sleepy/llama.cpp
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memory : add llama_memory_hybrid_iswa (#18601)

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* memory : add llama_memory_hybrid_iswa

* Update src/llama-memory-hybrid-iswa.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Tarek Dakhran
2026-01-21 13:30:23 +01:00
committed by GitHub
parent 12a4a47e6a
commit ad8d85bd94
6 changed files with 598 additions and 17 deletions
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src/llama-model.cpp
+39 -17
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@@ -8,6 +8,7 @@
#include "llama-kv-cache.h"
#include "llama-kv-cache-iswa.h"
#include "llama-memory-hybrid.h"
#include "llama-memory-hybrid-iswa.h"
#include "llama-memory-recurrent.h"
#include "ggml-cpp.h"
@@ -7528,23 +7529,44 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
};
}
res = new llama_memory_hybrid(
/* model */ *this,
/* attn_type_k */ params.type_k,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_kv_size */ cparams.n_ctx,
/* attn_n_pad */ 1,
/* attn_n_swa */ hparams.n_swa,
/* attn_swa_type */ hparams.swa_type,
/* recurrent_type_k */ GGML_TYPE_F32,
/* recurrent_type_v */ GGML_TYPE_F32,
/* recurrent_kv_size */ std::max((uint32_t) 1, cparams.n_seq_max),
/* n_seq_max */ cparams.n_seq_max,
/* offload */ cparams.offload_kqv,
/* unified */ cparams.kv_unified,
/* filter_attn */ std::move(filter_attn),
/* filter_recr */ std::move(filter_recr));
if (hparams.swa_type != LLAMA_SWA_TYPE_NONE) {
// Use hybrid-iswa for hybrid models with SWA
res = new llama_memory_hybrid_iswa(
/* model */ *this,
/* attn_type_k */ params.type_k,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_swa_full */ params.swa_full,
/* attn_kv_size */ cparams.n_ctx,
/* attn_n_ubatch */ cparams.n_ubatch,
/* attn_n_pad */ 1,
/* recurrent_type_r */ GGML_TYPE_F32,
/* recurrent_type_s */ GGML_TYPE_F32,
/* recurrent_rs_size */ std::max((uint32_t) 1, cparams.n_seq_max),
/* n_seq_max */ cparams.n_seq_max,
/* offload */ cparams.offload_kqv,
/* unified */ cparams.kv_unified,
/* filter_attn */ std::move(filter_attn),
/* filter_recr */ std::move(filter_recr));
} else {
res = new llama_memory_hybrid(
/* model */ *this,
/* attn_type_k */ params.type_k,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_kv_size */ cparams.n_ctx,
/* attn_n_pad */ 1,
/* attn_n_swa */ hparams.n_swa,
/* attn_swa_type */ hparams.swa_type,
/* recurrent_type_k */ GGML_TYPE_F32,
/* recurrent_type_v */ GGML_TYPE_F32,
/* recurrent_kv_size */ std::max((uint32_t) 1, cparams.n_seq_max),
/* n_seq_max */ cparams.n_seq_max,
/* offload */ cparams.offload_kqv,
/* unified */ cparams.kv_unified,
/* filter_attn */ std::move(filter_attn),
/* filter_recr */ std::move(filter_recr));
}
} else {
llama_memory_i::layer_reuse_cb reuse = nullptr;