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llama : refactor llama_model_quantize_params to expose a pure C interface (#20346)

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* Refactor llama_model_quantize_params to expose a pure C interface

* Restore comment and cleanup struct def

* Code review refactoring

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

* Code review refactoring

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Ed Addario
2026-04-01 06:43:00 +01:00
committed by GitHub
parent 82764c341a
commit 4951250235
3 changed files with 66 additions and 50 deletions
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src/llama-quant.cpp
+22 -25
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@@ -84,7 +84,6 @@ static std::string remap_imatrix(const std::string & orig_name, const std::map<i
for (const auto & p : mapped) {
if (p.second == blk) {
LLAMA_LOG_DEBUG("(blk.%d imatrix) ", p.first);
return new_name.replace(match.position(1), match.length(1), std::to_string(p.first));
}
}
@@ -188,10 +187,9 @@ struct quantize_state_impl {
model(model), params(params)
{
// compile regex patterns once - they are expensive
if (params->tensor_types) {
const auto & tensor_types = *static_cast<const std::vector<tensor_type_option> *>(params->tensor_types);
for (const auto & [tname, qtype] : tensor_types) {
tensor_type_patterns.emplace_back(std::regex(tname), qtype);
if (params->tt_overrides) {
for (const auto * p = params->tt_overrides; p->pattern != nullptr; p++) {
tensor_type_patterns.emplace_back(std::regex(p->pattern), p->type);
}
}
}
@@ -857,12 +855,7 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
constexpr bool use_mmap = false;
#endif
llama_model_kv_override * kv_overrides = nullptr;
if (params->kv_overrides) {
auto * v = (std::vector<llama_model_kv_override>*)params->kv_overrides;
kv_overrides = v->data();
}
const llama_model_kv_override * kv_overrides = params->kv_overrides;
std::vector<std::string> splits = {};
llama_model_loader ml(/*metadata*/ nullptr, /*set_tensor_data*/ nullptr, /*set_tensor_data_ud*/ nullptr,
fname_inp, splits, /*file*/ nullptr, use_mmap, /*use_direct_io*/ false, /*check_tensors*/ true, /*no_alloc*/ false, kv_overrides, nullptr);
@@ -879,9 +872,13 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
if (params->only_copy) {
ftype = ml.ftype;
}
std::unordered_map<std::string, std::vector<float>> i_data;
const std::unordered_map<std::string, std::vector<float>> * imatrix_data = nullptr;
if (params->imatrix) {
imatrix_data = static_cast<const std::unordered_map<std::string, std::vector<float>>*>(params->imatrix);
for (const llama_model_imatrix_data * p = params->imatrix; p->name != nullptr; p++) {
i_data.emplace(p->name, std::vector<float>(p->data, p->data + p->size));
}
imatrix_data = & i_data;
if (imatrix_data) {
LLAMA_LOG_INFO("\n%s: have importance matrix data with %d entries\n",
__func__, (int)imatrix_data->size());
@@ -902,7 +899,9 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
std::vector<int> prune_list = {};
if (params->prune_layers) {
prune_list = *static_cast<const std::vector<int> *>(params->prune_layers);
for (const int32_t * p = params->prune_layers; * p != -1; p++) {
prune_list.push_back(* p);
}
}
// copy the KV pairs from the input file
@@ -916,20 +915,18 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
gguf_remove_key(ctx_out.get(), ml.llm_kv(LLM_KV_SPLIT_TENSORS_COUNT).c_str());
if (params->kv_overrides) {
const std::vector<llama_model_kv_override> & overrides = *(const std::vector<llama_model_kv_override> *)params->kv_overrides;
for (const auto & o : overrides) {
if (o.key[0] == 0) break;
if (o.tag == LLAMA_KV_OVERRIDE_TYPE_FLOAT) {
gguf_set_val_f32(ctx_out.get(), o.key, o.val_f64);
} else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_INT) {
for (const llama_model_kv_override * o = params->kv_overrides; o->key[0] != 0; ++o) {
if (o->tag == LLAMA_KV_OVERRIDE_TYPE_FLOAT) {
gguf_set_val_f32(ctx_out.get(), o->key, o->val_f64);
} else if (o->tag == LLAMA_KV_OVERRIDE_TYPE_INT) {
// Setting type to UINT32. See https://github.com/ggml-org/llama.cpp/pull/14182 for context
gguf_set_val_u32(ctx_out.get(), o.key, (uint32_t)std::abs(o.val_i64));
} else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_BOOL) {
gguf_set_val_bool(ctx_out.get(), o.key, o.val_bool);
} else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_STR) {
gguf_set_val_str(ctx_out.get(), o.key, o.val_str);
gguf_set_val_u32(ctx_out.get(), o->key, (uint32_t)std::abs(o->val_i64));
} else if (o->tag == LLAMA_KV_OVERRIDE_TYPE_BOOL) {
gguf_set_val_bool(ctx_out.get(), o->key, o->val_bool);
} else if (o->tag == LLAMA_KV_OVERRIDE_TYPE_STR) {
gguf_set_val_str(ctx_out.get(), o->key, o->val_str);
} else {
LLAMA_LOG_WARN("%s: unknown KV override type for key %s\n", __func__, o.key);
LLAMA_LOG_WARN("%s: unknown KV override type for key %s\n", __func__, o->key);
}
}
}