#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);
cur = build_norm(cur, model.mm_pre_norm_w, nullptr, NORM_TYPE_RMS, eps, -1);
cur = ggml_reshape_3d(ctx0, cur, n_embd, pw, ph);
cur = ggml_permute(ctx0, cur, 2, 0, 1, 3);
cur = ggml_cont(ctx0, cur);
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];
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);
cur = ggml_permute(ctx0, cur, 1, 2, 0, 3);
cur = ggml_cont_2d(ctx0, cur, idim, (ow + 1) * oh);
cur = build_mm(model.mm_model_proj, cur);
if (model.mm_model_proj_b) {
cur = ggml_add(ctx0, cur, model.mm_model_proj_b);
}
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;
}