Brunobkr/llama.cpp_AlgMor24_github

1#include "models.h"2 3void llama_model_plamo3::load_arch_hparams(llama_model_loader & ml) {4    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);5    const bool found_swa = ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa, false);6    if (found_swa && hparams.n_swa > 0) {7        hparams.swa_type = LLAMA_SWA_TYPE_STANDARD;8        ml.get_key(LLM_KV_ROPE_FREQ_BASE_SWA, hparams.rope_freq_base_train_swa, false);9        uint32_t swa_period = 8;10        ml.get_key_or_arr(LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, swa_period, false);11        hparams.set_swa_pattern(swa_period);12    } else {13        hparams.swa_type = LLAMA_SWA_TYPE_NONE;14    }15 16    switch (hparams.n_layer()) {17        case 24: type = LLM_TYPE_2B; break;18        default: type = LLM_TYPE_UNKNOWN;19    }20}21 22void llama_model_plamo3::load_arch_tensors(llama_model_loader &) {23    LLAMA_LOAD_LOCALS;24 25    const int64_t head_dim_q = hparams.n_embd_head_k();26    const int64_t head_dim_v = hparams.n_embd_head_v();27 28    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);29 30    output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);31    output      = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);32    if (output == NULL) {33        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);34    }35 36    for (int i = 0; i < n_layer; ++i) {37        auto & layer = layers[i];38 39        const int64_t num_attention_heads = hparams.n_head(i);40        const int64_t num_key_value_heads = hparams.n_head_kv(i);41        const int64_t q_proj_dim = num_attention_heads * head_dim_q;42        const int64_t k_proj_dim = num_key_value_heads * head_dim_q;43        const int64_t v_proj_dim = num_key_value_heads * head_dim_v;44        const int64_t n_ff_cur   = hparams.n_ff(i);45 46        layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);47        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i),48                {n_embd,q_proj_dim + k_proj_dim + v_proj_dim}, 0);49        layer.attn_q_norm = create_tensor(tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {head_dim_q}, 0);50        layer.attn_k_norm = create_tensor(tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {head_dim_q}, 0);51        layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {num_attention_heads * head_dim_v, n_embd}, 0);52        layer.attn_post_norm = create_tensor(tn(LLM_TENSOR_ATTN_POST_NORM, i), {n_embd}, 0);53 54        layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);55        layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, i), {n_embd}, 0);56 57        layer.ffn_up   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff_cur * 2}, 0);58        layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff_cur, n_embd}, 0);59    }60}61 62std::unique_ptr<llm_graph_context> llama_model_plamo3::build_arch_graph(const llm_graph_params & params) const {63    if (hparams.swa_type != LLAMA_SWA_TYPE_NONE) {64        return std::make_unique<graph<true>> (*this, params);65    } else {66        return std::make_unique<graph<false>>(*this, params);67    }68}69 70template <bool iswa>71llama_model_plamo3::graph<iswa>::graph(const llama_model & model, const llm_graph_params & params) :72    llm_graph_context(params) {73    const int64_t head_dim_q = hparams.n_embd_head_k();74    const int64_t head_dim_v = hparams.n_embd_head_v();75 76    ggml_tensor * cur;77    ggml_tensor * inpL = build_inp_embd(model.tok_embd);78    ggml_tensor * inp_pos = build_inp_pos();79 80    using inp_attn_type = std::conditional_t<iswa, llm_graph_input_attn_kv_iswa, llm_graph_input_attn_kv>;81    inp_attn_type * inp_attn = nullptr;82 83    if constexpr (iswa) {84        inp_attn = build_attn_inp_kv_iswa();85    } else {86        inp_attn = build_attn_inp_kv();87    }88 89    ggml_tensor * inp_out_ids = build_inp_out_ids();90 91    for (int il = 0; il < n_layer; ++il) {92        ggml_tensor * residual = inpL;93 94        float freq_base_l  = 0.0f;95        float freq_scale_l = 0.0f;96        if constexpr (iswa) {97            freq_base_l  = model.get_rope_freq_base (cparams, il);98            freq_scale_l = model.get_rope_freq_scale(cparams, il);99        } else {100            freq_base_l  = freq_base;101            freq_scale_l = freq_scale;102        }103 104        cur = build_norm(inpL, model.layers[il].attn_norm, NULL, LLM_NORM_RMS, il);105        cb(cur, "attn_norm", il);106 107        ggml_tensor * qkv = build_lora_mm(model.layers[il].wqkv, cur);108        cb(cur, "wqkv", il);109 110        const int32_t n_head    = hparams.n_head(il);111        const int32_t n_head_kv = hparams.n_head_kv(il);112 113        const int64_t q_offset = 0;114        const int64_t k_offset = head_dim_q * n_head;115        const int64_t v_offset = k_offset + head_dim_q * n_head_kv;116 117        ggml_tensor * Qcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head, n_tokens,118                head_dim_q * sizeof(float), qkv->nb[1], q_offset * ggml_element_size(qkv));119        ggml_tensor * Kcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head_kv, n_tokens,120                head_dim_q * sizeof(float), qkv->nb[1], k_offset * ggml_element_size(qkv));121        ggml_tensor * Vcur = ggml_view_3d(ctx0, qkv, head_dim_v, n_head_kv, n_tokens,122                head_dim_v * sizeof(float), qkv->nb[1], v_offset * ggml_element_size(qkv));123 124        cb(Qcur, "Qcur", il);125        cb(Kcur, "Kcur", il);126        cb(Vcur, "Vcur", il);127 128        Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il);129        cb(Qcur, "attn_q_norm", il);130        Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il);131        cb(Kcur, "attn_k_norm", il);132 133        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr,134                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,135                ext_factor, attn_factor, beta_fast, beta_slow);136        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr,137                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,138                ext_factor, attn_factor, beta_fast, beta_slow);139 140        const float attn_scale = 1.0f / sqrtf(float(head_dim_q));141 142        cur = build_attn(inp_attn,143                model.layers[il].wo, NULL, model.layers[il].wo_s,144                Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, attn_scale, il);145        cb(cur, "attn_out", il);146 147        if (il == n_layer - 1 && inp_out_ids) {148            cur      = ggml_get_rows(ctx0, cur, inp_out_ids);149            residual = ggml_get_rows(ctx0, residual, inp_out_ids);150        }151 152        cur = build_norm(cur, model.layers[il].attn_post_norm, NULL, LLM_NORM_RMS, il);153        cb(cur, "attn_post_norm", il);154 155        cur = ggml_add(ctx0, cur, residual);156        cb(cur, "attn_residual", il);157 158        residual = cur;159 160        cur = build_norm(cur, model.layers[il].ffn_norm, NULL, LLM_NORM_RMS, il);161        cb(cur, "ffn_norm", il);162 163        cur = build_ffn(cur,164                model.layers[il].ffn_up,   NULL, NULL,165                NULL,                      NULL, NULL,166                model.layers[il].ffn_down, NULL, NULL,167                NULL,168                LLM_FFN_SWIGLU, LLM_FFN_SEQ, il);169        cb(cur, "ffn_out", il);170 171        cur = build_norm(cur, model.layers[il].ffn_post_norm, NULL, LLM_NORM_RMS, il);172        cb(cur, "ffn_post_norm", il);173 174        cur = ggml_add(ctx0, cur, residual);175        cb(cur, "ffn_residual", il);176 177        cur = build_cvec(cur, il);178        cb(cur, "l_out", il);179 180        // input for next layer181        inpL = cur;182    }183 184    cur = inpL;185 186    cur = build_norm(cur, model.output_norm, NULL, LLM_NORM_RMS, -1);187    res->t_embd = cur;188 189    cur = build_lora_mm(model.output, cur, model.output_s);190    res->t_logits = cur;191 192    ggml_build_forward_expand(gf, cur);193}194 195// Explicit template instantiations196template struct llama_model_plamo3::graph<false>;197template struct llama_model_plamo3::graph<true>;198