common : add option to sort sampling candidates by probability

ggml-ci

Author: ggerganov

common/sampling.cpp

@@ -426,8 +426,29 @@ uint32_t common_sampler_get_seed(const struct common_sampler * gsmpl) {
 
 // helpers
 
-llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl) {
-    return &gsmpl->cur_p;
+llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl, bool do_sort) {
+    auto * res = &gsmpl->cur_p;
+
+    if (do_sort && !gsmpl->cur_p.sorted) {
+        // remember the selected token before sorting
+        const llama_token id = res->data[res->selected].id;
+
+        std::sort(res->data, res->data + res->size, [](const llama_token_data & a, const llama_token_data & b) {
+            return a.p > b.p;
+        });
+
+        // restore the selected token after sorting
+        for (size_t i = 0; i < res->size; ++i) {
+            if (res->data[i].id == id) {
+                res->selected = i;
+                break;
+            }
+        }
+
+        res->sorted = true;
+    }
+
+    return res;
 }
 
 llama_token common_sampler_last(const struct common_sampler * gsmpl) {

common/sampling.h

@@ -86,7 +86,9 @@ uint32_t common_sampler_get_seed(const struct common_sampler * gsmpl);
 // helpers
 
 // access the internal list of current candidate tokens
-llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl);
+// if do_sort == true, the candidates will be sorted (in descending order of probability) in case they are not already sorted
+// if do_sort == false, the candidates *might* not be sorted. use the .sorted flag of the result to determine that
+llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl, bool do_sort);
 
 // get the last accepted token
 llama_token common_sampler_last(const struct common_sampler * gsmpl);

common/speculative.cpp

@@ -317,7 +317,7 @@ llama_tokens common_speculative_gen_draft(
 
         common_sampler_sample(smpl, ctx_dft, 0, true);
 
-        const auto * cur_p = common_sampler_get_candidates(smpl);
+        const auto * cur_p = common_sampler_get_candidates(smpl, true);
 
         for (int k = 0; k < std::min(3, (int) cur_p->size); ++k) {
             LOG_DBG(" - draft candidate %3d, pos %3d: %6d (%8.3f) '%s'\n",

examples/speculative/speculative.cpp

@@ -244,7 +244,7 @@ int main(int argc, char ** argv) {
                     // stochastic verification
                     common_sampler_sample(smpl, ctx_tgt, drafts[s_keep].i_batch_tgt[i_dft], true);
 
-                    auto & dist_tgt = *common_sampler_get_candidates(smpl);
+                    auto & dist_tgt = *common_sampler_get_candidates(smpl, true);
 
                     float p_tgt = 0.0f;
                     float p_dft = 0.0f;
@@ -493,7 +493,7 @@ int main(int argc, char ** argv) {
 
                 common_sampler_sample(drafts[s].smpl, ctx_dft, drafts[s].i_batch_dft, true);
 
-                const auto * cur_p = common_sampler_get_candidates(drafts[s].smpl);
+                const auto * cur_p = common_sampler_get_candidates(drafts[s].smpl, true);
 
                 for (int k = 0; k < std::min(n_seq_dft + 3, (int) cur_p->size); ++k) {
                     LOG_DBG(" - draft candidate %3d for seq %3d, pos %3d: %6d (%8.3f) '%s'\n",

include/llama.h

@@ -198,7 +198,7 @@ extern "C" {
         llama_token_data * data;
         size_t size;
         int64_t selected; // this is the index in the data array (i.e. not the token id)
-        bool sorted;
+        bool sorted;      // note: do not assume the data is sorted - always check this flag
     } llama_token_data_array;
 
     typedef bool (*llama_progress_callback)(float progress, void * user_data);

src/llama-sampling.cpp

@@ -1200,7 +1200,6 @@ static void llama_sample_xtc_apply(struct llama_sampler * smpl, llama_token_data
         return;
     }
 
-    // in case it's not sorted/recalculated yet
     llama_sampler_softmax_impl(cur_p, &ctx->buf_sort);
 
     int pos_last = 0;

tools/server/server.cpp

@@ -2485,11 +2485,12 @@ struct server_context {
         return slot.has_next_token; // continue
     }
 
-    void populate_token_probs(const server_slot & slot, completion_token_output & result, bool post_sampling, bool special, int idx) {
+    void populate_token_probs(const server_slot & slot, completion_token_output & result, bool post_sampling, bool special, int idx) const {
         size_t n_probs = slot.params.sampling.n_probs;
         size_t n_vocab = llama_vocab_n_tokens(vocab);
+
         if (post_sampling) {
-            const auto * cur_p = common_sampler_get_candidates(slot.smpl);
+            const auto * cur_p = common_sampler_get_candidates(slot.smpl, true);
             const size_t max_probs = cur_p->size;
 
             // set probability for sampled token

tools/tts/tts.cpp

@@ -895,7 +895,7 @@ lovely<|t_0.56|><|code_start|><|634|><|596|><|1766|><|1556|><|1306|><|1285|><|14
 
                 codes.push_back(new_token_id);
 
-                const auto * cands = common_sampler_get_candidates(smpl[i]);
+                const auto * cands = common_sampler_get_candidates(smpl[i], false);
 
                 // is it an end of generation? -> mark the stream as finished
                 if (llama_vocab_is_eog(vocab, new_token_id) || n_decode == n_predict) {