kv-cache : separate recurrent vs non-recurrent impl (#12799)

* kv-cache : serparate recurrent vs non-recurrent impl (wip)

ggml-ci

* kv-cache : init -> contructor + add llama_memory_params

ggml-ci

* kv-cache : fix callback reference

ggml-ci

* context : llama_kv_cache -> llama_memory_i

ggml-ci

* context : move memory creation logic to model

ggml-ci

* llama : remove reference of memory during encode

ggml-ci

* kv-cache : hide padding details in the implementation

ggml-ci

* kv-cache : add ubatch_next()

ggml-ci

* context : simplify sbatch logic

ggml-ci

* kv-cache : hide defrag logic in the implementation

ggml-ci

* context : hide kv cache details in implementation

ggml-ci

* build : fix

ggml-ci

* cont : another fix

ggml-ci

* kv-cache : simplify interface (wip)

ggml-ci

* kv-cache : use separate KV cell structs for unified/recurrent

ggml-ci

* kv-cache : clean-up

ggml-ci

* model : better llama_model::create_model() signature

ggml-ci

* kv-cache : fix recurrent seq_rm()

ggml-ci

* kv-cache : replace `struct callbacks` with `llama_model &`

ggml-ci

* kv-cache : replace `struct graph_params` with `llama_context &`

ggml-ci

* kv-cache : fix offload check

ggml-ci

* context : avoid passing unique_ptr

ggml-ci

* kv-cache : avoid using the backends from the llama_context

ref #13113

ggml-ci

* kv-cache : more consistent debug logs [no ci]

* kv-cache : do not pass the full llama_context for kv graphs

ggml-ci

* kv-cache : remove comment

* kv-cache : ggml_rope_ext_inplace -> ggml_rope_ext

ggml-ci

* kv-cache : fix recurrent multi-user case

ggml-ci

* memory : remove comments [no ci]

Author: ggerganov

src/llama-batch.cpp

@@ -189,7 +189,7 @@ llama_ubatch llama_sbatch::split_seq(size_t n_ubatch) {
     return ubatch;
 }
 
-void llama_sbatch::from_batch(const llama_batch & batch, size_t n_embd, bool simple_split, bool logits_all) {
+llama_sbatch::llama_sbatch(const llama_batch & batch, size_t n_embd, bool simple_split, bool logits_all) {
     GGML_ASSERT(batch.n_tokens >= 0);
     this->batch = &batch;
     this->n_embd = n_embd;
@@ -203,6 +203,7 @@ void llama_sbatch::from_batch(const llama_batch & batch, size_t n_embd, bool sim
     for (size_t i = 0; i < n_tokens; ++i) {
         ids[i] = i;
     }
+
     if (simple_split) {
         seq.resize(1);
         llama_sbatch_seq & s = seq[0];
@@ -212,6 +213,7 @@ void llama_sbatch::from_batch(const llama_batch & batch, size_t n_embd, bool sim
         s.length = n_tokens;
         return;
     }
+
     std::sort(ids.begin(), ids.end(),
             [&batch](size_t a, size_t b) {
                 int32_t n_seq_a = batch.n_seq_id ? batch.n_seq_id[a] : 1;
@@ -239,6 +241,7 @@ void llama_sbatch::from_batch(const llama_batch & batch, size_t n_embd, bool sim
                 return n_seq_a > n_seq_b;
             }
     );
+
     // init seq
     llama_sbatch_seq * last_seq = nullptr;
 
@@ -262,6 +265,7 @@ void llama_sbatch::from_batch(const llama_batch & batch, size_t n_embd, bool sim
         seq.push_back(new_seq);
         last_seq = &seq.back();
     }
+
     // keep shared prompts first at the end, then sort by length descending.
     std::sort(seq.begin(), seq.end(),
             [](llama_sbatch_seq & a, llama_sbatch_seq & b) {

src/llama-batch.h

@@ -70,7 +70,8 @@ struct llama_sbatch {
     // sequence-wise split
     llama_ubatch split_seq(size_t n_ubatch);
 
-    void from_batch(const llama_batch & batch, size_t n_embd, bool simple_split = false, bool logits_all = false);
+    llama_sbatch() = default;
+    llama_sbatch(const llama_batch & batch, size_t n_embd, bool simple_split = false, bool logits_all = false);
 };
 
 // temporary allocate memory for the input batch if needed