mtmd, model : merge HunyuanOCR into HunyuanVL and fix OCR vision precision (#23329)

- HunyuanOCR shares the same HF arch and vision layout as HunyuanVL butwas split into a separate path that skipped the +0.1 bilinear sampler used by the HF reference.
- Collapse OCR into the HUNYUANVL projector + HUNYUAN_VL text arch
This commit is contained in:
wendadawen
2026-05-21 00:35:37 +02:00
committed by GitHub
parent 3a479c9132
commit 6a257d4463
15 changed files with 58 additions and 134 deletions
@@ -1,25 +1,15 @@
#include "models.h"
ggml_cgraph * clip_graph_hunyuanocr::build() {
ggml_cgraph * clip_graph_hunyuanvl::build() {
const int merge = hparams.n_merge;
const int pw = n_patches_x;
const int ph = n_patches_y;
// Position embedding interpolation.
// HunyuanVL needs scale factors sf=(target+0.1)/n_grid, which the standard
// ggml_interpolate cannot express. To avoid adding a new ggml op, the
// resize is computed on CPU in clip_image_batch_encode and uploaded here
// as a graph input (named "hunyuanvl_pos_embd").
// HunyuanOCR uses the same square layout and the standard ratio-based
// interpolation provided by resize_position_embeddings().
ggml_tensor * pos_embd = nullptr;
if (proj_type == PROJECTOR_TYPE_HUNYUANVL && model.position_embeddings) {
pos_embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, ph * pw);
ggml_set_name(pos_embd, "hunyuanvl_pos_embd");
ggml_set_input(pos_embd);
} else {
pos_embd = resize_position_embeddings(GGML_SCALE_MODE_BILINEAR);
}
// position embedding: declared as a graph input, filled on CPU
// by clip_image_batch_encode (see PROJECTOR_TYPE_HUNYUANVL branch there).
ggml_tensor * pos_embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, ph * pw);
ggml_set_name(pos_embd, "hunyuanvl_pos_embd");
ggml_set_input(pos_embd);
ggml_tensor * inp = build_inp();
ggml_tensor * cur = build_vit(inp, n_patches, NORM_TYPE_NORMAL, hparams.ffn_op, pos_embd, nullptr);
+2 -2
View File
@@ -142,8 +142,8 @@ struct clip_graph_glm4v : clip_graph {
ggml_cgraph * build() override;
};
struct clip_graph_hunyuanocr : clip_graph {
clip_graph_hunyuanocr(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
struct clip_graph_hunyuanvl : clip_graph {
clip_graph_hunyuanvl(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
ggml_cgraph * build() override;
};