llama : add fd-based model loading via llama_model_load_from_fd ( REWORK )

ggml/include/gguf.h

@@ -78,6 +78,7 @@ extern "C" {
 
     GGML_API struct gguf_context * gguf_init_empty(void);
     GGML_API struct gguf_context * gguf_init_from_file(const char * fname, struct gguf_init_params params);
+    GGML_API struct gguf_context * gguf_init_from_file_ptr(FILE * file, struct gguf_init_params params);
     //GGML_API struct gguf_context * gguf_init_from_buffer(..);
 
     GGML_API void gguf_free(struct gguf_context * ctx);

ggml/src/ggml-impl.h

@@ -718,6 +718,5 @@ inline bool ggml_check_edges(const struct ggml_cgraph *                cgraph,
 
 // expose GGUF internals for test code
 GGML_API size_t gguf_type_size(enum gguf_type type);
-GGML_API struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_params params);
 GGML_API void gguf_write_to_buf(const struct gguf_context * ctx, std::vector<int8_t> & buf, bool only_meta);
 #endif // __cplusplus

ggml/src/gguf.cpp

@@ -394,7 +394,11 @@ bool gguf_read_emplace_helper(const struct gguf_reader & gr, std::vector<struct
     return true;
 }
 
-struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_params params) {
+struct gguf_context * gguf_init_from_file_ptr(FILE * file, struct gguf_init_params params) {
+    if (!file) {
+        return nullptr;
+    }
+
     const struct gguf_reader gr(file);
     struct gguf_context * ctx = new gguf_context;
 
@@ -848,7 +852,7 @@ struct gguf_context * gguf_init_from_file(const char * fname, struct gguf_init_p
         return nullptr;
     }
 
-    struct gguf_context * result = gguf_init_from_file_impl(file, params);
+    struct gguf_context * result = gguf_init_from_file_ptr(file, params);
     fclose(file);
     return result;
 }

include/llama.h

@@ -464,6 +464,11 @@ extern "C" {
                              const char * path_model,
               struct llama_model_params   params);
 
+    // Load a model from an open FILE pointer
+    LLAMA_API struct llama_model * llama_model_load_from_file_ptr(
+                                   FILE * file,
+              struct llama_model_params   params);
+
     // Load a model from multiple splits (support custom naming scheme)
     // The paths must be in the correct order
     LLAMA_API struct llama_model * llama_model_load_from_splits(

src/llama-mmap.cpp

@@ -86,6 +86,14 @@ struct llama_file::impl {
         seek(0, SEEK_SET);
     }
 
+    impl(FILE * file) : owns_fp(false) {
+        fp = file;
+        fp_win32 = (HANDLE) _get_osfhandle(_fileno(fp));
+        seek(0, SEEK_END);
+        size = tell();
+        seek(0, SEEK_SET);
+    }
+
     size_t tell() const {
         LARGE_INTEGER li;
         li.QuadPart = 0;
@@ -159,7 +167,7 @@ struct llama_file::impl {
     }
 
     ~impl() {
-        if (fp) {
+        if (fp && owns_fp) {
             std::fclose(fp);
         }
     }
@@ -209,6 +217,13 @@ struct llama_file::impl {
         seek(0, SEEK_SET);
     }
 
+    impl(FILE * file) : fname("(file*)"), owns_fp(false) {
+        fp = file;
+        seek(0, SEEK_END);
+        size = tell();
+        seek(0, SEEK_SET);
+    }
+
     size_t tell() const {
         if (fd == -1) {
             long ret = std::ftell(fp);
@@ -353,7 +368,7 @@ struct llama_file::impl {
     ~impl() {
         if (fd != -1) {
             close(fd);
-        } else {
+        } else if (owns_fp) {
             std::fclose(fp);
         }
     }
@@ -369,10 +384,14 @@ struct llama_file::impl {
 
     FILE * fp{};
     size_t size{};
+    bool owns_fp = true;
 };
 
 llama_file::llama_file(const char * fname, const char * mode, const bool use_direct_io) :
     pimpl(std::make_unique<impl>(fname, mode, use_direct_io)) {}
+
+llama_file::llama_file(FILE * file) : pimpl(std::make_unique<impl>(file)) {}
+
 llama_file::~llama_file() = default;
 
 size_t llama_file::tell() const { return pimpl->tell(); }

src/llama-mmap.h

@@ -15,12 +15,13 @@ using llama_mlocks = std::vector<std::unique_ptr<llama_mlock>>;
 
 struct llama_file {
     llama_file(const char * fname, const char * mode, bool use_direct_io = false);
+    llama_file(FILE * file);
     ~llama_file();
 
     size_t tell() const;
     size_t size() const;
 
-    int file_id() const; // fileno overload
+    int file_id() const;
 
     void seek(size_t offset, int whence) const;
 

src/llama-model-loader.cpp

@@ -510,6 +510,7 @@ 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,
@@ -657,6 +658,36 @@ llama_model_loader::llama_model_loader(
 
             LLAMA_LOG_INFO("%s: additional %d GGUFs metadata loaded.\n",  __func__, n_split - 1);
         }
+    } else if (file) {
+        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));
@@ -668,7 +699,7 @@ 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

src/llama-model-loader.h

@@ -125,6 +125,7 @@ struct llama_model_loader {
         void * set_tensor_data_ud,
         const std::string & fname,
         std::vector<std::string> & splits, // optional, only need if the split does not follow naming scheme
+        FILE * file,
         bool use_mmap,
         bool use_direct_io,
         bool check_tensors,

src/llama-quant.cpp

@@ -859,7 +859,7 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
 
     std::vector<std::string> splits = {};
     llama_model_loader ml(/*metadata*/ nullptr, /*set_tensor_data*/ nullptr, /*set_tensor_data_ud*/ nullptr,
-        fname_inp, splits, use_mmap, /*use_direct_io*/ false, /*check_tensors*/ true, /*no_alloc*/ false, kv_overrides, nullptr);
+        fname_inp, splits, /*file*/ nullptr, use_mmap, /*use_direct_io*/ false, /*check_tensors*/ true, /*no_alloc*/ false, kv_overrides, nullptr);
     ml.init_mappings(false); // no prefetching
 
     llama_model model(llama_model_default_params());

src/llama.cpp

@@ -828,7 +828,7 @@ int64_t llama_time_us(void) {
 
 // Returns 0 on success, -1 on error, and -2 on cancellation via llama_progress_callback
 static int llama_model_load(struct gguf_context * metadata, llama_model_set_tensor_data_t set_tensor_data, void * set_tensor_data_ud,
-        const std::string & fname, std::vector<std::string> & splits, llama_model & model, llama_model_params & params) {
+        const std::string & fname, std::vector<std::string> & splits, FILE * file, llama_model & model, llama_model_params & params) {
     // loading time will be recalculated after the first eval, so
     // we take page faults deferred by mmap() into consideration
     model.t_load_us = 0;
@@ -837,7 +837,7 @@ static int llama_model_load(struct gguf_context * metadata, llama_model_set_tens
     model.t_start_us = tm.t_start_us;
 
     try {
-        llama_model_loader ml(metadata, set_tensor_data, set_tensor_data_ud, fname, splits, params.use_mmap, params.use_direct_io,
+        llama_model_loader ml(metadata, set_tensor_data, set_tensor_data_ud, fname, splits, file, params.use_mmap, params.use_direct_io,
             params.check_tensors, params.no_alloc, params.kv_overrides, params.tensor_buft_overrides);
 
         ml.print_info();
@@ -889,8 +889,12 @@ static struct llama_model * llama_model_load_from_file_impl(
         void * set_tensor_data_ud,
         const std::string & path_model,
         std::vector<std::string> & splits,
+        FILE * file,
         struct llama_model_params params) {
-    GGML_ASSERT((metadata == nullptr) != path_model.empty() && "exactly one out of metadata and path_model needs to be defined");
+    if (metadata == nullptr && path_model.empty() && !file) {
+        LLAMA_LOG_ERROR("%s: no model source provided\n", __func__);
+        return nullptr;
+    }
     ggml_time_init();
 
     if (!params.vocab_only && ggml_backend_reg_count() == 0) {
@@ -1011,7 +1015,7 @@ static struct llama_model * llama_model_load_from_file_impl(
                 props.memory_free/1024/1024);
     }
 
-    const int status = llama_model_load(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, *model, params);
+    const int status = llama_model_load(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, file, *model, params);
     GGML_ASSERT(status <= 0);
     if (status < 0) {
         if (status == -1) {
@@ -1037,7 +1041,7 @@ struct llama_model * llama_model_init_from_user(
     std::vector<std::string> splits = {};
     params.use_mmap = false;
     params.use_extra_bufts = false;
-    return llama_model_load_from_file_impl(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, params);
+    return llama_model_load_from_file_impl(metadata, set_tensor_data, set_tensor_data_ud, path_model, splits, /*file*/ nullptr, params);
 }
 // deprecated
 struct llama_model * llama_load_model_from_file(
@@ -1050,7 +1054,7 @@ struct llama_model * llama_model_load_from_file(
         const char * path_model,
         struct llama_model_params params) {
     std::vector<std::string> splits = {};
-    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, params);
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, /*file*/ nullptr, params);
 }
 
 struct llama_model * llama_model_load_from_splits(
@@ -1066,7 +1070,17 @@ struct llama_model * llama_model_load_from_splits(
     for (size_t i = 0; i < n_paths; ++i) {
         splits.push_back(paths[i]);
     }
-    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, splits.front(), splits, params);
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, splits.front(), splits, /*file*/ nullptr, params);
+}
+
+struct llama_model * llama_model_load_from_file_ptr(FILE * file, struct llama_model_params params) {
+    if (!file) {
+        LLAMA_LOG_ERROR("%s: file is NULL\n", __func__);
+        return nullptr;
+    }
+    std::string path_model;
+    std::vector<std::string> splits = {};
+    return llama_model_load_from_file_impl(nullptr, nullptr, nullptr, path_model, splits, file, params);
 }
 
 void llama_model_save_to_file(const struct llama_model * model, const char * path_model) {

tests/CMakeLists.txt

@@ -240,6 +240,7 @@ llama_build_and_test(test-gguf.cpp)
 llama_build_and_test(test-backend-ops.cpp)
 
 llama_build_and_test(test-model-load-cancel.cpp LABEL "model")
+llama_build_and_test(test-model-load-fd.cpp     LABEL "model")
 llama_build_and_test(test-autorelease.cpp       LABEL "model")
 llama_build_and_test(test-backend-sampler.cpp   LABEL "model")
 

tests/test-gguf.cpp

@@ -742,7 +742,7 @@ static std::pair<int, int> test_handcrafted_file(const unsigned int seed) {
             /*ctx      =*/ hft >= offset_has_data ? &ctx : nullptr,
         };
 
-        struct gguf_context * gguf_ctx = gguf_init_from_file_impl(file, gguf_params);
+        struct gguf_context * gguf_ctx = gguf_init_from_file_ptr(file, gguf_params);
 
         if (expect_context_not_null(hft)) {
             printf("%s:   - context_not_null: ", __func__);
@@ -1137,7 +1137,7 @@ static std::pair<int, int> test_roundtrip(ggml_backend_dev_t dev, const unsigned
         /*no_alloc =*/ false,
         /*ctx      =*/ only_meta ? nullptr : &ctx_1,
     };
-    struct gguf_context * gguf_ctx_1 = gguf_init_from_file_impl(file, gguf_params);
+    struct gguf_context * gguf_ctx_1 = gguf_init_from_file_ptr(file, gguf_params);
 
     printf("%s: same_version: ", __func__);
     if (gguf_get_version(gguf_ctx_0) == gguf_get_version(gguf_ctx_1)) {

tests/test-model-load-fd.cpp

@@ -0,0 +1,54 @@
+#include "llama.h"
+#include "get-model.h"
+
+#include <cstdio>
+#include <cstdlib>
+
+#ifdef _WIN32
+int main(int /*argc*/, char ** /*argv*/) {
+    fprintf(stderr, "skipping on Windows\n");
+    return EXIT_SUCCESS;
+}
+#else
+#    include <fcntl.h>
+#    include <unistd.h>
+
+int main(int argc, char ** argv) {
+    auto * model_path = get_model_or_exit(argc, argv);
+
+    llama_backend_init();
+
+    const int fd = open(model_path, O_RDONLY);
+    if (fd < 0) {
+        fprintf(stderr, "failed to open %s\n", model_path);
+        return EXIT_FAILURE;
+    }
+
+    FILE * f = fdopen(dup(fd), "rb");
+    close(fd);
+    if (!f) {
+        fprintf(stderr, "failed to fdopen\n");
+        return EXIT_FAILURE;
+    }
+
+    auto params = llama_model_default_params();
+    params.use_mmap = true;
+    params.vocab_only = true;
+
+    struct llama_model * model = llama_model_load_from_file_ptr(f, params);
+    fclose(f);
+
+    if (model == nullptr) {
+        fprintf(stderr, "load from file pointer failed\n");
+        return EXIT_FAILURE;
+    }
+
+    const int n_vocab = llama_vocab_n_tokens(llama_model_get_vocab(model));
+    fprintf(stderr, "loaded %d tokens via file pointer\n", n_vocab);
+
+    llama_model_free(model);
+    llama_backend_free();
+
+    return n_vocab > 0 ? EXIT_SUCCESS : EXIT_FAILURE;
+}
+#endif // _WIN32