchData(uint32_t ty, const MMDict& items);

bool has(uint32_t type) const { return type & ty_ != 0; }
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type & (ty_ != 0) may be better.

if (model_backend == "llm") {
worker_type =
(options.task_type() == "generate") ? WorkerType::LLM : WorkerType::ELM;
if (options.task_type() == "gnerate") {
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generate may be ok?

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4 participants