duo: v5

examples/duo/duo.cpp

@@ -82,7 +82,8 @@ static int decode(llama_context * ctx, iter_t from, iter_t to, int offset, bool
     }
     batch.logits[batch.n_tokens - 1] = true;
     int res = 0;
-    if (llama_decode(ctx, batch) != 0) {
+    if (llama_decode(ctx, batch) != 0)
+    {
         fprintf(stderr, "llama_decode() failed\n");
         res = 1;
     }
@@ -126,7 +127,8 @@ static int speculation(
         }
 
         auto next_tokens = greedy_tokens(model, ctx, logit_idx, logit_idx + 1);
-        if (next_tokens.size() != 1) {
+        if (next_tokens.size() != 1)
+        {
             fprintf(stderr, "invalid next tokens\n");
             return 1;
         }
@@ -157,9 +159,7 @@ static int speculation(
             }
         }
 
-
         decode(ctx, local.begin() + match_len, local.end(), match_len, false, batch);
-
         logit_idx = local.size() - match_len - 1;
     }
 
@@ -179,9 +179,8 @@ static int target(
     llama_batch batch = llama_batch_init(512, 0, 1);
     decode(ctx, input.begin(), input.end(), 0, false, batch);
 
-    // TODO: rename to n_accepted
-    size_t n_cur = input.size();
-    size_t n_decode = 0;
+    size_t n_accepted = input.size();
+    size_t n_decoded  = 0;
 
     const auto t_main_start = ggml_time_us();
 
@@ -192,7 +191,7 @@ static int target(
     llama_tokens input_seq, next_tokens;
     input_seq.push_back(input.back());
 
-    while (n_decode <= n_predict)
+    while (n_decoded < n_predict)
     {
         next_tokens = greedy_tokens(model, ctx, logits_from, logits_to);
         if (next_tokens.size() != input_seq.size())
@@ -201,16 +200,16 @@ static int target(
             return 1;
         }
 
-        size_t next_tokens_pos = n_cur;
+        size_t next_tokens_pos = n_accepted;
         // we always accept at least one new token
-        n_cur    += 1;
-        n_decode += 1;
+        n_accepted += 1;
+        n_decoded  += 1;
         for (size_t i = 0; i + 1 < input_seq.size(); i++)
         {
             if (next_tokens[i] == input_seq[i + 1])
             {
-                n_cur += 1;
-                n_decode += 1;
+                n_accepted += 1;
+                n_decoded  += 1;
             }
             else
             {
@@ -222,7 +221,7 @@ static int target(
 
         // empty the non-matching portion of kv cache. 
         // n_cur is incremented at least once and will be > 0
-        llama_kv_cache_seq_rm(ctx, 0, n_cur - 1, -1);
+        llama_kv_cache_seq_rm(ctx, 0, n_accepted - 1, -1);
 
         bool done = false;
         for (size_t i = 0; i < next_tokens.size(); i++)
@@ -263,14 +262,14 @@ static int target(
                     spec.push_back(tok);
                 }
             }
-            input_seq.assign(spec.begin() + n_cur - 1, spec.end());
+            input_seq.assign(spec.begin() + n_accepted - 1, spec.end());
         }
-        if (n_decode >= n_predict || done)
+        if (n_decoded >= n_predict || done)
         {
             break;
         }
 
-        decode(ctx, input_seq.begin(), input_seq.end(), n_cur - 1, true, batch);
+        decode(ctx, input_seq.begin(), input_seq.end(), n_accepted - 1, true, batch);
 
         logits_from = 0;
         logits_to   = input_seq.size();
@@ -279,7 +278,7 @@ static int target(
     const auto t_main_end = ggml_time_us();
 
     fprintf(stderr, "decoded %zu tokens in %.2f s, speed: %.2f t/s\n",
-            n_decode, (t_main_end - t_main_start) / 1000000.0f, n_decode / ((t_main_end - t_main_start) / 1000000.0f));
+            n_decoded, (t_main_end - t_main_start) / 1000000.0f, n_decoded / ((t_main_end - t_main_start) / 1000000.0f));
 
     llama_print_timings(ctx);
     fprintf(stderr, "\n");
@@ -295,11 +294,13 @@ static int target(
 int main(int argc, char ** argv) {
     gpt_params params;
 
-    if (gpt_params_parse(argc, argv, params) == false) {
+    if (gpt_params_parse(argc, argv, params) == false)
+    {
         return 1;
     }
 
-    if (params.seed == LLAMA_DEFAULT_SEED) {
+    if (params.seed == LLAMA_DEFAULT_SEED)
+    {
         params.seed = time(NULL);
     }