llama: fix llama-model-saver

ggml/include/gguf.h

@@ -77,6 +77,7 @@ extern "C" {
     };
 
     GGML_API struct gguf_context * gguf_init_empty(void);
+    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_file(const char * fname, struct gguf_init_params params);
     //GGML_API struct gguf_context * gguf_init_from_buffer(..);
 
@@ -189,6 +190,7 @@ extern "C" {
     //
 
     // write the entire context to a binary file
+    GGML_API bool gguf_write_to_file_ptr(const struct gguf_context * ctx, FILE * file, bool only_meta);
     GGML_API bool gguf_write_to_file(const struct gguf_context * ctx, const char * fname, bool only_meta);
 
     // get the size in bytes of the meta data (header, kv pairs, tensor info) including padding

ggml/src/ggml-impl.h

@@ -773,6 +773,5 @@ 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;
 }
@@ -1508,6 +1512,19 @@ void gguf_write_to_buf(const struct gguf_context * ctx, std::vector<int8_t> & bu
     gguf_write_out(ctx, gw, only_meta);
 }
 
+bool gguf_write_to_file_ptr(const struct gguf_context * ctx, FILE * file, bool only_meta) {
+    GGML_ASSERT(file);
+
+    try {
+        gguf_writer_file gw(file);
+        gguf_write_out(ctx, gw, only_meta);
+    } catch (const std::runtime_error& ex) {
+        GGML_LOG_ERROR("%s: failed to write GGUF data: %s\n", __func__, ex.what());
+        return false;
+    }
+    return true;
+}
+
 bool gguf_write_to_file(const struct gguf_context * ctx, const char * fname, bool only_meta) {
     FILE * file = ggml_fopen(fname, "wb");
 
@@ -1516,17 +1533,13 @@ bool gguf_write_to_file(const struct gguf_context * ctx, const char * fname, boo
         return false;
     }
 
-    try {
-        gguf_writer_file gw(file);
-        gguf_write_out(ctx, gw, only_meta);
-    } catch (const std::runtime_error& ex) {
-        GGML_LOG_ERROR("%s: failed to write GGUF data into '%s': %s\n", __func__, fname, ex.what());
-        fclose(file);
-        return false;
+    const bool success = gguf_write_to_file_ptr(ctx, file, only_meta);
+    if (!success) {
+        GGML_LOG_ERROR("%s: failed to write GGUF data into '%s'\n", __func__, fname);
     }
 
     fclose(file);
-    return true;
+    return success;
 }
 
 size_t gguf_get_meta_size(const struct gguf_context * ctx) {

include/llama.h

@@ -465,6 +465,11 @@ 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-arch.cpp

@@ -544,6 +544,10 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
         case LLM_ARCH_CLIP:
             return {};
         case LLM_ARCH_LLAMA:
+        case LLM_ARCH_REFACT:
+        case LLM_ARCH_MINICPM:
+        case LLM_ARCH_GRANITE:
+        case LLM_ARCH_GRANITE_MOE:
         case LLM_ARCH_DECI:
         case LLM_ARCH_MISTRAL3:
         case LLM_ARCH_LLAMA_EMBED:
@@ -744,11 +748,9 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_ATTN_Q_NORM,
                 LLM_TENSOR_ATTN_K_NORM,
             };
-        case LLM_ARCH_REFACT:
         case LLM_ARCH_QWEN2:
         case LLM_ARCH_QWEN2VL:
         case LLM_ARCH_INTERNLM2:
-        case LLM_ARCH_GRANITE:
         case LLM_ARCH_ERNIE4_5:
         case LLM_ARCH_PADDLEOCR:
         case LLM_ARCH_SMOLLM3:
@@ -759,6 +761,7 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_TOKEN_EMBD,
                 LLM_TENSOR_OUTPUT_NORM,
                 LLM_TENSOR_OUTPUT,
+                LLM_TENSOR_ROPE_FREQS,
                 LLM_TENSOR_ATTN_NORM,
                 LLM_TENSOR_ATTN_Q,
                 LLM_TENSOR_ATTN_K,
@@ -1232,29 +1235,6 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_FFN_DOWN,
                 LLM_TENSOR_FFN_UP,
             };
-        case LLM_ARCH_MINICPM:
-            return {
-                LLM_TENSOR_TOKEN_EMBD,
-                LLM_TENSOR_OUTPUT_NORM,
-                LLM_TENSOR_OUTPUT,
-                LLM_TENSOR_ROPE_FREQS,
-                LLM_TENSOR_ROPE_FACTORS_LONG,
-                LLM_TENSOR_ROPE_FACTORS_SHORT,
-                LLM_TENSOR_ATTN_NORM,
-                LLM_TENSOR_ATTN_Q,
-                LLM_TENSOR_ATTN_K,
-                LLM_TENSOR_ATTN_V,
-                LLM_TENSOR_ATTN_OUT,
-                LLM_TENSOR_ATTN_ROT_EMBD,
-                LLM_TENSOR_FFN_GATE_INP,
-                LLM_TENSOR_FFN_NORM,
-                LLM_TENSOR_FFN_GATE,
-                LLM_TENSOR_FFN_DOWN,
-                LLM_TENSOR_FFN_UP,
-                LLM_TENSOR_FFN_GATE_EXP,
-                LLM_TENSOR_FFN_DOWN_EXP,
-                LLM_TENSOR_FFN_UP_EXP,
-            };
         case LLM_ARCH_MINICPM3:
             return {
                 LLM_TENSOR_TOKEN_EMBD,
@@ -1442,6 +1422,7 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_TOKEN_EMBD,
                 LLM_TENSOR_OUTPUT,
                 LLM_TENSOR_OUTPUT_NORM,
+                LLM_TENSOR_ROPE_FREQS,
                 LLM_TENSOR_ATTN_NORM,
                 LLM_TENSOR_ATTN_Q,
                 LLM_TENSOR_ATTN_K,
@@ -1657,7 +1638,9 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_ROPE_FREQS,
                 LLM_TENSOR_OUTPUT_NORM,
                 LLM_TENSOR_OUTPUT,
+                LLM_TENSOR_TOKEN_EMBD,
                 LLM_TENSOR_ATTN_NORM,
+                LLM_TENSOR_ATTN_QKV,
                 LLM_TENSOR_ATTN_Q,
                 LLM_TENSOR_ATTN_K,
                 LLM_TENSOR_ATTN_V,
@@ -2061,30 +2044,12 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_FFN_DOWN,
                 LLM_TENSOR_FFN_UP,
             };
-        case LLM_ARCH_GRANITE_MOE:
-            return {
-                LLM_TENSOR_TOKEN_EMBD,
-                LLM_TENSOR_OUTPUT_NORM,
-                LLM_TENSOR_OUTPUT,
-                LLM_TENSOR_ATTN_NORM,
-                LLM_TENSOR_ATTN_Q,
-                LLM_TENSOR_ATTN_K,
-                LLM_TENSOR_ATTN_V,
-                LLM_TENSOR_ATTN_OUT,
-                LLM_TENSOR_FFN_NORM,
-                LLM_TENSOR_FFN_GATE_INP,
-                LLM_TENSOR_FFN_GATE_EXPS,
-                LLM_TENSOR_FFN_DOWN_EXPS,
-                LLM_TENSOR_FFN_UP_EXPS,
-                LLM_TENSOR_FFN_GATE_SHEXP,
-                LLM_TENSOR_FFN_DOWN_SHEXP,
-                LLM_TENSOR_FFN_UP_SHEXP,
-            };
         case LLM_ARCH_GRANITE_HYBRID:
             return {
                 LLM_TENSOR_TOKEN_EMBD,
                 LLM_TENSOR_OUTPUT_NORM,
                 LLM_TENSOR_OUTPUT,
+                LLM_TENSOR_ROPE_FREQS,
                 LLM_TENSOR_ATTN_NORM,
                 LLM_TENSOR_SSM_IN,
                 LLM_TENSOR_SSM_CONV1D,
@@ -2412,6 +2377,7 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_TOKEN_EMBD,
                 LLM_TENSOR_OUTPUT_NORM,
                 LLM_TENSOR_OUTPUT,
+                LLM_TENSOR_ROPE_FREQS,
                 LLM_TENSOR_ATTN_NORM,
                 LLM_TENSOR_ATTN_QKV,
                 LLM_TENSOR_ATTN_OUT,
@@ -2789,7 +2755,12 @@ std::string LLM_TN_IMPL::str() const {
     }
 
     if (model_tensors.find(tensor) == model_tensors.end()) {
-        return LLM_TENSOR_NAMES.at(tensor);
+        const char * name = LLM_TENSOR_NAMES.at(tensor);
+        if (suffix != nullptr || bid != -1 || xid != -1) {
+            LLAMA_LOG_WARN("%s: cannot properly format tensor name %s with suffix=%s bid=%d xid=%d\n",
+                __func__, name, suffix, bid, xid);
+        }
+        return name;
     }
 
     std::string name = ::format(LLM_TENSOR_NAMES.at(tensor), bid, xid);

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

@@ -15,6 +15,7 @@ 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;

src/llama-model-loader.cpp

@@ -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

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,