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llama: fix llama-model-saver (#20503)

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* llama : add fd-based model loading via llama_model_load_from_fd

* llama : address review feedback for fd-based model loading

* llama : use FILE pointer instead of fd in public API

* llama : use FILE pointer consistently, address review feedback

* fixup

* fix tensor names

* fix llama-model-saver

* roundtrip tests

* fixup

* refactor tests

* fix prints

* fix model saving

* fix CI, disable Chameleon

* print seed

---------

Co-authored-by: Siddhesh2377 <siddheshsonar2377@gmail.com>
This commit is contained in:
Johannes Gäßler 2026-03-25 11:53:16 +01:00 • committed by GitHub
parent 69e0ecef06
commit 36dafba5c4
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GPG key ID: B5690EEEBB952194
16 changed files with 338 additions and 99 deletions
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33
src/llama-model-loader.cpp
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@ -511,6 +511,7 @@ llama_model_loader::llama_model_loader(
void * set_tensor_data_ud,
const std::string & fname,
std::vector<std::string> & splits,
FILE * file,
bool use_mmap,
bool use_direct_io,
bool check_tensors,
@ -658,6 +659,36 @@ llama_model_loader::llama_model_loader(
LLAMA_LOG_INFO("%s: additional %d GGUFs metadata loaded.\n", __func__, n_split - 1);
}
} else if (file != nullptr) {
struct ggml_context * ctx = NULL;
struct gguf_init_params params = {
/*.no_alloc = */ true,
/*.ctx = */ &ctx,
};
metadata_ptr.reset(gguf_init_from_file_ptr(file, params));
metadata = metadata_ptr.get();
if (metadata == nullptr) {
throw std::runtime_error(format("%s: failed to load model from file pointer", __func__));
}
get_key(llm_kv(LLM_KV_GENERAL_ARCHITECTURE), arch_name, false);
llm_kv = LLM_KV(llm_arch_from_string(arch_name));
files.emplace_back(new llama_file(file));
contexts.emplace_back(ctx);
// Save tensors data offset info of the main file.
for (ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) {
std::string tensor_name = std::string(cur->name);
// make sure there is no duplicated tensor names
if (weights_map.find(tensor_name) != weights_map.end()) {
throw std::runtime_error(format("invalid model: tensor '%s' is duplicated", ggml_get_name(cur)));
}
n_elements += ggml_nelements(cur);
n_bytes += ggml_nbytes(cur);
weights_map.emplace(tensor_name, llama_tensor_weight(files.back().get(), 0, metadata, cur));
}
} else {
get_key(llm_kv(LLM_KV_GENERAL_ARCHITECTURE), arch_name, false);
llm_kv = LLM_KV(llm_arch_from_string(arch_name));
@ -669,7 +700,7 @@ llama_model_loader::llama_model_loader(
fver = (enum llama_fver) gguf_get_version(metadata);
LLAMA_LOG_INFO("%s: loaded meta data with %d key-value pairs and %d tensors from %s (version %s)\n",
__func__, n_kv, n_tensors, fname.c_str(), llama_file_version_name(fver));
__func__, n_kv, n_tensors, fname.empty() ? "(file*)" : fname.c_str(), llama_file_version_name(fver));
// determine file type based on the number of tensors for each quantization and print meta data
// TODO: make optional