mtmd : remove libllava, remove clip-quantize-cli (⚠️ breaking change) (#13460)

* mtmd : remove libllava, remove clip-quantize-cli

* rm clip_model_quantize

Author: ngxson

tools/mtmd/CMakeLists.txt

@@ -1,29 +1,3 @@
-# llava (legacy)
-
-add_library(llava OBJECT
-            llava.cpp
-            llava.h
-            clip.cpp
-            clip.h
-            )
-
-target_link_libraries(llava PRIVATE ggml llama ${CMAKE_THREAD_LIBS_INIT})
-
-target_include_directories(llava PUBLIC .)
-target_include_directories(llava PUBLIC ../..)
-target_include_directories(llava PUBLIC ../../common)
-
-target_compile_features(llava PRIVATE cxx_std_17)
-
-add_library(llava_static STATIC $<TARGET_OBJECTS:llava>)
-if (BUILD_SHARED_LIBS)
-    set_target_properties(llava PROPERTIES POSITION_INDEPENDENT_CODE ON)
-    target_compile_definitions(llava PRIVATE LLAMA_SHARED LLAMA_BUILD)
-    add_library(llava_shared SHARED $<TARGET_OBJECTS:llava>)
-    target_link_libraries(llava_shared PRIVATE ggml llama ${CMAKE_THREAD_LIBS_INIT})
-    install(TARGETS llava_shared LIBRARY)
-endif()
-
 # mtmd
 
 add_library(mtmd OBJECT
@@ -53,12 +27,10 @@ if (BUILD_SHARED_LIBS)
 endif()
 
 if (NOT MSVC)
-    target_compile_options(llava PRIVATE -Wno-cast-qual) # stb_image.h
     target_compile_options(mtmd PRIVATE -Wno-cast-qual) # stb_image.h
 endif()
 
 if(TARGET BUILD_INFO)
-    add_dependencies(llava BUILD_INFO)
     add_dependencies(mtmd BUILD_INFO)
 endif()
 
@@ -73,10 +45,3 @@ set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama-mtmd-cli)
 install(TARGETS ${TARGET} RUNTIME)
 target_link_libraries(${TARGET} PRIVATE common mtmd ${CMAKE_THREAD_LIBS_INIT})
 target_compile_features(${TARGET} PRIVATE cxx_std_17)
-
-set(TARGET llama-llava-clip-quantize-cli)
-add_executable(${TARGET} clip-quantize-cli.cpp)
-set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama-llava-clip-quantize-cli)
-install(TARGETS ${TARGET} RUNTIME)
-target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
-target_compile_features(${TARGET} PRIVATE cxx_std_17)

tools/mtmd/README-quantize.md

@@ -41,8 +41,8 @@ Built upon `clip.cpp` (similar to `llava.cpp`), `libmtmd` offers several advanta
 
 Multimodal projector (`mmproj`) files are specific to each model architecture.
 
-For the following models, you can use `convert_hf_to_gguf.py`with `--mmproj` flag to get the `mmproj` file:
-- [Gemma 3](https://huggingface.co/collections/google/gemma-3-release-67c6c6f89c4f76621268bb6d) - Note: 1B variant does not have vision support
+For the following models, you can use `convert_hf_to_gguf.py` with `--mmproj` flag to get the `mmproj` file:
+- [Gemma 3](https://huggingface.co/collections/google/gemma-3-release-67c6c6f89c4f76621268bb6d) ; See the guide [here](../../docs/multimodal/gemma3.md) - Note: 1B variant does not have vision support
 - SmolVLM (from [HuggingFaceTB](https://huggingface.co/HuggingFaceTB))
 - SmolVLM2 (from [HuggingFaceTB](https://huggingface.co/HuggingFaceTB))
 - [Pixtral 12B](https://huggingface.co/mistral-community/pixtral-12b) - only works with `transformers`-compatible checkpoint
@@ -52,11 +52,12 @@ For the following models, you can use `convert_hf_to_gguf.py`with `--mmproj` fla
 
 For older models, please refer to the relevant guide for instructions on how to obtain or create them:
 
+NOTE: conversion scripts are located under `tools/mtmd/legacy-models`
+
 - [LLaVA](../../docs/multimodal/llava.md)
 - [MobileVLM](../../docs/multimodal/MobileVLM.md)
 - [GLM-Edge](../../docs/multimodal/glmedge.md)
 - [MiniCPM-V 2.5](../../docs/multimodal/minicpmv2.5.md)
 - [MiniCPM-V 2.6](../../docs/multimodal/minicpmv2.6.md)
 - [MiniCPM-o 2.6](../../docs/multimodal/minicpmo2.6.md)
 - [IBM Granite Vision](../../docs/multimodal/granitevision.md)
-- [Google Gemma 3](../../docs/multimodal/gemma3.md)

tools/mtmd/README.md

@@ -3586,141 +3586,6 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
     return true;
 }
 
-bool clip_model_quantize(const char * fname_inp, const char * fname_out, const int itype) {
-    assert(itype < GGML_TYPE_COUNT);
-    ggml_type type = static_cast<ggml_type>(itype);
-
-    auto * ctx_clip = clip_init(fname_inp, clip_context_params{
-        /* use_gpu */   false,
-        /* verbosity */ GGML_LOG_LEVEL_ERROR,
-    });
-
-    const auto & ctx_src = ctx_clip->ctx_gguf.get();
-    const auto & ctx_data = ctx_clip->ctx_data.get();
-
-    auto * ctx_out = gguf_init_empty();
-    gguf_set_kv(ctx_out, ctx_src);
-    gguf_set_val_u32(ctx_out, "general.quantization_version", GGML_QNT_VERSION);
-    gguf_set_val_u32(ctx_out, "general.file_type", itype);
-
-    auto fout = std::ofstream(fname_out, std::ios::binary);
-
-    const int n_tensors = gguf_get_n_tensors(ctx_src);
-
-    for (int i = 0; i < n_tensors; ++i) {
-        const char * name = gguf_get_tensor_name(ctx_src, i);
-        ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
-        gguf_add_tensor(ctx_out, cur);
-    }
-
-    const size_t meta_size = gguf_get_meta_size(ctx_out);
-    for (size_t i = 0; i < meta_size; ++i) {
-        fout.put(0);
-    }
-
-    // regexes of tensor names to be quantized
-    const std::vector<std::string> k_names = {
-        ".*weight",
-    };
-
-    std::vector<uint8_t> work(512);
-    std::vector<float> conv_buf(512);
-    size_t total_size_org = 0;
-    size_t total_size_new = 0;
-
-    for (int i = 0; i < n_tensors; ++i) {
-        const std::string name = gguf_get_tensor_name(ctx_src, i);
-        ggml_tensor * cur = ggml_get_tensor(ctx_data, name.c_str());
-
-        enum ggml_type new_type;
-        void * new_data;
-        size_t new_size;
-
-        bool quantize = false;
-        for (const auto & s : k_names) {
-            if (std::regex_match(name, std::regex(s))) {
-                quantize = true;
-                break;
-            }
-        }
-
-        // quantize only 2D tensors and bigger than block size
-        quantize &= (ggml_n_dims(cur) == 2) && cur->ne[0] > ggml_blck_size(type);
-
-        if (quantize) {
-            new_type = type;
-            if (new_type >= GGML_TYPE_Q2_K && name.find("embd") != std::string::npos) {
-                new_type = GGML_TYPE_Q8_0; // ggml_get_rows needs non K type
-                // LOG_ERR("%s: quantizing %s to %s\n", __func__, name.c_str(), ggml_type_name(new_type));
-            }
-            const size_t n_elms = ggml_nelements(cur);
-            float * f32_data;
-
-            switch (cur->type) {
-            case GGML_TYPE_F32:
-                f32_data = (float *)cur->data;
-                break;
-            case GGML_TYPE_F16:
-                if (conv_buf.size() < n_elms) {
-                    conv_buf.resize(n_elms);
-                }
-                for (size_t j = 0; j < n_elms; ++j) {
-                    conv_buf[j] = ggml_fp16_to_fp32(((ggml_fp16_t *)cur->data)[j]);
-                }
-                f32_data = (float *)conv_buf.data();
-                break;
-            default:
-                LOG_ERR("%s: Please use an input file in f32 or f16\n", __func__);
-                gguf_free(ctx_out);
-                return false;
-            }
-
-            if (work.size() < n_elms * 4) {
-                work.resize(n_elms * 4);
-            }
-            new_data = work.data();
-
-            new_size = ggml_quantize_chunk(new_type, f32_data, new_data, 0, n_elms/cur->ne[0], cur->ne[0], nullptr);
-        } else {
-            new_type = cur->type;
-            new_data = cur->data;
-            new_size = ggml_nbytes(cur);
-        }
-        const size_t orig_size = ggml_nbytes(cur);
-        total_size_org += orig_size;
-        total_size_new += new_size;
-        gguf_set_tensor_type(ctx_out, name.c_str(), new_type);
-        GGML_ASSERT(gguf_get_tensor_size(ctx_out, gguf_find_tensor(ctx_out, name.c_str())) == new_size);
-        gguf_set_tensor_data(ctx_out, name.c_str(), new_data);
-        fout.write((const char *)new_data, new_size);
-        size_t pad = GGML_PAD(new_size, gguf_get_alignment(ctx_out)) - new_size;
-        for (size_t j = 0; j < pad; ++j) {
-            fout.put(0);
-        }
-
-        LOG_INF("%s: n_dims = %d | quantize=%d | size = %f MB -> %f MB\n", name.c_str(), ggml_n_dims(cur), quantize,
-               orig_size / 1024.0 / 1024.0, new_size / 1024.0 / 1024.0);
-    }
-
-    // go back to beginning of file and write the updated metadata
-    fout.seekp(0, std::ios::beg);
-    std::vector<uint8_t> meta(meta_size);
-    gguf_get_meta_data(ctx_out, meta.data());
-    fout.write((const char *)meta.data(), meta_size);
-
-    fout.close();
-
-    clip_free(ctx_clip);
-    gguf_free(ctx_out);
-
-    {
-        LOG_INF("%s: original  size = %8.2f MB\n", __func__, total_size_org / 1024.0 / 1024.0);
-        LOG_INF("%s: quantized size = %8.2f MB\n", __func__, total_size_new / 1024.0 / 1024.0);
-    }
-
-    return true;
-}
-
 int clip_n_mmproj_embd(const struct clip_ctx * ctx) {
     switch (ctx->proj_type) {
         case PROJECTOR_TYPE_LDP: