Repository: ggerganov/llama.cpp
File: src/models/plamo3.cpp (C++)

Code before:
        const int32_t n_head_kv = hparams.n_head_kv(il);

        const int64_t q_offset = 0;
        const int64_t k_offset = head_dim_q * n_head;
        const int64_t v_offset = k_offset + head_dim_q * n_head_kv;

        ggml_tensor * Qcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head, n_tokens,
                head_dim_q * sizeof(float), qkv->nb[1], q_offset * ggml_element_size(qkv));
        ggml_tensor * Kcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head_kv, n_tokens,
                head_dim_q * sizeof(float), qkv->nb[1], k_offset * ggml_element_size(qkv));
        ggml_tensor * Vcur = ggml_view_3d(ctx0, qkv, head_dim_v, n_head_kv, n_tokens,
                head_dim_v * sizeof(float), qkv->nb[1], v_offset * ggml_element_size(qkv));

        cb(Qcur, "Qcur", il);
        cb(Kcur, "Kcur", il);
        cb(Vcur, "Vcur", il);

        Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il);
        cb(Qcur, "attn_q_norm", il);
        Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il);
        cb(Kcur, "attn_k_norm", il);

        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, rope_factors,
                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
                ext_factor, attn_factor, beta_fast, beta_slow);
        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, rope_factors,
                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
                ext_factor, attn_factor, beta_fast, beta_slow);

        const float attn_scale = 1.0f / sqrtf(float(head_dim_q));

        cur = build_attn(inp_attn,
                model.layers[il].wo, NULL,
                Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, attn_scale, il);
        cb(cur, "attn_out", il);

        if (il == n_layer - 1 && inp_out_ids) {
            cur      = ggml_get_rows(ctx0, cur, inp_out_ids);
            residual = ggml_get_rows(ctx0, residual, inp_out_ids);
        }

        cur = build_norm(cur, model.layers[il].attn_post_norm, NULL, LLM_NORM_RMS, il);
        cb(cur, "attn_post_norm", il);

        cur = ggml_add(ctx0, cur, residual);
        cb(cur, "attn_residual", il);

        residual = cur;

        cur = build_norm(cur, model.layers[il].ffn_norm, NULL, LLM_NORM_RMS, il);
        cb(cur, "ffn_norm", il);

Review comment (bug):
```suggestion
        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr,
                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
                ext_factor, attn_factor, beta_fast, beta_slow);
        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr,
```

Code after:
        cb(cur, "attn_norm", il);

        ggml_tensor * qkv = build_lora_mm(model.layers[il].wqkv, cur);
        cb(cur, "wqkv", il);

        const int32_t n_head    = hparams.n_head(il);
        const int32_t n_head_kv = hparams.n_head_kv(il);

        const int64_t q_offset = 0;
        const int64_t k_offset = head_dim_q * n_head;
        const int64_t v_offset = k_offset + head_dim_q * n_head_kv;

        ggml_tensor * Qcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head, n_tokens,
                head_dim_q * sizeof(float), qkv->nb[1], q_offset * ggml_element_size(qkv));
        ggml_tensor * Kcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head_kv, n_tokens,
                head_dim_q * sizeof(float), qkv->nb[1], k_offset * ggml_element_size(qkv));
        ggml_tensor * Vcur = ggml_view_3d(ctx0, qkv, head_dim_v, n_head_kv, n_tokens,
                head_dim_v * sizeof(float), qkv->nb[1], v_offset * ggml_element_size(qkv));

        cb(Qcur, "Qcur", il);
        cb(Kcur, "Kcur", il);
        cb(Vcur, "Vcur", il);

        Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il);
        cb(Qcur, "attn_q_norm", il);
        Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il);
        cb(Kcur, "attn_k_norm", il);

        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr,
                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
                ext_factor, attn_factor, beta_fast, beta_slow);
        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr,
                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
                ext_factor, attn_factor, beta_fast, beta_slow);

        const float attn_scale = 1.0f / sqrtf(float(head_dim_q));

        cur = build_attn(inp_attn,
                model.layers[il].wo, NULL,
                Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, attn_scale, il);
        cb(cur, "attn_out", il);

        if (il == n_layer - 1 && inp_out_ids) {
            cur      = ggml_get_rows(ctx0, cur, inp_out_ids);
            residual = ggml_get_rows(ctx0, residual, inp_out_ids);
        }

        cur = build_norm(cur, model.layers[il].attn_post_norm, NULL, LLM_NORM_RMS, il);
        cb(cur, "attn_post_norm", il);

        cur = ggml_add(ctx0, cur, residual);