ver4a/llama.cpp
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llama : refactor llama_context, llama_kv_cache, llm_build_context (#12181)

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* llama : refactor llama_context, llama_kv_cache, llm_build_context

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* graph : don't mutate the KV cache during defrag

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* context : reduce virtuals + remove test function

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* context : move interface implementation to source file + factory

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* graph : move KV cache build functions to llama_context impl

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* graph : remove model reference from build_pooling

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* graph : remove llama_model reference

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* kv_cache : provide rope factors

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* graph : rework inputs to use only unique_ptr, remove attn input abstraction

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* context : remove llama_context_i abstraction

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* context : clean-up

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* graph : clean-up

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* llama : remove redundant keywords (struct, enum)

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* model : adapt gemma3

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* graph : restore same attention ops as on master

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* llama : remove TODO + fix indent

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This commit is contained in:
Georgi Gerganov 2025-03-13 12:35:44 +02:00 • committed by GitHub
parent 2048b5913d
commit e0dbec0bc6
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46 changed files with 13903 additions and 12190 deletions
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4
examples/run/run.cpp
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@ -891,7 +891,7 @@ static int apply_chat_template(const struct common_chat_templates * tmpls, Llama
// Function to tokenize the prompt
static int tokenize_prompt(const llama_vocab * vocab, const std::string & prompt,
std::vector<llama_token> & prompt_tokens, const LlamaData & llama_data) {
const bool is_first = llama_get_kv_cache_used_cells(llama_data.context.get()) == 0;
const bool is_first = llama_kv_self_used_cells(llama_data.context.get()) == 0;
const int n_prompt_tokens = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, is_first, true);
prompt_tokens.resize(n_prompt_tokens);
@ -907,7 +907,7 @@ static int tokenize_prompt(const llama_vocab * vocab, const std::string & prompt
// Check if we have enough space in the context to evaluate this batch
static int check_context_size(const llama_context_ptr & ctx, const llama_batch & batch) {
const int n_ctx = llama_n_ctx(ctx.get());
const int n_ctx_used = llama_get_kv_cache_used_cells(ctx.get());
const int n_ctx_used = llama_kv_self_used_cells(ctx.get());
if (n_ctx_used + batch.n_tokens > n_ctx) {
printf(LOG_COL_DEFAULT "\n");
printe("context size exceeded\n");