ikawrakow/ik_llama.cpp
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bitnet(scale in a separate tensor): replace ggml_mul with ggml_scale

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This recovers part of the performance loss. On Metal TG-128 is now
92 t/s, still short of the ~100 t/s with scales applied on the fly.
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Kawrakow
2024-06-19 17:14:42 +02:00
parent 3c5cd34a05
commit f024804b9a
1 changed files with 8 additions and 8 deletions
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llama.cpp
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@@ -11826,7 +11826,7 @@ struct llm_build_context {
{
// compute Q and K and RoPE them
struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
Qcur = ggml_mul(ctx0, Qcur, model.layers[il].wq_scale);
Qcur = ggml_scale(ctx0, Qcur, *(const float *)model.layers[il].wq_scale->data);
cb(Qcur, "Qcur", il);
if (model.layers[il].bq) {
Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
@@ -11835,7 +11835,7 @@ struct llm_build_context {
// B1.K
struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
Kcur = ggml_mul(ctx0, Kcur, model.layers[il].wk_scale);
Kcur = ggml_scale(ctx0, Kcur, *(const float *)model.layers[il].wk_scale->data);
cb(Kcur, "Kcur", il);
if (model.layers[il].bk) {
Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
@@ -11844,7 +11844,7 @@ struct llm_build_context {
// B1.V
struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
Vcur = ggml_mul(ctx0, Vcur, model.layers[il].wv_scale);
Vcur = ggml_scale(ctx0, Vcur, *(const float *)model.layers[il].wv_scale->data);
cb(Vcur, "Vcur", il);
if (model.layers[il].bv) {
Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -11938,7 +11938,7 @@ struct llm_build_context {
ggml_build_forward_expand(gf, cur_attn);
cur = ggml_mul_mat(ctx0, model.layers[il].wo, cur_attn);
cur = ggml_mul(ctx0, cur, model.layers[il].wo_scale);
cur = ggml_scale(ctx0, cur, *(const float *)model.layers[il].wo_scale->data);
cb(cur, "kqv_out", il);
}
@@ -11961,12 +11961,12 @@ struct llm_build_context {
cb(cur, "ffn_norm", il);
struct ggml_tensor *tmp = ggml_mul_mat(ctx0, model.layers[il].ffn_up, cur);
tmp = ggml_mul(ctx0, tmp, model.layers[il].ffn_up_scale);
tmp = ggml_scale(ctx0, tmp, *(const float *)model.layers[il].ffn_up_scale->data);
cb(tmp, "ffn_up", il);
cur = ggml_mul_mat(ctx0, model.layers[il].ffn_gate, cur);
cur = ggml_mul(ctx0, cur, model.layers[il].ffn_gate_scale);
cur = ggml_scale(ctx0, cur, *(const float *)model.layers[il].ffn_gate_scale->data);
cb(cur, "ffn_gate", il);
@@ -11983,7 +11983,7 @@ struct llm_build_context {
cb(cur, "ffn_sub_norm", il);
cur = ggml_mul_mat(ctx0, model.layers[il].ffn_down, cur);
cur = ggml_mul(ctx0, cur, model.layers[il].ffn_down_scale);
cur = ggml_scale(ctx0, cur, *(const float *)model.layers[il].ffn_down_scale->data);
cb(cur, "ffn_down", il);
}
cur = ggml_add(ctx0, cur, ffn_inp);