| File: | root/firefox-clang/third_party/llama.cpp/src/models/eurobert.cpp |
| Warning: | line 55, column 23 Value stored to 'cur' during its initialization is never read |
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| 1 | #include "models.h" |
| 2 | |
| 3 | void llama_model_eurobert::load_arch_hparams(llama_model_loader & ml) { |
| 4 | ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps); |
| 5 | |
| 6 | if (hparams.n_layer() == 12) { |
| 7 | type = LLM_TYPE_SMALL; // 0.2B |
| 8 | } |
| 9 | } |
| 10 | |
| 11 | void llama_model_eurobert::load_arch_tensors(llama_model_loader &) { |
| 12 | LLAMA_LOAD_LOCALSconst int n_layer = hparams.n_layer(); (void)(n_layer); const int n_layer_all = hparams.n_layer_all; (void)(n_layer_all); const int n_layer_nextn = hparams.n_layer_nextn; (void)(n_layer_nextn ); const int64_t n_head = hparams.n_head(); (void)(n_head); const int64_t n_head_kv = hparams.n_head_kv(); (void)(n_head_kv); const int64_t n_embd = hparams.n_embd; (void)(n_embd); const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(); (void)(n_embd_k_gqa); const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa(); (void)( n_embd_v_gqa); const int64_t n_embd_head_k = hparams.n_embd_head_k (); (void)(n_embd_head_k); const int64_t n_embd_head_v = hparams .n_embd_head_v(); (void)(n_embd_head_v); const int64_t n_ff = hparams.n_ff(); (void)(n_ff); const int64_t n_embd_gqa = n_embd_v_gqa ; (void)(n_embd_gqa); const int64_t n_vocab = vocab.n_tokens( ); (void)(n_vocab); const int64_t n_token_types = vocab.n_token_types (); (void)(n_token_types); const int64_t n_rot = hparams.n_rot (); (void)(n_rot); const int64_t n_expert = hparams.n_expert; (void)(n_expert); const int64_t n_expert_used = hparams.n_expert_used ; (void)(n_expert_used); const int64_t n_ctx_train = hparams. n_ctx_train; (void)(n_ctx_train);; |
| 13 | |
| 14 | tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0); |
| 15 | |
| 16 | output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0); |
| 17 | |
| 18 | for (int i = 0; i < n_layer; ++i) { |
| 19 | auto & layer = layers[i]; |
| 20 | |
| 21 | layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0); |
| 22 | |
| 23 | create_tensor_qkv(layer, i, n_embd, n_embd, n_embd_gqa, n_embd_gqa, 0); |
| 24 | layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0); |
| 25 | |
| 26 | layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0); |
| 27 | |
| 28 | layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, 0); |
| 29 | layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, 0); |
| 30 | layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0); |
| 31 | } |
| 32 | } |
| 33 | |
| 34 | std::unique_ptr<llm_graph_context> llama_model_eurobert::build_arch_graph(const llm_graph_params & params) const { |
| 35 | return std::make_unique<graph>(*this, params); |
| 36 | } |
| 37 | |
| 38 | llama_model_eurobert::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) { |
| 39 | const int64_t n_embd_head = hparams.n_embd_head_v(); |
| 40 | |
| 41 | GGML_ASSERT(n_embd_head == hparams.n_embd_head_k())if (!(n_embd_head == hparams.n_embd_head_k())) ggml_abort("/root/firefox-clang/third_party/llama.cpp/src/models/eurobert.cpp" , 41, "GGML_ASSERT(%s) failed", "n_embd_head == hparams.n_embd_head_k()" ); |
| 42 | |
| 43 | ggml_tensor * cur; |
| 44 | ggml_tensor * inpL; |
| 45 | ggml_tensor * inp_pos = build_inp_pos(); |
| 46 | |
| 47 | inpL = build_inp_embd(model.tok_embd); |
| 48 | cb(inpL, "inp_embd", -1); |
| 49 | |
| 50 | auto * inp_attn = build_attn_inp_no_cache(); |
| 51 | |
| 52 | ggml_tensor * inp_out_ids = build_inp_out_ids(); |
| 53 | |
| 54 | for (int il = 0; il < n_layer; ++il) { |
| 55 | ggml_tensor * cur = inpL; |
Value stored to 'cur' during its initialization is never read | |
| 56 | |
| 57 | cur = build_norm(inpL, |
| 58 | model.layers[il].attn_norm, NULL__null, |
| 59 | LLM_NORM_RMS, il); |
| 60 | |
| 61 | { |
| 62 | auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur, |
| 63 | n_embd_head, n_head, n_head_kv, il); |
| 64 | |
| 65 | Qcur = ggml_rope_ext( |
| 66 | ctx0, Qcur, inp_pos, nullptr, |
| 67 | n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, |
| 68 | ext_factor, attn_factor, beta_fast, beta_slow |
| 69 | ); |
| 70 | |
| 71 | Kcur = ggml_rope_ext( |
| 72 | ctx0, Kcur, inp_pos, nullptr, |
| 73 | n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, |
| 74 | ext_factor, attn_factor, beta_fast, beta_slow |
| 75 | ); |
| 76 | |
| 77 | cb(Qcur, "Qcur", il); |
| 78 | cb(Kcur, "Kcur", il); |
| 79 | cb(Vcur, "Vcur", il); |
| 80 | |
| 81 | cur = build_attn(inp_attn, |
| 82 | model.layers[il].wo, nullptr, model.layers[il].wo_s, |
| 83 | Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il); |
| 84 | cb(cur, "kqv_out", il); |
| 85 | } |
| 86 | |
| 87 | if (il == n_layer - 1 && inp_out_ids) { |
| 88 | cur = ggml_get_rows(ctx0, cur, inp_out_ids); |
| 89 | inpL = ggml_get_rows(ctx0, inpL, inp_out_ids); |
| 90 | } |
| 91 | |
| 92 | cur = ggml_add(ctx0, cur, inpL); |
| 93 | |
| 94 | ggml_tensor * ffn_inp = cur; |
| 95 | cb(ffn_inp, "ffn_inp", il); |
| 96 | |
| 97 | cur = build_norm(ffn_inp, |
| 98 | model.layers[il].ffn_norm, NULL__null, |
| 99 | LLM_NORM_RMS, il); |
| 100 | cb(cur, "ffn_norm", il); |
| 101 | |
| 102 | cur = build_ffn(cur, |
| 103 | model.layers[il].ffn_up, NULL__null, NULL__null, |
| 104 | model.layers[il].ffn_gate, NULL__null, NULL__null, |
| 105 | model.layers[il].ffn_down, NULL__null, NULL__null, |
| 106 | NULL__null, LLM_FFN_SILU, LLM_FFN_PAR, il); |
| 107 | cb(cur, "ffn_out", il); |
| 108 | |
| 109 | cur = ggml_add(ctx0, cur, ffn_inp); |
| 110 | |
| 111 | // input for next layer |
| 112 | inpL = cur; |
| 113 | } |
| 114 | cur = inpL; |
| 115 | |
| 116 | cur = build_norm(cur, |
| 117 | model.output_norm, NULL__null, |
| 118 | LLM_NORM_RMS, -1); |
| 119 | |
| 120 | cb(cur, "result_embd", -1); |
| 121 | res->t_embd = cur; |
| 122 | |
| 123 | ggml_build_forward_expand(gf, cur); |
| 124 | } |