| | #include "models.h"
|
| |
|
| | ggml_cgraph * clip_graph_kimivl::build() {
|
| |
|
| | ggml_tensor * pos_h = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_patches);
|
| | ggml_set_name(pos_h, "pos_h");
|
| | ggml_set_input(pos_h);
|
| |
|
| | ggml_tensor * pos_w = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_patches);
|
| | ggml_set_name(pos_w, "pos_w");
|
| | ggml_set_input(pos_w);
|
| |
|
| | ggml_tensor * learned_pos_embd = resize_position_embeddings();
|
| |
|
| |
|
| | auto add_pos = [&](ggml_tensor * cur, const clip_layer &) {
|
| |
|
| | return build_rope_2d(ctx0, cur, pos_w, pos_h, hparams.rope_theta, false);
|
| | };
|
| |
|
| | ggml_tensor * inp = build_inp();
|
| | ggml_tensor * cur = build_vit(
|
| | inp, n_patches,
|
| | NORM_TYPE_NORMAL,
|
| | hparams.ffn_op,
|
| | learned_pos_embd,
|
| | add_pos);
|
| |
|
| | cb(cur, "vit_out", -1);
|
| |
|
| | {
|
| |
|
| | const int scale_factor = model.hparams.n_merge;
|
| | cur = build_patch_merge_permute(cur, scale_factor);
|
| |
|
| |
|
| | int proj_inp_dim = cur->ne[0];
|
| | cur = ggml_view_2d(ctx0, cur,
|
| | n_embd, cur->ne[1] * scale_factor * scale_factor,
|
| | ggml_row_size(cur->type, n_embd), 0);
|
| | cur = ggml_norm(ctx0, cur, 1e-5);
|
| | cur = ggml_mul(ctx0, cur, model.mm_input_norm_w);
|
| | cur = ggml_add(ctx0, cur, model.mm_input_norm_b);
|
| | cur = ggml_view_2d(ctx0, cur,
|
| | proj_inp_dim, cur->ne[1] / scale_factor / scale_factor,
|
| | ggml_row_size(cur->type, proj_inp_dim), 0);
|
| | cb(cur, "proj_inp_normed", -1);
|
| |
|
| |
|
| | cur = build_ffn(cur,
|
| | model.mm_1_w, model.mm_1_b,
|
| | nullptr, nullptr,
|
| | model.mm_2_w, model.mm_2_b,
|
| | FFN_GELU,
|
| | -1);
|
| | cb(cur, "proj_out", -1);
|
| | }
|
| |
|
| |
|
| | ggml_build_forward_expand(gf, cur);
|
| |
|
| | return gf;
|
| | }
|
| |
|