1#include "models.h"
 2
 3llm_build_rwkv6qwen2::llm_build_rwkv6qwen2(const llama_model & model, const llm_graph_params & params) : llm_build_rwkv6_base(model, params) {
 4    GGML_ASSERT(n_embd == hparams.n_embd_r());
 5
 6    ggml_tensor * cur;
 7    ggml_tensor * inpL;
 8
 9    inpL = build_inp_embd(model.tok_embd);
10
11    auto * rs_inp = build_rs_inp();
12
13    const auto n_embd = hparams.n_embd;
14    const auto n_seq_tokens = ubatch.n_seq_tokens;
15    const auto n_seqs = ubatch.n_seqs;
16
17    ggml_tensor * inp_out_ids = build_inp_out_ids();
18
19    for (int il = 0; il < n_layer; ++il) {
20        const llama_layer * layer = &model.layers[il];
21        inpL = ggml_reshape_3d(ctx0, inpL, n_embd, n_seq_tokens, n_seqs);
22
23        ggml_tensor * token_shift = build_rwkv_token_shift_load(rs_inp, ubatch, il);
24
25        ggml_tensor * att_norm = build_norm(inpL, layer->attn_norm, layer->attn_norm_b, LLM_NORM_RMS, il);
26        cb(att_norm, "attn_norm", il);
27
28        ggml_tensor * x_prev = ggml_concat(
29                ctx0,
30                token_shift,
31                ggml_view_3d(ctx0, att_norm, n_embd, n_seq_tokens - 1, n_seqs, att_norm->nb[1], att_norm->nb[2], 0),
32                1
33                );
34
35        cur = build_rwkv6_time_mix(rs_inp, att_norm, x_prev, ubatch, il);
36
37        token_shift = ggml_view_3d(ctx0, att_norm, n_embd, 1, n_seqs, att_norm->nb[1], att_norm->nb[2], (n_seq_tokens-1)*n_embd*ggml_element_size(att_norm));
38        ggml_build_forward_expand(gf, build_rwkv_token_shift_store(token_shift, ubatch, il));
39
40        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);
41        cb(ffn_inp, "ffn_inp", il);
42
43        cur     = ggml_reshape_2d(ctx0, cur,     n_embd, n_tokens);
44        ffn_inp = ggml_reshape_2d(ctx0, ffn_inp, n_embd, n_tokens);
45
46        if (il == n_layer - 1 && inp_out_ids) {
47            cur     = ggml_get_rows(ctx0, cur,     inp_out_ids);
48            ffn_inp = ggml_get_rows(ctx0, ffn_inp, inp_out_ids);
49        }
50
51        // feed-forward network
52        cur = build_norm(ffn_inp,
53                model.layers[il].ffn_norm, NULL,
54                LLM_NORM_RMS, il);
55        cb(cur, "ffn_norm", il);
56
57        cur = build_ffn(cur,
58                model.layers[il].ffn_up,   NULL, NULL,
59                model.layers[il].ffn_gate, NULL, NULL,
60                model.layers[il].ffn_down, NULL, NULL,
61                NULL,
62                LLM_FFN_SILU, LLM_FFN_PAR, il);
63        cb(cur, "ffn_out", il);
64
65        cur = ggml_add(ctx0, cur, ffn_inp);
66
67        cur = build_cvec(cur, il);
68        cb(cur, "l_out", il);
69
70        // input for next layer
71        inpL = cur;
72    }
73
74    cur = inpL;
75    cur = build_norm(cur, model.output_norm, model.output_norm_b, LLM_NORM_RMS, -1);
76
77    cb(cur, "result_norm", -1);
78    res->t_embd = cur;
79
80    cur = build_lora_mm(model.output, cur);
81
82    cb(cur, "result_output", -1);
83    res->t_logits = cur;
84
85    ggml_build_forward_expand(gf, cur);
86}