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Add heuristic algorithm for speculative #3006

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merged 6 commits into from
Sep 14, 2023
Merged

Add heuristic algorithm for speculative #3006

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98230ef
Add heuristic algo for speculative
leng-yue Sep 4, 2023
9248528
Constrain minimum n_draft to 2
leng-yue Sep 4, 2023
dddd784
speculative : improve heuristic impl
ggerganov Sep 5, 2023
4e6e951
Merge branch 'master' into HEAD
ggerganov Sep 5, 2023
d9559b7
speculative : be more rewarding upon guessing max drafted tokens
ggerganov Sep 5, 2023
b5efa62
speculative : fix typos
ggerganov Sep 5, 2023
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24 changes: 23 additions & 1 deletion examples/speculative/speculative.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@ int main(int argc, char ** argv) {
//GGML_ASSERT(n_vocab == llama_n_vocab(ctx_dft));

// how many tokens to draft each time
const int n_draft = params.n_draft;
int n_draft = params.n_draft;

int n_predict = 0;
int n_drafted = 0;
Expand Down Expand Up @@ -134,6 +134,7 @@ int main(int argc, char ** argv) {
LOG("drafted: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx_dft, drafted));

int i_dft = 0;

while (true) {
// sample from the target model
const llama_token id = llama_sample_token(ctx_tgt, NULL, grammar_tgt, params, last_tokens, candidates, i_dft);
Expand Down Expand Up @@ -177,6 +178,27 @@ int main(int argc, char ** argv) {
llama_eval(ctx_dft, &id, 1, n_past_dft, params.n_threads);
++n_past_dft;

// heuristic for n_draft
{
const int n_draft_cur = (int) drafted.size();
const bool all_accepted = i_dft == n_draft_cur;

LOG("n_draft = %d\n", n_draft);
LOG("n_draft_cur = %d\n", n_draft_cur);
LOG("i_dft = %d\n", i_dft);
LOG("all_accepted = %d\n", all_accepted);

if (all_accepted && n_draft == n_draft_cur) {
LOG(" - max drafted tokens accepted - n_draft += 8\n");
n_draft = std::min(30, n_draft + 8);
} else if (all_accepted) {
LOG(" - partially drafted tokens accepted - no change\n");
} else {
LOG(" - drafted token rejected - n_draft -= 1\n");
n_draft = std::max(2, n_draft - 1);
}
}

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@leng-yue

I've refactored the implementation to be more contained.
Also, we were rewarding the draft even when it hasn't sampled all n_draft tokens, which does not seem correct.

For example, let's say n_draft is 16 currently, but the draft samples just 3 tokens because the "low-probability" check has been triggered. Even if all 3 tokens were accepted, we should not reward the draft model, because this is just a small part of what we asked it to do.

Regarding the reproducibility - we will study this more in #3014
My guess is that this behavior would occur even without the heuristic - probably it's just less likely to happen for some reason when the heuristic is disabled.

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In my earlier implementation, rewards were given only when all tokens were accepted. So if only 3 out of 16 tokens are accepted, the n_tokens value would be decreased by 1.

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Not exactly. This check does not guarantee you have n_draft tokens accepted:

llama.cpp/examples/speculative/speculative.cpp

Lines 146 to 148 in 98230ef

if (i_dft == (int) drafted.size()) {
all_accepted = true;
}

The reason is because drafted.size() <= n_draft due to another heuristic of not drafting more tokens if the drafter becomes "unsure":

llama.cpp/examples/speculative/speculative.cpp

Lines 192 to 196 in 98230ef

// too low probability, stop drafting
if (cur_p.data[0].p < 2*cur_p.data[1].p) {
break;
}

So in the majority of cases, when all_accepted == true, you would have accepted less than n_draft tokens. That's why your n_draft would increase so much even beyond 70 in some cases.

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Got it.

drafted.clear();
drafted.push_back(id);

Expand Down
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