ikawrakow/ik_llama.cpp
1
0
Fork 0
mirror of https://github.com/ikawrakow/ik_llama.cpp.git synced 2026-03-03 10:30:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

multi_add: simplify

Browse Source
This commit is contained in:
Iwan Kawrakow
2024-10-30 11:02:15 +02:00
parent 8af4111f97
commit c08af00548
4 changed files with 53 additions and 105 deletions
Download Patch File Download Diff File Expand all files Collapse all files

57
src/llama.cpp
View File

@@ -8358,44 +8358,33 @@ static struct ggml_tensor * llm_build_moe_ffn(
return ggml_add(ctx, ggml_view_2d(ctx, experts, n_embd, n_tokens, experts->nb[2], 0),
ggml_view_2d(ctx, experts, n_embd, n_tokens, experts->nb[2], experts->nb[1]));
}
if (n_expert_used <= GGML_MAX_SRC) {
ggml_tensor * src[GGML_MAX_SRC];
for (int i = 0; i < n_expert_used; ++i) {
src[i] = ggml_view_2d(ctx, experts, n_embd, n_tokens, experts->nb[2], i*experts->nb[1]);
}
for (int i = n_expert_used; i < GGML_MAX_SRC; ++i) src[i] = nullptr;
return ggml_multi_add(ctx, src);
}
return ggml_multi_add(ctx, ggml_view_2d(ctx, experts, n_embd, n_tokens, experts->nb[2], 0), n_expert_used);
GGML_ABORT("fatal error");
//// aggregate experts
//ggml_tensor * moe_out = nullptr;
////ggml_tensor * first_expert = nullptr;
//for (int i = 0; i < n_expert_used; ++i) {
// ggml_tensor * cur_expert = ggml_view_2d(ctx, experts, n_embd, n_tokens,
// experts->nb[2], i*experts->nb[1]);
//int nloop = (n_expert_used + GGML_MAX_SRC - 1)/GGML_MAX_SRC;
// if (i == 0) {
// moe_out = cur_expert;
// //first_expert = cur_expert;
// //printf("%s: %d: %d x %d x %d x %d | %d x %d x %d x %d\n", __func__, ggml_is_contiguous(first_expert),
// // (int)cur_expert->ne[0], (int)cur_expert->ne[1], (int)cur_expert->ne[2], (int)cur_expert->ne[3],
// // (int)cur_expert->nb[0], (int)cur_expert->nb[1], (int)cur_expert->nb[2], (int)cur_expert->nb[3]);
// } else {
// moe_out = ggml_add(ctx, moe_out, cur_expert);
// //printf("%s: %d %d\n", __func__, ggml_is_contiguous(cur_expert), ggml_are_same_shape(cur_expert, first_expert));
// }
//}
// aggregate experts
ggml_tensor * moe_out = nullptr;
//ggml_tensor * first_expert = nullptr;
for (int i = 0; i < n_expert_used; ++i) {
ggml_tensor * cur_expert = ggml_view_2d(ctx, experts, n_embd, n_tokens,
experts->nb[2], i*experts->nb[1]);
//if (n_expert_used == 1) {
// // avoid returning a non-contiguous tensor
// moe_out = ggml_cont(ctx, moe_out);
//}
if (i == 0) {
moe_out = cur_expert;
//first_expert = cur_expert;
//printf("%s: %d: %d x %d x %d x %d | %d x %d x %d x %d\n", __func__, ggml_is_contiguous(first_expert),
// (int)cur_expert->ne[0], (int)cur_expert->ne[1], (int)cur_expert->ne[2], (int)cur_expert->ne[3],
// (int)cur_expert->nb[0], (int)cur_expert->nb[1], (int)cur_expert->nb[2], (int)cur_expert->nb[3]);
} else {
moe_out = ggml_add(ctx, moe_out, cur_expert);
//printf("%s: %d %d\n", __func__, ggml_is_contiguous(cur_expert), ggml_are_same_shape(cur_expert, first_expert));
}
}
if (n_expert_used == 1) {
// avoid returning a non-contiguous tensor
moe_out = ggml_cont(ctx, moe_out);
}
return moe_out;
//return moe_out;
}
static struct ggml_tensor * llm_build_kqv(