af76639f72
* HunyuanOCR: add support for text and vision models - Add HunyuanOCR vision projector (perceiver-based) with Conv2d merge - Add separate HUNYUAN_OCR chat template (content-before-role format) - Handle HunyuanOCR's invalid pad_token_id=-1 in converter - Fix EOS/EOT token IDs from generation_config.json - Support xdrope RoPE scaling type - Add tensor mappings for perceiver projector (mm.before_rms, mm.after_rms, etc.) - Register HunYuanVLForConditionalGeneration for both text and mmproj conversion * fix proper mapping * Update gguf-py/gguf/tensor_mapping.py Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> * Update tools/mtmd/clip.cpp Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> * address comments * update * Fix typecheck * Update convert_hf_to_gguf.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Update convert_hf_to_gguf.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Update convert_hf_to_gguf.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Update convert_hf_to_gguf.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> --------- Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
59 lines
2.2 KiB
C++
59 lines
2.2 KiB
C++
#include "models.h"
|
|
|
|
ggml_cgraph * clip_graph_hunyuanocr::build() {
|
|
const int merge = hparams.n_merge;
|
|
const int pw = n_patches_x;
|
|
const int ph = n_patches_y;
|
|
|
|
ggml_tensor * pos_embd = resize_position_embeddings(GGML_SCALE_MODE_BILINEAR);
|
|
|
|
ggml_tensor * inp = build_inp();
|
|
ggml_tensor * cur = build_vit(inp, n_patches, NORM_TYPE_NORMAL, hparams.ffn_op, pos_embd, nullptr);
|
|
|
|
// perceiver projector
|
|
cur = build_norm(cur, model.mm_pre_norm_w, nullptr, NORM_TYPE_RMS, eps, -1);
|
|
|
|
// [C, W*H] -> [W, H, C] for conv2d
|
|
cur = ggml_reshape_3d(ctx0, cur, n_embd, pw, ph);
|
|
cur = ggml_permute(ctx0, cur, 2, 0, 1, 3);
|
|
cur = ggml_cont(ctx0, cur);
|
|
|
|
// Conv2d(1152->2304, k=2, s=2) + GELU + Conv2d(2304->4608, k=1, s=1)
|
|
cur = ggml_conv_2d(ctx0, model.mm_0_w, cur, merge, merge, 0, 0, 1, 1);
|
|
if (model.mm_0_b) {
|
|
cur = ggml_add(ctx0, cur, ggml_reshape_3d(ctx0, model.mm_0_b, 1, 1, model.mm_0_b->ne[0]));
|
|
}
|
|
cur = ggml_gelu(ctx0, cur);
|
|
cur = ggml_conv_2d(ctx0, model.mm_1_w, cur, 1, 1, 0, 0, 1, 1);
|
|
if (model.mm_1_b) {
|
|
cur = ggml_add(ctx0, cur, ggml_reshape_3d(ctx0, model.mm_1_b, 1, 1, model.mm_1_b->ne[0]));
|
|
}
|
|
|
|
const int ow = pw / merge;
|
|
const int oh = ph / merge;
|
|
const int idim = (int)cur->ne[2]; // OC = 4608
|
|
|
|
// append newline along W (dim 0)
|
|
ggml_tensor * nl = ggml_reshape_4d(ctx0, model.image_newline, 1, 1, idim, 1);
|
|
nl = ggml_repeat_4d(ctx0, nl, 1, oh, idim, 1);
|
|
cur = ggml_concat(ctx0, cur, nl, 0);
|
|
|
|
// [OW+1, OH, OC] -> [OC, (OW+1)*OH]
|
|
cur = ggml_permute(ctx0, cur, 1, 2, 0, 3);
|
|
cur = ggml_cont_2d(ctx0, cur, idim, (ow + 1) * oh);
|
|
|
|
// project to LLM hidden size
|
|
cur = build_mm(model.mm_model_proj, cur);
|
|
if (model.mm_model_proj_b) {
|
|
cur = ggml_add(ctx0, cur, model.mm_model_proj_b);
|
|
}
|
|
|
|
// wrap with begin/end tokens
|
|
cur = ggml_concat(ctx0, ggml_reshape_2d(ctx0, model.mm_img_begin, model.mm_img_begin->ne[0], 1), cur, 1);
|
|
cur = ggml_concat(ctx0, cur, ggml_reshape_2d(ctx0, model.mm_img_end, model.mm_img_end->ne[0], 1), 1);
|
|
|
|
cur = build_norm(cur, model.mm_post_norm_w, nullptr, NORM_TYPE_RMS, eps, -1);
|
|
|
|
ggml_build_forward_expand(gf, cur);
|
|
return gf;
|
|
}
|