model : Granite docling + Idefics3 preprocessing (SmolVLM) (#16206)
* feat: Add granite-docling conversion using trillion pretokenizer Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Add granite-docling vocab pre enum Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Use granite-docling pre Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Add clip_is_idefics3 Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Allow multi-token boundary sequences for image templating Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Add tiling support for idefices3 in clip.cpp This should likely be moved into llava_uhd::get_slice_instructions, but for now this avoids disrupting the logic there. Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Partial support for full templating for idefics3 in mtmd There are still errors encoding some of the image chunks, but the token sequence now matches transformers _almost_ perfectly, except for the double newline before the global image which shows up as two consecutive newline tokens instead of a single double-newline token. I think this is happening because the blocks are tokenized separately then concatenated. Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Fully working image preprocessing for idefics3 w/ resize and slicing Branch: gabe-l-hart/GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: Parse the preprocessor config's longest side and add it to the mmproj hparams Branch: GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Use the longest side instead of size * scale_factor For Granite Docling, these come out to the same value, but that was just a conicidence. Branch: GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Allow batch encoding and remove clip_is_idefics3 Branch: GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * refactor: Remove unnecessary conditionals for empty token vectors Branch: GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * refactor: Use image_manipulation util Branch: GraniteDocling Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * add test model --------- Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This commit is contained in:
Gabe Goodhart
GitHub
parent
35266573b9
commit
ca71fb9b36
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@ -891,6 +891,9 @@ class TextModel(ModelBase):
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if chkhsh == "9b1be57e70d20d9501b2b3186e792d81181ae36ada3903c26f9fea418cf87206":
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# ref: https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base
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res = "llada-moe"
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if chkhsh == "53e325976a6e142379c19b09afcae354f2f496f147afa8f9e189a33fe4e3024e":
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# ref: https://huggingface.co/ibm-granite/granite-docling-258M
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res = "granite-docling"
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if res is None:
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logger.warning("\n")
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@ -1325,6 +1328,7 @@ class MmprojModel(ModelBase):
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self.tensor_map = gguf.get_tensor_name_map(gguf.MODEL_ARCH.MMPROJ, self.block_count)
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# load preprocessor config
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self.preprocessor_config = {}
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if not self.is_mistral_format:
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with open(self.dir_model / "preprocessor_config.json", "r", encoding="utf-8") as f:
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self.preprocessor_config = json.load(f)
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@ -1347,7 +1351,8 @@ class MmprojModel(ModelBase):
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self.gguf_writer.add_vision_projection_dim(self.n_embd_text)
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# vision config
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self.gguf_writer.add_vision_image_size(self.find_vparam(["image_size"]))
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self.image_size = self.find_vparam(["image_size"])
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self.gguf_writer.add_vision_image_size(self.image_size)
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self.gguf_writer.add_vision_patch_size(self.find_vparam(["patch_size"]))
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self.gguf_writer.add_vision_embedding_length(self.find_vparam(["hidden_size"]))
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self.gguf_writer.add_vision_feed_forward_length(self.find_vparam(["intermediate_size"]))
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@ -2378,6 +2383,10 @@ class SmolVLMModel(MmprojModel):
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self.gguf_writer.add_vision_projector_scale_factor(self.global_config.get("scale_factor", 2))
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self.gguf_writer.add_vision_use_gelu(True)
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# Add the preprocessor longest edge size
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preproc_image_size = self.preprocessor_config.get("size", {}).get("longest_edge", self.image_size)
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self.gguf_writer.add_vision_preproc_image_size(preproc_image_size)
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def tensor_force_quant(self, name, new_name, bid, n_dims):
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if ".embeddings." in name:
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return gguf.GGMLQuantizationType.F32
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@ -140,6 +140,7 @@ models = [
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{"name": "exaone4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B", },
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{"name": "mellum", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/JetBrains/Mellum-4b-base", },
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{"name": "llada-moe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base", },
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{"name": "granite-docling", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ibm-granite/granite-docling-258M", },
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]
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# some models are known to be broken upstream, so we will skip them as exceptions
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@ -261,6 +261,7 @@ class Keys:
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class ClipVision:
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IMAGE_SIZE = "clip.vision.image_size"
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PREPROC_IMAGE_SIZE = "clip.vision.preproc_image_size"
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PATCH_SIZE = "clip.vision.patch_size"
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EMBEDDING_LENGTH = "clip.vision.embedding_length"
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FEED_FORWARD_LENGTH = "clip.vision.feed_forward_length"
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@ -1037,6 +1037,9 @@ class GGUFWriter:
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def add_vision_image_size(self, value: int) -> None:
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self.add_uint32(Keys.ClipVision.IMAGE_SIZE, value)
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def add_vision_preproc_image_size(self, value: int) -> None:
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self.add_uint32(Keys.ClipVision.PREPROC_IMAGE_SIZE, value)
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def add_vision_image_mean(self, values: Sequence[float]) -> None:
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self.add_array(Keys.ClipVision.IMAGE_MEAN, values)
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@ -347,6 +347,7 @@ struct llm_tokenizer_bpe : llm_tokenizer {
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case LLAMA_VOCAB_PRE_TYPE_OLMO:
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case LLAMA_VOCAB_PRE_TYPE_JAIS:
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case LLAMA_VOCAB_PRE_TYPE_TRILLION:
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case LLAMA_VOCAB_PRE_TYPE_GRANITE_DOCLING:
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regex_exprs = {
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"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
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};
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@ -1961,6 +1962,10 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
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tokenizer_pre == "trillion") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_TRILLION;
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clean_spaces = false;
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} else if (
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tokenizer_pre == "granite-docling") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_GRANITE_DOCLING;
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clean_spaces = false;
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} else if (
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tokenizer_pre == "bailingmoe" ||
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tokenizer_pre == "llada-moe") {
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@ -48,6 +48,7 @@ enum llama_vocab_pre_type {
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LLAMA_VOCAB_PRE_TYPE_KIMI_K2 = 37,
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LLAMA_VOCAB_PRE_TYPE_HUNYUAN_DENSE = 38,
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LLAMA_VOCAB_PRE_TYPE_GROK_2 = 39,
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LLAMA_VOCAB_PRE_TYPE_GRANITE_DOCLING = 40,
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};
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struct LLM_KV;
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@ -31,6 +31,7 @@
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// vision-specific
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#define KEY_IMAGE_SIZE "clip.vision.image_size"
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#define KEY_PREPROC_IMAGE_SIZE "clip.vision.preproc_image_size"
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#define KEY_PATCH_SIZE "clip.vision.patch_size"
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#define KEY_IMAGE_MEAN "clip.vision.image_mean"
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#define KEY_IMAGE_STD "clip.vision.image_std"
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@ -170,7 +170,9 @@ struct clip_hparams {
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int32_t projection_dim;
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int32_t n_head;
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int32_t n_layer;
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int32_t proj_scale_factor = 0; // idefics3
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// idefics3
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int32_t preproc_image_size = 0;
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int32_t proj_scale_factor = 0;
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float image_mean[3];
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float image_std[3];
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@ -2250,6 +2252,7 @@ struct clip_model_loader {
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if (is_vision) {
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get_u32(KEY_IMAGE_SIZE, hparams.image_size);
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get_u32(KEY_PREPROC_IMAGE_SIZE, hparams.preproc_image_size, false);
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get_u32(KEY_PATCH_SIZE, hparams.patch_size);
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get_u32(KEY_IMAGE_CROP_RESOLUTION, hparams.image_crop_resolution, false);
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get_i32(KEY_MINICPMV_VERSION, hparams.minicpmv_version, false); // legacy
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@ -3551,10 +3554,51 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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// res_imgs->data[0] = *res;
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res_imgs->entries.push_back(std::move(img_f32));
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return true;
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} else if (ctx->proj_type() == PROJECTOR_TYPE_IDEFICS3) {
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// The refined size has two steps:
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// 1. Resize w/ aspect-ratio preserving such that the longer side is
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// the preprocessor longest size
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// 2. Resize w/out preserving aspect ratio such that both sides are
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// multiples of image_size (always rounding up)
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//
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// CITE: https://github.com/huggingface/transformers/blob/main/src/transformers/models/idefics3/image_processing_idefics3.py#L737
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const clip_image_size refined_size = image_manipulation::calc_size_preserved_ratio(
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original_size, params.image_size, params.preproc_image_size);
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llava_uhd::slice_instructions instructions;
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instructions.overview_size = clip_image_size{params.image_size, params.image_size};
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instructions.refined_size = refined_size;
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instructions.grid_size = clip_image_size{
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static_cast<int>(std::ceil(static_cast<float>(refined_size.width) / params.image_size)),
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static_cast<int>(std::ceil(static_cast<float>(refined_size.height) / params.image_size)),
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};
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for (int y = 0; y < refined_size.height; y += params.image_size) {
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for (int x = 0; x < refined_size.width; x += params.image_size) {
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instructions.slices.push_back(llava_uhd::slice_coordinates{
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/* x */x,
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/* y */y,
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/* size */clip_image_size{
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std::min(params.image_size, refined_size.width - x),
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std::min(params.image_size, refined_size.height - y)
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}
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else if (ctx->proj_type() == PROJECTOR_TYPE_GLM_EDGE
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});
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}
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}
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auto imgs = llava_uhd::slice_image(img, instructions);
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// cast and normalize to f32
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for (size_t i = 0; i < imgs.size(); ++i) {
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// clip_image_save_to_bmp(*imgs[i], "slice_" + std::to_string(i) + ".bmp");
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clip_image_f32_ptr res(clip_image_f32_init());
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normalize_image_u8_to_f32(*imgs[i], *res, params.image_mean, params.image_std);
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res_imgs->entries.push_back(std::move(res));
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}
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res_imgs->grid_x = instructions.grid_size.width;
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res_imgs->grid_y = instructions.grid_size.height;
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return true;
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} else if (ctx->proj_type() == PROJECTOR_TYPE_GLM_EDGE
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|| ctx->proj_type() == PROJECTOR_TYPE_GEMMA3
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|| ctx->proj_type() == PROJECTOR_TYPE_IDEFICS3
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|| ctx->proj_type() == PROJECTOR_TYPE_INTERNVL // TODO @ngxson : support dynamic resolution
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) {
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clip_image_u8 resized_image;
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@ -76,7 +76,7 @@ enum mtmd_slice_tmpl {
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MTMD_SLICE_TMPL_MINICPMV_2_5,
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MTMD_SLICE_TMPL_MINICPMV_2_6,
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MTMD_SLICE_TMPL_LLAMA4,
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// TODO @ngxson : add support for idefics (SmolVLM)
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MTMD_SLICE_TMPL_IDEFICS3,
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};
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const char * mtmd_default_marker() {
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@ -114,19 +114,22 @@ struct mtmd_context {
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// for llava-uhd style models, we need special tokens in-between slices
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// minicpmv calls them "slices", llama 4 calls them "tiles"
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mtmd_slice_tmpl slice_tmpl = MTMD_SLICE_TMPL_NONE;
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llama_token tok_ov_img_start = LLAMA_TOKEN_NULL; // overview image
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llama_token tok_ov_img_end = LLAMA_TOKEN_NULL; // overview image
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llama_token tok_slices_start = LLAMA_TOKEN_NULL; // start of all slices
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llama_token tok_slices_end = LLAMA_TOKEN_NULL; // end of all slices
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llama_token tok_sli_img_start = LLAMA_TOKEN_NULL; // single slice start
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llama_token tok_sli_img_end = LLAMA_TOKEN_NULL; // single slice end
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llama_token tok_sli_img_mid = LLAMA_TOKEN_NULL; // between 2 slices
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llama_token tok_row_end = LLAMA_TOKEN_NULL; // end of row
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std::vector<llama_token> tok_ov_img_start; // overview image
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std::vector<llama_token> tok_ov_img_end; // overview image
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std::vector<llama_token> tok_slices_start; // start of all slices
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std::vector<llama_token> tok_slices_end; // end of all slices
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std::vector<llama_token> tok_sli_img_start; // single slice start
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std::vector<llama_token> tok_sli_img_end; // single slice end
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std::vector<llama_token> tok_sli_img_mid; // between 2 slices
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std::vector<llama_token> tok_row_end; // end of row
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bool tok_row_end_trail = false;
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bool ov_img_first = false;
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bool use_mrope = false; // for Qwen2VL, we need to use M-RoPE
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// string template for slice image delimiters with row/col (idefics3)
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std::string sli_img_start_tmpl;
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// for whisper, we pre-calculate the mel filter bank
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whisper_preprocessor::whisper_filters w_filters;
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@ -197,13 +200,13 @@ struct mtmd_context {
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// minicpmv 2.5 format:
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// <image> (overview) </image><slice><image> (slice) </image><image> (slice) </image>\n ... </slice>
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slice_tmpl = MTMD_SLICE_TMPL_MINICPMV_2_5;
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tok_ov_img_start = lookup_token("<image>");
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tok_ov_img_end = lookup_token("</image>");
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tok_slices_start = lookup_token("<slice>");
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tok_slices_end = lookup_token("</slice>");
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tok_ov_img_start = {lookup_token("<image>")};
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tok_ov_img_end = {lookup_token("</image>")};
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tok_slices_start = {lookup_token("<slice>")};
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tok_slices_end = {lookup_token("</slice>")};
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tok_sli_img_start = tok_ov_img_start;
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tok_sli_img_end = tok_ov_img_end;
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tok_row_end = lookup_token("\n");
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tok_row_end = {lookup_token("\n")};
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tok_row_end_trail = false; // no trailing end-of-row token
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ov_img_first = true;
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@ -211,11 +214,11 @@ struct mtmd_context {
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// minicpmv 2.6 format:
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// <image> (overview) </image><slice> (slice) </slice><slice> (slice) </slice>\n ...
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slice_tmpl = MTMD_SLICE_TMPL_MINICPMV_2_6;
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tok_ov_img_start = lookup_token("<image>");
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tok_ov_img_end = lookup_token("</image>");
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tok_sli_img_start = lookup_token("<slice>");
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tok_sli_img_end = lookup_token("</slice>");
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tok_row_end = lookup_token("\n");
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tok_ov_img_start = {lookup_token("<image>")};
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tok_ov_img_end = {lookup_token("</image>")};
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tok_sli_img_start = {lookup_token("<slice>")};
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tok_sli_img_end = {lookup_token("</slice>")};
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tok_row_end = {lookup_token("\n")};
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tok_row_end_trail = false; // no trailing end-of-row token
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ov_img_first = true;
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@ -230,9 +233,9 @@ struct mtmd_context {
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// <|image|> (overview) <-- overview image is last
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// <|image_end|>
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slice_tmpl = MTMD_SLICE_TMPL_LLAMA4;
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tok_ov_img_start = lookup_token("<|image|>");
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tok_sli_img_mid = lookup_token("<|tile_x_separator|>");
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tok_row_end = lookup_token("<|tile_y_separator|>");
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tok_ov_img_start = {lookup_token("<|image|>")};
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tok_sli_img_mid = {lookup_token("<|tile_x_separator|>")};
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tok_row_end = {lookup_token("<|tile_y_separator|>")};
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tok_row_end_trail = true; // add trailing end-of-row token
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ov_img_first = false; // overview image is last
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}
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@ -245,8 +248,12 @@ struct mtmd_context {
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} else if (proj == PROJECTOR_TYPE_IDEFICS3) {
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// https://github.com/huggingface/transformers/blob/a42ba80fa520c784c8f11a973ca9034e5f859b79/src/transformers/models/idefics3/processing_idefics3.py#L192-L215
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img_beg = "<fake_token_around_image><global-img>";
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img_end = "<fake_token_around_image>";
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slice_tmpl = MTMD_SLICE_TMPL_IDEFICS3;
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tok_ov_img_start = {lookup_token("\n"), lookup_token("<fake_token_around_image>"), lookup_token("<global-img>")};
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tok_ov_img_end = {lookup_token("<fake_token_around_image>")};
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tok_row_end = {lookup_token("\n")};
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img_beg = "<fake_token_around_image>";
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sli_img_start_tmpl = "<fake_token_around_image><row_%d_col_%d>";
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} else if (proj == PROJECTOR_TYPE_PIXTRAL) {
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// https://github.com/huggingface/transformers/blob/1cd110c6cb6a6237614130c470e9a902dbc1a4bd/docs/source/en/model_doc/pixtral.md
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@ -504,6 +511,7 @@ struct mtmd_tokenizer {
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ctx->slice_tmpl == MTMD_SLICE_TMPL_MINICPMV_2_5
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|| ctx->slice_tmpl == MTMD_SLICE_TMPL_MINICPMV_2_6
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|| ctx->slice_tmpl == MTMD_SLICE_TMPL_LLAMA4
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|| ctx->slice_tmpl == MTMD_SLICE_TMPL_IDEFICS3
|
||||
) {
|
||||
const int n_col = batch_f32.grid_x;
|
||||
const int n_row = batch_f32.grid_y;
|
||||
|
|
@ -517,53 +525,45 @@ struct mtmd_tokenizer {
|
|||
|
||||
// add overview image (first)
|
||||
if (ctx->ov_img_first) {
|
||||
if (ctx->tok_ov_img_start != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_ov_img_start});
|
||||
}
|
||||
add_text(ctx->tok_ov_img_start);
|
||||
cur.entries.emplace_back(std::move(ov_chunk));
|
||||
if (ctx->tok_ov_img_end != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_ov_img_end});
|
||||
}
|
||||
add_text(ctx->tok_ov_img_end);
|
||||
}
|
||||
|
||||
// add slices (or tiles)
|
||||
if (!chunks.empty()) {
|
||||
GGML_ASSERT((int)chunks.size() == n_row * n_col);
|
||||
if (ctx->tok_slices_start != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_slices_start});
|
||||
}
|
||||
add_text(ctx->tok_slices_start);
|
||||
for (int y = 0; y < n_row; y++) {
|
||||
for (int x = 0; x < n_col; x++) {
|
||||
const bool is_last_in_row = (x == n_col - 1);
|
||||
if (ctx->tok_sli_img_start != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_sli_img_start});
|
||||
if (!ctx->tok_sli_img_start.empty()) {
|
||||
add_text(ctx->tok_sli_img_start);
|
||||
} else if (!ctx->sli_img_start_tmpl.empty()) {
|
||||
// If using a template to preceed a slice image
|
||||
const size_t sz = std::snprintf(nullptr, 0, ctx->sli_img_start_tmpl.c_str(), y+1, x+1) + 1;
|
||||
std::unique_ptr<char[]> buf(new char[sz]);
|
||||
std::snprintf(buf.get(), sz, ctx->sli_img_start_tmpl.c_str(), y+1, x+1);
|
||||
add_text(std::string(buf.get(), buf.get() + sz - 1), true);
|
||||
}
|
||||
cur.entries.emplace_back(std::move(chunks[y * n_col + x]));
|
||||
if (ctx->tok_sli_img_end != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_sli_img_end});
|
||||
}
|
||||
if (!is_last_in_row && ctx->tok_sli_img_mid != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_sli_img_mid});
|
||||
add_text(ctx->tok_sli_img_end);
|
||||
if (!is_last_in_row) {
|
||||
add_text(ctx->tok_sli_img_mid);
|
||||
}
|
||||
}
|
||||
if ((y != n_row - 1 || ctx->tok_row_end_trail) && ctx->tok_row_end != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_row_end});
|
||||
if ((y != n_row - 1 || ctx->tok_row_end_trail)) {
|
||||
add_text(ctx->tok_row_end);
|
||||
}
|
||||
}
|
||||
if (ctx->tok_slices_end != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_slices_end});
|
||||
}
|
||||
add_text(ctx->tok_slices_end);
|
||||
}
|
||||
|
||||
// add overview image (last)
|
||||
if (!ctx->ov_img_first) {
|
||||
if (ctx->tok_ov_img_start != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_ov_img_start});
|
||||
}
|
||||
add_text(ctx->tok_ov_img_start);
|
||||
cur.entries.emplace_back(std::move(ov_chunk));
|
||||
if (ctx->tok_ov_img_end != LLAMA_TOKEN_NULL) {
|
||||
add_text({ctx->tok_ov_img_end});
|
||||
}
|
||||
add_text(ctx->tok_ov_img_end);
|
||||
}
|
||||
|
||||
} else {
|
||||
|
|
@ -780,7 +780,9 @@ int32_t mtmd_encode(mtmd_context * ctx, const mtmd_image_tokens * image_tokens)
|
|||
ctx->image_embd_v.resize(image_tokens->n_tokens() * n_mmproj_embd);
|
||||
bool ok = false;
|
||||
|
||||
if (clip_is_llava(ctx_clip) || clip_is_minicpmv(ctx_clip) || clip_is_glm(ctx_clip)) {
|
||||
if (clip_is_llava(ctx_clip)
|
||||
|| clip_is_minicpmv(ctx_clip)
|
||||
|| clip_is_glm(ctx_clip)) {
|
||||
// TODO @ngxson : llava does not support batched encoding ; this should be fixed inside clip_image_batch_encode()
|
||||
const auto & entries = image_tokens->batch_f32.entries;
|
||||
for (size_t i = 0; i < entries.size(); i++) {
|
||||
|
|
|
|||
|
|
@ -69,6 +69,7 @@ add_test_vision "ggml-org/InternVL2_5-1B-GGUF:Q8_0"
|
|||
add_test_vision "ggml-org/InternVL3-1B-Instruct-GGUF:Q8_0"
|
||||
add_test_vision "ggml-org/Qwen2.5-Omni-3B-GGUF:Q4_K_M"
|
||||
add_test_vision "ggml-org/LFM2-VL-450M-GGUF:Q8_0"
|
||||
add_test_vision "ggml-org/granite-docling-258M-GGUF:Q8_0"
|
||||
|
||||
add_test_audio "ggml-org/ultravox-v0_5-llama-3_2-1b-GGUF:Q8_0"
|
||||
add_test_audio "ggml-org/Qwen2.5-Omni-3B-GGUF:Q4_K_M"
|
||||
|
|
|
|||
Loading…
Reference in New Issue