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memory : rename interface to llama_memory_context_i (#14296)

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* memory : rename interface to llama_memory_context_i

ggml-ci

* cont : fix comments

* cont : use "mctx" for referencing a memory context

ggml-ci
This commit is contained in:
Georgi Gerganov
2025-06-21 08:03:46 +03:00
committed by GitHub
parent b23fa0b3f4
commit 692e3cdd0a
14 changed files with 339 additions and 341 deletions
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70
src/llama-memory-hybrid.cpp
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@@ -56,7 +56,7 @@ llama_memory_hybrid::llama_memory_hybrid(
n_seq_max
)) {}
llama_memory_state_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & balloc, uint32_t n_ubatch, bool embd_all) {
llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & balloc, uint32_t n_ubatch, bool embd_all) {
do {
balloc.split_reset();
@@ -82,31 +82,31 @@ llama_memory_state_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & ball
// prepare the recurrent batches first
if (!mem_recr->prepare(ubatches)) {
// TODO: will the recurrent cache be in an undefined state at this point?
// TODO: will the recurrent cache be in an undefined context at this point?
LLAMA_LOG_ERROR("%s: failed to prepare recurrent ubatches\n", __func__);
return std::make_unique<llama_memory_hybrid_state>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
return std::make_unique<llama_memory_hybrid_context>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
}
// prepare the attention cache
auto heads_attn = mem_attn->prepare(ubatches);
if (heads_attn.empty()) {
LLAMA_LOG_ERROR("%s: failed to prepare attention ubatches\n", __func__);
return std::make_unique<llama_memory_hybrid_state>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
return std::make_unique<llama_memory_hybrid_context>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
}
return std::make_unique<llama_memory_hybrid_state>(
return std::make_unique<llama_memory_hybrid_context>(
this, std::move(heads_attn), std::move(ubatches));
} while(false);
return std::make_unique<llama_memory_hybrid_state>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
return std::make_unique<llama_memory_hybrid_context>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
}
llama_memory_state_ptr llama_memory_hybrid::init_full() {
return std::make_unique<llama_memory_hybrid_state>(this);
llama_memory_context_ptr llama_memory_hybrid::init_full() {
return std::make_unique<llama_memory_hybrid_context>(this);
}
llama_memory_state_ptr llama_memory_hybrid::init_update(llama_context * lctx, bool optimize) {
return std::make_unique<llama_memory_hybrid_state>(this, lctx, optimize);
llama_memory_context_ptr llama_memory_hybrid::init_update(llama_context * lctx, bool optimize) {
return std::make_unique<llama_memory_hybrid_context>(this, lctx, optimize);
}
bool llama_memory_hybrid::get_can_shift() const {
@@ -176,39 +176,39 @@ llama_memory_recurrent * llama_memory_hybrid::get_mem_recr() const {
return mem_recr.get();
}
llama_memory_hybrid_state::llama_memory_hybrid_state(llama_memory_status status) : status(status) {}
llama_memory_hybrid_context::llama_memory_hybrid_context(llama_memory_status status) : status(status) {}
llama_memory_hybrid_state::llama_memory_hybrid_state(llama_memory_hybrid * mem) :
state_attn(mem->get_mem_attn()->init_full()),
state_recr(mem->get_mem_recr()->init_full()),
status(llama_memory_status_combine(state_attn->get_status(), state_recr->get_status())) {
llama_memory_hybrid_context::llama_memory_hybrid_context(llama_memory_hybrid * mem) :
ctx_attn(mem->get_mem_attn()->init_full()),
ctx_recr(mem->get_mem_recr()->init_full()),
status(llama_memory_status_combine(ctx_attn->get_status(), ctx_recr->get_status())) {
}
llama_memory_hybrid_state::llama_memory_hybrid_state(
llama_memory_hybrid_context::llama_memory_hybrid_context(
llama_memory_hybrid * mem,
llama_context * lctx,
bool optimize) :
state_attn(mem->get_mem_attn()->init_update(lctx, optimize)),
state_recr(mem->get_mem_recr()->init_update(lctx, optimize)),
status(llama_memory_status_combine(state_attn->get_status(), state_recr->get_status())) {
ctx_attn(mem->get_mem_attn()->init_update(lctx, optimize)),
ctx_recr(mem->get_mem_recr()->init_update(lctx, optimize)),
status(llama_memory_status_combine(ctx_attn->get_status(), ctx_recr->get_status())) {
}
llama_memory_hybrid_state::llama_memory_hybrid_state(
llama_memory_hybrid_context::llama_memory_hybrid_context(
llama_memory_hybrid * mem,
std::vector<uint32_t> heads_attn,
std::vector<llama_ubatch> ubatches) :
ubatches(std::move(ubatches)),
// note: here we copy the ubatches. not sure if this is ideal
state_attn(new llama_kv_cache_unified_state(mem->get_mem_attn(), std::move(heads_attn), this->ubatches)),
state_recr(new llama_memory_recurrent_state(mem->get_mem_recr(), this->ubatches)),
status(llama_memory_status_combine(state_attn->get_status(), state_recr->get_status())) {
ctx_attn(new llama_kv_cache_unified_context(mem->get_mem_attn(), std::move(heads_attn), this->ubatches)),
ctx_recr(new llama_memory_recurrent_context(mem->get_mem_recr(), this->ubatches)),
status(llama_memory_status_combine(ctx_attn->get_status(), ctx_recr->get_status())) {
}
bool llama_memory_hybrid_state::next() {
bool llama_memory_hybrid_context::next() {
assert(status == LLAMA_MEMORY_STATUS_SUCCESS);
state_attn->next();
state_recr->next();
ctx_attn->next();
ctx_recr->next();
if (++i_next >= ubatches.size()) {
return false;
@@ -217,30 +217,30 @@ bool llama_memory_hybrid_state::next() {
return true;
}
bool llama_memory_hybrid_state::apply() {
bool llama_memory_hybrid_context::apply() {
assert(status == LLAMA_MEMORY_STATUS_SUCCESS);
bool res = true;
res = res & state_attn->apply();
res = res & state_recr->apply();
res = res & ctx_attn->apply();
res = res & ctx_recr->apply();
return res;
}
llama_memory_status llama_memory_hybrid_state::get_status() const {
llama_memory_status llama_memory_hybrid_context::get_status() const {
return status;
}
const llama_ubatch & llama_memory_hybrid_state::get_ubatch() const {
const llama_ubatch & llama_memory_hybrid_context::get_ubatch() const {
assert(status == LLAMA_MEMORY_STATUS_SUCCESS);
return ubatches[i_next];
}
const llama_kv_cache_unified_state * llama_memory_hybrid_state::get_state_attn() const {
return static_cast<const llama_kv_cache_unified_state *>(state_attn.get());
const llama_kv_cache_unified_context * llama_memory_hybrid_context::get_attn() const {
return static_cast<const llama_kv_cache_unified_context *>(ctx_attn.get());
}
const llama_memory_recurrent_state * llama_memory_hybrid_state::get_state_recr() const {
return static_cast<const llama_memory_recurrent_state *>(state_recr.get());
const llama_memory_recurrent_context * llama_memory_hybrid_context::get_recr() const {
return static_cast<const llama_memory_recurrent_context *>(ctx_recr.get());
}