Commit 7a2e5aba9 for llama.cpp
commit 7a2e5aba905126be2de919dd5dd9f1491a893a73
Author: Georgi Gerganov <ggerganov@gmail.com>
Date: Tue Oct 27 07:53:44 2026 +0200
llama : remove obsolete n_pad from memory instances (#31200)
Every caller passes n_pad = 1 and the only two users clamp it to 256.
Drop the parameter, the members and the trivially true kv_size assert.
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
diff --git a/src/llama-kv-cache-dsa-iswa.cpp b/src/llama-kv-cache-dsa-iswa.cpp
index 02d14a344..3d91228f3 100644
--- a/src/llama-kv-cache-dsa-iswa.cpp
+++ b/src/llama-kv-cache-dsa-iswa.cpp
@@ -23,7 +23,6 @@ llama_kv_cache_dsa_iswa::llama_kv_cache_dsa_iswa(
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
const layer_filter_cb & filter_mla,
const layer_filter_cb & filter_lid,
const layer_reuse_cb & reuse) : unified(unified) {
@@ -65,14 +64,14 @@ llama_kv_cache_dsa_iswa::llama_kv_cache_dsa_iswa(
kv_dsa = std::make_unique<llama_kv_cache_dsa>(
model, no_alloc, type_k, type_v,
- v_trans, offload, unified, size_dsa, n_seq_max, n_pad,
+ v_trans, offload, unified, size_dsa, n_seq_max,
0, LLAMA_SWA_TYPE_NONE, filter_dsa, filter_lid, reuse);
LLAMA_LOG_INFO("%s: creating SWA KV cache, size = %u cells\n", __func__, size_swa);
kv_swa = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams, type_k, type_v,
- v_trans, offload, unified, size_swa, n_seq_max, n_pad,
+ v_trans, offload, unified, size_swa, n_seq_max,
hparams.n_swa, hparams.swa_type, nullptr, filter_swa, reuse, nullptr);
}
diff --git a/src/llama-kv-cache-dsa-iswa.h b/src/llama-kv-cache-dsa-iswa.h
index 1aae269da..73fbaa7df 100644
--- a/src/llama-kv-cache-dsa-iswa.h
+++ b/src/llama-kv-cache-dsa-iswa.h
@@ -24,7 +24,6 @@ public:
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
const layer_filter_cb & filter_mla,
const layer_filter_cb & filter_lid,
const layer_reuse_cb & reuse);
diff --git a/src/llama-kv-cache-dsa.cpp b/src/llama-kv-cache-dsa.cpp
index 307ff31dd..2602ae3c3 100644
--- a/src/llama-kv-cache-dsa.cpp
+++ b/src/llama-kv-cache-dsa.cpp
@@ -21,7 +21,6 @@ llama_kv_cache_dsa::llama_kv_cache_dsa(
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
const layer_filter_cb & filter_mla,
@@ -33,7 +32,7 @@ llama_kv_cache_dsa::llama_kv_cache_dsa(
kv_mla = std::make_unique<llama_kv_cache>(
model, no_alloc, model.hparams, type_k, type_v,
- v_trans, offload, unified, kv_size, n_seq_max, n_pad,
+ v_trans, offload, unified, kv_size, n_seq_max,
n_swa, swa_type, nullptr, filter_mla, reuse, nullptr);
// we use llama_kv_cache for caching indexer keys
@@ -50,7 +49,7 @@ llama_kv_cache_dsa::llama_kv_cache_dsa(
kv_lid = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams_lid, type_k, type_v,
- v_trans, offload, unified, kv_size, n_seq_max, n_pad,
+ v_trans, offload, unified, kv_size, n_seq_max,
n_swa, swa_type, nullptr, filter_lid, reuse, nullptr);
}
diff --git a/src/llama-kv-cache-dsa.h b/src/llama-kv-cache-dsa.h
index 584ab40b9..13a59047c 100644
--- a/src/llama-kv-cache-dsa.h
+++ b/src/llama-kv-cache-dsa.h
@@ -24,7 +24,6 @@ public:
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
const layer_filter_cb & filter_mla,
diff --git a/src/llama-kv-cache-dsv4.cpp b/src/llama-kv-cache-dsv4.cpp
index 70bfee8f9..f0ab9f35d 100644
--- a/src/llama-kv-cache-dsv4.cpp
+++ b/src/llama-kv-cache-dsv4.cpp
@@ -1252,7 +1252,6 @@ llama_kv_cache_dsv4::llama_kv_cache_dsv4(
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
uint32_t n_rs_seq,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse) :
@@ -1288,7 +1287,7 @@ llama_kv_cache_dsv4::llama_kv_cache_dsv4(
kv_raw = std::make_unique<llama_kv_cache_iswa>(
model, no_alloc, hparams_raw, type_k, type_v,
- v_trans, offload, swa_full, unified_raw, kv_size, n_seq_max, n_ubatch, n_pad,
+ v_trans, offload, swa_full, unified_raw, kv_size, n_seq_max, n_ubatch,
nullptr, filter_raw, reuse, nullptr);
// V4.1: CSA slot = ratio 2, HCA slot = ratio 1, no overlap and no indexer compressor; the index K is stored
@@ -1392,7 +1391,7 @@ llama_kv_cache_dsv4::llama_kv_cache_dsv4(
kv_csa = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams_csa, type_k, type_v,
- v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_csa), 256u), n_seq_max, n_pad,
+ v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_csa), 256u), n_seq_max,
0, LLAMA_SWA_TYPE_NONE, nullptr, filter_csa, nullptr, nullptr);
LLAMA_LOG_INFO("%s: creating DSV4 HCA compressed KV cache, size = %u cells\n",
@@ -1400,7 +1399,7 @@ llama_kv_cache_dsv4::llama_kv_cache_dsv4(
kv_hca = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams_hca, type_k, type_v,
- v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_hca), 256u), n_seq_max, n_pad,
+ v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_hca), 256u), n_seq_max,
0, LLAMA_SWA_TYPE_NONE, nullptr, filter_hca, nullptr, nullptr);
LLAMA_LOG_INFO("%s: creating DSV4 lightning-indexer KV cache, size = %u cells\n",
@@ -1408,7 +1407,7 @@ llama_kv_cache_dsv4::llama_kv_cache_dsv4(
kv_lid = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams_lid, type_k, type_v,
- v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_csa), 256u), n_seq_max, n_pad,
+ v_trans, offload, unified_compressed, GGML_PAD(dsv4_comp_size(kv_size, ratio_csa), 256u), n_seq_max,
0, LLAMA_SWA_TYPE_NONE, nullptr, filter_lid, nullptr, nullptr);
LLAMA_LOG_INFO("%s: creating DSV4 CSA compressor state\n", __func__);
diff --git a/src/llama-kv-cache-dsv4.h b/src/llama-kv-cache-dsv4.h
index 3e97c46e2..44bf95955 100644
--- a/src/llama-kv-cache-dsv4.h
+++ b/src/llama-kv-cache-dsv4.h
@@ -101,7 +101,6 @@ public:
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
uint32_t n_rs_seq,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse);
diff --git a/src/llama-kv-cache-iswa.cpp b/src/llama-kv-cache-iswa.cpp
index 4606bcf98..8ce8e0165 100644
--- a/src/llama-kv-cache-iswa.cpp
+++ b/src/llama-kv-cache-iswa.cpp
@@ -23,13 +23,12 @@ llama_kv_cache_iswa::llama_kv_cache_iswa(
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
llama_memory_t mem_other,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse,
const layer_share_cb & share) :
llama_kv_cache_iswa(model, no_alloc, model.hparams, type_k, type_v, v_trans, offload, swa_full, unified,
- kv_size, n_seq_max, n_ubatch, n_pad, mem_other, filter, reuse, share) {
+ kv_size, n_seq_max, n_ubatch, mem_other, filter, reuse, share) {
}
llama_kv_cache_iswa::llama_kv_cache_iswa(
@@ -45,7 +44,6 @@ llama_kv_cache_iswa::llama_kv_cache_iswa(
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
llama_memory_t mem_other,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse,
@@ -96,14 +94,14 @@ llama_kv_cache_iswa::llama_kv_cache_iswa(
kv_base = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams, type_k, type_v,
- v_trans, offload, unified, size_base, n_seq_max, n_pad,
+ v_trans, offload, unified, size_base, n_seq_max,
0, LLAMA_SWA_TYPE_NONE, mem_other_base, filter_base, reuse, share);
LLAMA_LOG_INFO("%s: creating SWA KV cache, size = %u cells\n", __func__, size_swa);
kv_swa = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams, type_k, type_v,
- v_trans, offload, unified, size_swa, n_seq_max, n_pad,
+ v_trans, offload, unified, size_swa, n_seq_max,
hparams.n_swa, hparams.swa_type, mem_other_swa, filter_swa, reuse, share);
}
diff --git a/src/llama-kv-cache-iswa.h b/src/llama-kv-cache-iswa.h
index 8352669dd..65aba2af7 100644
--- a/src/llama-kv-cache-iswa.h
+++ b/src/llama-kv-cache-iswa.h
@@ -25,7 +25,6 @@ public:
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
llama_memory_t mem_other,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse,
@@ -44,7 +43,6 @@ public:
uint32_t kv_size,
uint32_t n_seq_max,
uint32_t n_ubatch,
- uint32_t n_pad,
llama_memory_t mem_other,
const layer_filter_cb & filter,
const layer_reuse_cb & reuse,
diff --git a/src/llama-kv-cache-msa.cpp b/src/llama-kv-cache-msa.cpp
index a57937ff4..2d6bac0cb 100644
--- a/src/llama-kv-cache-msa.cpp
+++ b/src/llama-kv-cache-msa.cpp
@@ -20,21 +20,20 @@ llama_kv_cache_msa::llama_kv_cache_msa(
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
const layer_filter_cb & filter,
const layer_filter_cb & filter_idx,
const layer_reuse_cb & reuse) :
hparams_idx(model.hparams),
- n_stream(unified ? 1 : n_seq_max), n_seq_max(n_seq_max), n_pad(n_pad),
+ n_stream(unified ? 1 : n_seq_max), n_seq_max(n_seq_max),
n_swa(n_swa), swa_type(swa_type) {
LLAMA_LOG_INFO("%s: creating main KV cache, size = %u cells\n", __func__, kv_size);
kv_base = std::make_unique<llama_kv_cache>(
model, no_alloc, model.hparams, type_k, type_v,
- v_trans, offload, unified, kv_size, n_seq_max, n_pad,
+ v_trans, offload, unified, kv_size, n_seq_max,
n_swa, swa_type, nullptr, filter, reuse, nullptr);
// the MSA indexer uses a single key head per layer
@@ -46,7 +45,7 @@ llama_kv_cache_msa::llama_kv_cache_msa(
kv_idx = std::make_unique<llama_kv_cache>(
model, no_alloc, hparams_idx, type_k, type_v,
- v_trans, offload, unified, kv_size, n_seq_max, n_pad,
+ v_trans, offload, unified, kv_size, n_seq_max,
n_swa, swa_type, nullptr, filter_idx, reuse, nullptr);
}
@@ -262,7 +261,7 @@ const llama_kv_cache_context * llama_kv_cache_msa_context::get_idx() const {
uint32_t llama_kv_cache_msa_context::get_n_pos() const {
// pad the value so that the graph remains constant across batches and can be reused
- const uint32_t n_pad_cur = std::max(kv->get_n_pad(), 256u);
+ const uint32_t n_pad = 256;
llama_pos pos_max = -1;
@@ -270,7 +269,7 @@ uint32_t llama_kv_cache_msa_context::get_n_pos() const {
pos_max = std::max(pos_max, kv->seq_pos_max(seq_id));
}
- return std::max(n_pad_cur, GGML_PAD((uint32_t) (pos_max + 1), n_pad_cur));
+ return std::max(n_pad, GGML_PAD((uint32_t) (pos_max + 1), n_pad));
}
void llama_kv_cache_msa_context::set_input_cell_pos(ggml_tensor * dst, const llama_ubatch * ubatch, int32_t div) const {
diff --git a/src/llama-kv-cache-msa.h b/src/llama-kv-cache-msa.h
index 3b1477c83..81c6827f3 100644
--- a/src/llama-kv-cache-msa.h
+++ b/src/llama-kv-cache-msa.h
@@ -23,7 +23,6 @@ public:
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
const layer_filter_cb & filter,
@@ -68,7 +67,6 @@ public:
llama_kv_cache * get_base() const;
llama_kv_cache * get_idx () const;
- uint32_t get_n_pad() const { return n_pad; }
uint32_t get_n_seq_max() const { return n_seq_max; }
uint32_t get_n_swa() const { return n_swa; }
llama_swa_type get_swa_type() const { return swa_type; }
@@ -79,7 +77,6 @@ private:
const uint32_t n_stream = 1;
const uint32_t n_seq_max = 1;
- const uint32_t n_pad = 1;
const uint32_t n_swa = 0;
const llama_swa_type swa_type = LLAMA_SWA_TYPE_NONE;
diff --git a/src/llama-kv-cache.cpp b/src/llama-kv-cache.cpp
index 61b5cb370..e108f0423 100644
--- a/src/llama-kv-cache.cpp
+++ b/src/llama-kv-cache.cpp
@@ -73,7 +73,6 @@ llama_kv_cache::llama_kv_cache(
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
llama_memory_t mem_other,
@@ -82,7 +81,7 @@ llama_kv_cache::llama_kv_cache(
const layer_share_cb & share,
const char * name_tag) :
model(model), hparams(hparams), v_trans(v_trans),
- n_seq_max(n_seq_max), n_stream(unified ? 1 : n_seq_max), n_pad(n_pad), n_swa(n_swa), swa_type(swa_type),
+ n_seq_max(n_seq_max), n_stream(unified ? 1 : n_seq_max), n_swa(n_swa), swa_type(swa_type),
ctxs_bufs(no_alloc),
other(static_cast<llama_kv_cache *>(mem_other)),
v_cells_impl(other ? other->v_cells_impl : std::make_shared<llama_kv_cells_vec>()),
@@ -99,8 +98,6 @@ llama_kv_cache::llama_kv_cache(
}
}
- GGML_ASSERT(kv_size % n_pad == 0);
-
const uint32_t n_layer = hparams.n_layer_all;
// define a comparator for the buft -> ctx map to ensure that the order is well-defined:
@@ -1260,12 +1257,12 @@ uint32_t llama_kv_cache::get_n_kv(const slot_info & sinfo) const {
// pad the n_kv value so that the graph remains constant across batches and can be reused
// note: this also helps some backends with performance (f.ex https://github.com/ggml-org/llama.cpp/pull/16812#issuecomment-3455112220)
- const uint32_t n_pad_cur = std::max(n_pad, 256u);
+ const uint32_t n_pad = 256;
for (uint32_t s = 0; s < sinfo.n_stream(); ++s) {
const auto & cells = v_cells[sinfo.strm[s]];
- result = std::max(std::min(cells.size(), std::max(n_pad_cur, GGML_PAD(cells.used_max_p1(), n_pad_cur))), result);
+ result = std::max(std::min(cells.size(), std::max(n_pad, GGML_PAD(cells.used_max_p1(), n_pad))), result);
}
return result;
diff --git a/src/llama-kv-cache.h b/src/llama-kv-cache.h
index b31cc226d..60d2e183c 100644
--- a/src/llama-kv-cache.h
+++ b/src/llama-kv-cache.h
@@ -107,7 +107,6 @@ public:
bool unified,
uint32_t kv_size,
uint32_t n_seq_max,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
llama_memory_t mem_other,
@@ -272,9 +271,6 @@ private:
const uint32_t n_seq_max = 1;
const uint32_t n_stream = 1;
- // required padding
- const uint32_t n_pad = 1;
-
// SWA
const uint32_t n_swa = 0;
diff --git a/src/llama-memory-hybrid-idx.cpp b/src/llama-memory-hybrid-idx.cpp
index 03f0c342d..da1747649 100644
--- a/src/llama-memory-hybrid-idx.cpp
+++ b/src/llama-memory-hybrid-idx.cpp
@@ -24,7 +24,6 @@ llama_memory_hybrid_idx::llama_memory_hybrid_idx(
ggml_type type_v,
bool v_trans,
uint32_t kv_size,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
/* recurrent */
@@ -43,7 +42,7 @@ llama_memory_hybrid_idx::llama_memory_hybrid_idx(
llama_memory_hybrid(
model,
no_alloc,
- type_k, type_v, v_trans, kv_size, n_pad, n_swa, swa_type,
+ type_k, type_v, v_trans, kv_size, n_swa, swa_type,
type_r, type_s, rs_size,
n_seq_max, n_rs_seq, offload, unified,
filter_attn, filter_recr),
@@ -67,7 +66,7 @@ llama_memory_hybrid_idx::llama_memory_hybrid_idx(
return new llama_kv_cache(
model, no_alloc, hparams_idx, type_k, type_v, v_trans, offload, unified,
- kv_size, n_seq_max, n_pad, n_swa, swa_type,
+ kv_size, n_seq_max, n_swa, swa_type,
nullptr, filter_idx, nullptr, nullptr, "idx_");
}()) {}
diff --git a/src/llama-memory-hybrid-idx.h b/src/llama-memory-hybrid-idx.h
index faa1724b0..59940dbb8 100644
--- a/src/llama-memory-hybrid-idx.h
+++ b/src/llama-memory-hybrid-idx.h
@@ -24,7 +24,6 @@ public:
ggml_type type_v,
bool v_trans,
uint32_t kv_size,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
/* recurrent */
diff --git a/src/llama-memory-hybrid-iswa.cpp b/src/llama-memory-hybrid-iswa.cpp
index 4c0f14c22..6d843c76e 100644
--- a/src/llama-memory-hybrid-iswa.cpp
+++ b/src/llama-memory-hybrid-iswa.cpp
@@ -18,7 +18,6 @@ llama_memory_hybrid_iswa::llama_memory_hybrid_iswa(
bool swa_full,
uint32_t kv_size,
uint32_t n_ubatch,
- uint32_t n_pad,
/* recurrent */
ggml_type type_r,
ggml_type type_s,
@@ -44,7 +43,6 @@ llama_memory_hybrid_iswa::llama_memory_hybrid_iswa(
kv_size,
n_seq_max,
n_ubatch,
- n_pad,
nullptr,
filter_attn == nullptr ?
[&](int32_t il) { return !hparams.is_recr(il); }
diff --git a/src/llama-memory-hybrid-iswa.h b/src/llama-memory-hybrid-iswa.h
index 6e68f3f44..52c885ac9 100644
--- a/src/llama-memory-hybrid-iswa.h
+++ b/src/llama-memory-hybrid-iswa.h
@@ -28,7 +28,6 @@ public:
bool swa_full,
uint32_t kv_size,
uint32_t n_ubatch,
- uint32_t n_pad,
/* recurrent */
ggml_type type_r,
ggml_type type_s,
diff --git a/src/llama-memory-hybrid.cpp b/src/llama-memory-hybrid.cpp
index 0361b23ca..7d3b27908 100644
--- a/src/llama-memory-hybrid.cpp
+++ b/src/llama-memory-hybrid.cpp
@@ -16,7 +16,6 @@ llama_memory_hybrid::llama_memory_hybrid(
ggml_type type_v,
bool v_trans,
uint32_t kv_size,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
/* recurrent */
@@ -43,7 +42,6 @@ llama_memory_hybrid::llama_memory_hybrid(
unified,
kv_size,
n_seq_max,
- n_pad,
n_swa,
swa_type,
nullptr,
diff --git a/src/llama-memory-hybrid.h b/src/llama-memory-hybrid.h
index 74fa89ea6..2b4d1269c 100644
--- a/src/llama-memory-hybrid.h
+++ b/src/llama-memory-hybrid.h
@@ -26,7 +26,6 @@ public:
ggml_type type_v,
bool v_trans,
uint32_t kv_size,
- uint32_t n_pad,
uint32_t n_swa,
llama_swa_type swa_type,
/* recurrent */
diff --git a/src/llama-model.cpp b/src/llama-model.cpp
index 78a387e5d..0220c5ab8 100644
--- a/src/llama-model.cpp
+++ b/src/llama-model.cpp
@@ -2842,7 +2842,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,
@@ -2870,7 +2869,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,
@@ -2896,7 +2894,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
filter_mla,
@@ -2935,7 +2932,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_kv_size */ cparams.n_ctx_seq,
- /* attn_n_pad */ 1,
/* attn_n_swa */ hparams.n_swa,
/* attn_swa_type */ hparams.swa_type,
/* recurrent_type_r */ GGML_TYPE_F32,
@@ -2964,7 +2960,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,
@@ -2985,7 +2980,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,
@@ -3013,7 +3007,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,
@@ -3040,7 +3033,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
filter_mla,
filter_lid,
nullptr);
@@ -3068,7 +3060,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
nullptr,
filter_mtp,
nullptr,
@@ -3086,7 +3077,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
cparams.n_rs_seq,
nullptr,
nullptr);
@@ -3110,7 +3100,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
nullptr,
nullptr,
nullptr,
@@ -3198,7 +3187,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
/* attn_swa_full */ params.swa_full,
/* attn_kv_size */ cparams.n_ctx_seq,
/* 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),
@@ -3217,7 +3205,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_kv_size */ cparams.n_ctx_seq,
- /* attn_n_pad */ 1,
/* attn_n_swa */ hparams.n_swa,
/* attn_swa_type */ hparams.swa_type,
/* recurrent_type_k */ GGML_TYPE_F32,
@@ -3238,7 +3225,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
/* attn_type_v */ params.type_v,
/* attn_v_trans */ !cparams.flash_attn,
/* attn_kv_size */ cparams.n_ctx_seq,
- /* attn_n_pad */ 1,
/* attn_n_swa */ hparams.n_swa,
/* attn_swa_type */ hparams.swa_type,
/* recurrent_type_k */ GGML_TYPE_F32,
@@ -3310,7 +3296,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
mem_other,
filter,
reuse,
@@ -3328,7 +3313,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.n_ctx_seq,
cparams.n_seq_max,
cparams.n_ubatch,
- 1,
nullptr,
filter,
reuse,
@@ -3348,7 +3332,6 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
cparams.kv_unified,
cparams.n_ctx_seq,
cparams.n_seq_max,
- 1,
hparams.n_swa,
hparams.swa_type,
nullptr,