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https://github.com/ggml-org/llama.cpp.git
synced 2025-11-05 09:36:52 +00:00
mtmd: add --image-min/max-tokens (#16921)
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@@ -2768,6 +2768,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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params.image.emplace_back(value);
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}
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).set_examples({LLAMA_EXAMPLE_MTMD}));
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add_opt(common_arg(
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{"--image-min-tokens"}, "N",
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"minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)",
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[](common_params & params, int value) {
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params.image_min_tokens = value;
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}
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).set_examples(mmproj_examples).set_env("LLAMA_ARG_IMAGE_MIN_TOKENS"));
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add_opt(common_arg(
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{"--image-max-tokens"}, "N",
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"maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)",
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[](common_params & params, int value) {
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params.image_max_tokens = value;
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}
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).set_examples(mmproj_examples).set_env("LLAMA_ARG_IMAGE_MAX_TOKENS"));
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if (llama_supports_rpc()) {
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add_opt(common_arg(
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{"--rpc"}, "SERVERS",
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@@ -406,6 +406,8 @@ struct common_params {
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bool mmproj_use_gpu = true; // use GPU for multimodal model
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bool no_mmproj = false; // explicitly disable multimodal model
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std::vector<std::string> image; // path to image file(s)
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int image_min_tokens = -1;
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int image_max_tokens = -1;
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// finetune
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struct lr_opt lr;
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@@ -169,8 +169,8 @@ struct clip_hparams {
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int32_t n_layer;
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// idefics3
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int32_t image_longest_edge = 0;
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int32_t image_min_pixels = 0;
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int32_t image_max_pixels = 0;
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int32_t image_min_pixels = -1;
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int32_t image_max_pixels = -1;
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int32_t n_merge = 0; // number of patch merges **per-side**
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float image_mean[3];
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@@ -203,11 +203,15 @@ struct clip_hparams {
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int minicpmv_version = 0;
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int32_t minicpmv_query_num = 0; // MiniCPM-V query number
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// custom value provided by user, can be undefined if not set
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int32_t custom_image_min_tokens = -1;
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int32_t custom_image_max_tokens = -1;
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void set_limit_image_tokens(int n_tokens_min, int n_tokens_max) {
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const int cur_merge = n_merge == 0 ? 1 : n_merge;
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const int patch_area = patch_size * patch_size * cur_merge * cur_merge;
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image_min_pixels = n_tokens_min * patch_area;
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image_max_pixels = n_tokens_max * patch_area;
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image_min_pixels = (custom_image_min_tokens > 0 ? custom_image_min_tokens : n_tokens_min) * patch_area;
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image_max_pixels = (custom_image_max_tokens > 0 ? custom_image_max_tokens : n_tokens_max) * patch_area;
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warmup_image_size = static_cast<int>(std::sqrt(image_max_pixels));
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}
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@@ -216,6 +220,7 @@ struct clip_hparams {
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GGML_ASSERT(n_tok_per_side * n_tok_per_side == n_tokens && "n_tokens must be n*n");
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const int cur_merge = n_merge == 0 ? 1 : n_merge;
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warmup_image_size = n_tok_per_side * patch_size * cur_merge;
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// TODO: support warmup size for custom token numbers
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}
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};
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@@ -459,6 +464,13 @@ struct clip_ctx {
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LOG_INF("%s: CLIP using CPU backend\n", __func__);
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}
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if (ctx_params.image_min_tokens > 0) {
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model.hparams.custom_image_min_tokens = ctx_params.image_min_tokens;
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}
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if (ctx_params.image_max_tokens > 0) {
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model.hparams.custom_image_max_tokens = ctx_params.image_max_tokens;
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}
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backend_ptrs.push_back(backend_cpu);
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backend_buft.push_back(ggml_backend_get_default_buffer_type(backend_cpu));
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@@ -2786,6 +2798,12 @@ struct clip_model_loader {
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// see: https://github.com/ggml-org/llama.cpp/issues/16842#issuecomment-3475144858
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hparams.set_limit_image_tokens(8, 2048);
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hparams.set_warmup_n_tokens(256); // avoid OOM on warmup
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const int warn_min_pixels = 1024 * hparams.n_merge * hparams.n_merge * hparams.patch_size * hparams.patch_size;
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if (hparams.image_min_pixels < warn_min_pixels) {
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LOG_WRN("%s: Qwen-VL models require at minimum 1024 image tokens to function correctly on grounding tasks\n", __func__);
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LOG_WRN("%s: if you encounter problems with accuracy, try adding --image-min-tokens 1024\n", __func__);
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LOG_WRN("%s: more info: https://github.com/ggml-org/llama.cpp/issues/16842\n\n", __func__);
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}
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} break;
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case PROJECTOR_TYPE_LLAMA4:
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{
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@@ -2810,6 +2828,13 @@ struct clip_model_loader {
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break;
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}
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// sanity check
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{
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if (hparams.image_max_pixels < hparams.image_min_pixels) {
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throw std::runtime_error(string_format("%s: image_max_pixels (%d) is less than image_min_pixels (%d)\n", __func__, hparams.image_max_pixels, hparams.image_min_pixels));
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}
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}
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LOG_INF("%s: projector: %s\n", __func__, proj_type.c_str());
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LOG_INF("%s: n_embd: %d\n", __func__, hparams.n_embd);
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LOG_INF("%s: n_head: %d\n", __func__, hparams.n_head);
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@@ -2826,10 +2851,10 @@ struct clip_model_loader {
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LOG_INF("%s: n_merge: %d\n", __func__, hparams.n_merge);
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LOG_INF("%s: n_wa_pattern: %d\n", __func__, hparams.n_wa_pattern);
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if (hparams.image_min_pixels > 0) {
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LOG_INF("%s: image_min_pixels: %d\n", __func__, hparams.image_min_pixels);
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LOG_INF("%s: image_min_pixels: %d%s\n", __func__, hparams.image_min_pixels, hparams.custom_image_min_tokens > 0 ? " (custom value)" : "");
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}
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if (hparams.image_max_pixels > 0) {
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LOG_INF("%s: image_max_pixels: %d\n", __func__, hparams.image_max_pixels);
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LOG_INF("%s: image_max_pixels: %d%s\n", __func__, hparams.image_max_pixels, hparams.custom_image_max_tokens > 0 ? " (custom value)" : "");
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}
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} else if (is_audio) {
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LOG_INF("\n--- audio hparams ---\n");
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@@ -4169,7 +4194,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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case PROJECTOR_TYPE_QWEN25VL:
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case PROJECTOR_TYPE_QWEN3VL:
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{
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// step 1: make a blank canvas which aligns to the grid
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GGML_ASSERT(params.image_min_pixels > 0 && params.image_max_pixels > 0);
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clip_image_u8 resized;
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const clip_image_size new_size = img_tool::calc_size_preserved_ratio(
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original_size,
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@@ -4262,7 +4287,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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case PROJECTOR_TYPE_PIXTRAL:
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case PROJECTOR_TYPE_LIGHTONOCR:
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{
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GGML_ASSERT(params.image_min_pixels && params.image_max_pixels);
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GGML_ASSERT(params.image_min_pixels > 0 && params.image_max_pixels > 0);
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clip_image_u8 resized_image;
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// the original pixtral model doesn't have n_merge
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const int cur_merge = params.n_merge == 0 ? 1 : params.n_merge;
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@@ -4296,7 +4321,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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case PROJECTOR_TYPE_LFM2:
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case PROJECTOR_TYPE_KIMIVL:
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{
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GGML_ASSERT(params.image_min_pixels && params.image_max_pixels);
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GGML_ASSERT(params.image_min_pixels > 0 && params.image_max_pixels > 0);
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const clip_image_size target_size = img_tool::calc_size_preserved_ratio(
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original_size,
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params.patch_size * params.n_merge,
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@@ -33,6 +33,8 @@ struct clip_context_params {
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bool use_gpu;
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enum ggml_log_level verbosity;
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enum clip_flash_attn_type flash_attn_type;
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int image_min_tokens;
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int image_max_tokens;
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};
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struct clip_init_result {
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@@ -132,11 +132,13 @@ struct mtmd_cli_context {
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void init_vision_context(common_params & params) {
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const char * clip_path = params.mmproj.path.c_str();
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mtmd_context_params mparams = mtmd_context_params_default();
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mparams.use_gpu = params.mmproj_use_gpu;
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mparams.print_timings = true;
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mparams.n_threads = params.cpuparams.n_threads;
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mparams.verbosity = params.verbosity > 0 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_INFO;
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mparams.flash_attn_type = params.flash_attn_type;
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mparams.use_gpu = params.mmproj_use_gpu;
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mparams.print_timings = true;
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mparams.n_threads = params.cpuparams.n_threads;
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mparams.verbosity = params.verbosity > 0 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_INFO;
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mparams.flash_attn_type = params.flash_attn_type;
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mparams.image_min_tokens = params.image_min_tokens;
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mparams.image_max_tokens = params.image_max_tokens;
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ctx_vision.reset(mtmd_init_from_file(clip_path, model, mparams));
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if (!ctx_vision.get()) {
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LOG_ERR("Failed to load vision model from %s\n", clip_path);
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@@ -109,6 +109,8 @@ mtmd_context_params mtmd_context_params_default() {
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params.image_marker = MTMD_DEFAULT_IMAGE_MARKER;
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params.media_marker = mtmd_default_marker();
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params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_AUTO;
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params.image_min_tokens = -1;
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params.image_max_tokens = -1;
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return params;
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}
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@@ -171,9 +173,13 @@ struct mtmd_context {
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}
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clip_context_params ctx_clip_params;
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ctx_clip_params.use_gpu = ctx_params.use_gpu;
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ctx_clip_params.verbosity = ctx_params.verbosity;
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ctx_clip_params.flash_attn_type = mtmd_get_clip_flash_attn_type(ctx_params.flash_attn_type);
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ctx_clip_params.use_gpu = ctx_params.use_gpu;
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ctx_clip_params.verbosity = ctx_params.verbosity;
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ctx_clip_params.flash_attn_type = mtmd_get_clip_flash_attn_type(ctx_params.flash_attn_type);
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// custom image token limits
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ctx_clip_params.image_min_tokens = ctx_params.image_min_tokens;
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ctx_clip_params.image_max_tokens = ctx_params.image_max_tokens;
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auto res = clip_init(mmproj_fname, ctx_clip_params);
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ctx_v = res.ctx_v;
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ctx_a = res.ctx_a;
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@@ -83,6 +83,10 @@ struct mtmd_context_params {
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const char * image_marker; // deprecated, use media_marker instead
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const char * media_marker;
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enum llama_flash_attn_type flash_attn_type;
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// limit number of image tokens, only for vision models with dynamic resolution
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int image_min_tokens; // minimum number of tokens for image input (default: read from metadata)
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int image_max_tokens; // maximum number of tokens for image input (default: read from metadata)
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};
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MTMD_API const char * mtmd_default_marker(void);
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@@ -2452,11 +2452,13 @@ struct server_context {
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std::string & mmproj_path = params_base.mmproj.path;
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if (!mmproj_path.empty()) {
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mtmd_context_params mparams = mtmd_context_params_default();
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mparams.use_gpu = params_base.mmproj_use_gpu;
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mparams.print_timings = false;
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mparams.n_threads = params_base.cpuparams.n_threads;
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mparams.verbosity = params_base.verbosity > 0 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_INFO;
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mparams.flash_attn_type = params_base.flash_attn_type;
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mparams.use_gpu = params_base.mmproj_use_gpu;
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mparams.print_timings = false;
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mparams.n_threads = params_base.cpuparams.n_threads;
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mparams.verbosity = params_base.verbosity > 0 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_INFO;
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mparams.flash_attn_type = params_base.flash_attn_type;
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mparams.image_min_tokens = params_base.image_min_tokens;
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mparams.image_max_tokens = params_base.image_max_tokens;
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mctx = mtmd_init_from_file(mmproj_path.c_str(), model, mparams);
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if (mctx == nullptr) {
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SRV_ERR("failed to load multimodal model, '%s'\n", mmproj_path.c_str());
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