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server : normalize embeddings (#5956)

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* output normalize embedding in '/v1/embeddings'

* common : reuse llama_embd_normalize

* common : better normalize impl

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
SeungWon Jeong 2024-03-09 21:27:58 +09:00 committed by GitHub
parent 2c4f566c88
commit fb215c3832
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GPG Key ID: B5690EEEBB952194
4 changed files with 30 additions and 14 deletions
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15
common/common.cpp
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@ -1852,3 +1852,18 @@ void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size) {
printf("\n=== Done dumping\n");
}
void llama_embd_normalize(const float * inp, float * out, int n) {
double sum = 0.0;
for (int i = 0; i < n; i++) {
sum += inp[i] * inp[i];
}
sum = sqrt(sum);
const float norm = sum > 0.0 ? 1.0f / sum : 0.0f;
for (int i = 0; i < n; i++) {
out[i] = inp[i] * norm;
}
}

7
common/common.h
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@ -260,3 +260,10 @@ void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size = 80);
// Dump the KV cache view showing individual sequences in each cell (long output).
void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
//
// Embedding utils
//
void llama_embd_normalize(const float * inp, float * out, int n);

14
examples/embedding/embedding.cpp
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@ -23,17 +23,6 @@ static void batch_add_seq(llama_batch & batch, const std::vector<int32_t> & toke
}
}
static void normalize(const float * vec, float * out, int n) {
float norm = 0;
for (int i = 0; i < n; i++) {
norm += vec[i] * vec[i];
}
norm = sqrt(norm);
for (int i = 0; i < n; i++) {
out[i] = vec[i] / norm;
}
}
static void batch_decode(llama_context * ctx, llama_batch & batch, float * output, int n_seq, int n_embd) {
// clear previous kv_cache values (irrelevant for embeddings)
llama_kv_cache_clear(ctx);
@ -44,7 +33,6 @@ static void batch_decode(llama_context * ctx, llama_batch & batch, float * outpu
fprintf(stderr, "%s : failed to decode\n", __func__);
}
// normalize on copy
for (int i = 0; i < batch.n_tokens; i++) {
if (!batch.logits[i]) {
continue;
@ -61,7 +49,7 @@ static void batch_decode(llama_context * ctx, llama_batch & batch, float * outpu
}
float * out = output + batch.seq_id[i][0] * n_embd;
normalize(embd, out, n_embd);
llama_embd_normalize(embd, out, n_embd);
}
}

8
examples/server/server.cpp
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@ -1327,6 +1327,8 @@ struct server_context {
const int n_embd = llama_n_embd(model);
std::vector<float> embd_res(n_embd, 0.0f);
for (int i = 0; i < batch.n_tokens; ++i) {
if (!batch.logits[i] || batch.seq_id[i][0] != slot.id + 1) {
continue;
@ -1350,8 +1352,10 @@ struct server_context {
continue;
}
llama_embd_normalize(embd, embd_res.data(), n_embd);
res.data = json {
{"embedding", std::vector<float>(embd, embd + n_embd)},
{"embedding", embd_res},
};
}
@ -3354,6 +3358,8 @@ int main(int argc, char ** argv) {
// get the result
server_task_result result = ctx_server.queue_results.recv(id_task);
ctx_server.queue_results.remove_waiting_task_id(id_task);
// append to the responses
responses.push_back(result.data);
}