// if max_alibi_bias > 0 then apply ALiBi
static struct ggml_tensor * llm_build_kqv(
struct ggml_context * ctx,
- struct ggml_tensor * cur,
const llama_hparams & hparams,
const llama_kv_cache & kv,
struct ggml_tensor * wo,
struct ggml_tensor * kqv_merged = ggml_permute(ctx, kqv, 0, 2, 1, 3);
cb(kqv_merged, "kqv_merged", il);
- cur = ggml_cont_2d(ctx, kqv_merged, n_embd, n_tokens);
+ struct ggml_tensor * cur = ggml_cont_2d(ctx, kqv_merged, n_embd, n_tokens);
cb(cur, "kqv_merged_cont", il);
cur = ggml_mul_mat(ctx, wo, cur);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, cur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, NULL,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, -1.0f, cb, il);
cb(cur, "kqv_out", il);
// apply ALiBi for 13B model
const float max_alibi_bias = model.type == MODEL_13B ? 8.0f : -1.0f;
- cur = llm_build_kqv(ctx0, cur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, NULL,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, max_alibi_bias, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, attn_norm, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, NULL,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, -1.0f, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, cur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, model.layers[il].bo,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, -1.0f, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
// TODO: not tested, could be broken
- cur = llm_build_kqv(ctx0, Q, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, model.layers[il].bo,
Q, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, -1.0f, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, Qcur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, NULL,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, 8.0f, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, Qcur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, model.layers[il].bo,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, 8.0f, cb, il);
cb(cur, "kqv_out", il);
llm_build_kv_store(ctx0, hparams, kv_self, gf, Kcur, Vcur, n_ctx, n_tokens, kv_head, cb, il);
- cur = llm_build_kqv(ctx0, Qcur, hparams, kv_self,
+ cur = llm_build_kqv(ctx0, hparams, kv_self,
model.layers[il].wo, NULL,
Qcur, KQ_scale, KQ_mask, n_ctx, n_tokens, n_kv, hparams.f_max_alibi_bias, cb, il);
cb(cur, "kqv_out", il);