Load all MoE experts during warmup and make warmup 1 token (#198)

* Load all MoE experts during warmup

Co-authored-by: Stanisław Szymczyk <[email protected]>

* Unify warmup to one token

---------

Co-authored-by: Stanisław Szymczyk <[email protected]>

Author: saood06

common/common.cpp

@@ -2169,8 +2169,10 @@ struct llama_init_result llama_init_from_gpt_params(gpt_params & params) {
         if (bos != -1) {
             tmp.push_back(bos);
         }
-        tmp.push_back(eos);
-
+	else
+	{
+	    tmp.push_back(eos);
+	}
         if (llama_model_has_encoder(model)) {
             llama_encode(lctx, llama_batch_get_one(tmp.data(), tmp.size(), 0, 0));
             llama_token decoder_start_token_id = llama_model_decoder_start_token(model);

examples/llama-bench/llama-bench.cpp

@@ -1586,7 +1586,7 @@ int main(int argc, char ** argv) {
         if (params.warmup) {
             if (t.n_prompt > 0) {
                 //test_prompt(ctx, std::min(t.n_batch, std::min(t.n_prompt, 32)), 0, t.n_batch, t.n_threads);
-                test_prompt(ctx, t.n_prompt, 0, t.n_batch, t.n_threads);
+                test_prompt(ctx, 1, 0, t.n_batch, t.n_threads);
             }
             if (t.n_gen > 0) {
                 test_gen(ctx, 1, 0, t.n_threads);

src/llama.cpp

@@ -3784,7 +3784,7 @@ static size_t llama_model_max_nodes(const llama_model & /*model*/) {
     //    return 32768;
     //}
 
-    return 8192;
+    return 65536;
 }
 
 struct llama_model_loader {
@@ -8879,7 +8879,8 @@ struct llm_build_context {
         llama_context  & lctx,
     const llama_batch  & batch,
     const llm_build_cb & cb,
-                  bool   worst_case) :
+    bool   worst_case,
+    bool   warmup) :
         model            (lctx.model),
         lctx             (lctx),
         hparams          (model.hparams),
@@ -8897,7 +8898,7 @@ struct llm_build_context {
         n_embd_head_v    (hparams.n_embd_head_v),
         n_embd_v_gqa     (hparams.n_embd_v_gqa()),
         n_expert         (hparams.n_expert),
-        n_expert_used    (hparams.n_expert_used),
+        n_expert_used    (warmup ? hparams.n_expert : hparams.n_expert_used),
         freq_base        (cparams.rope_freq_base),
         freq_scale       (cparams.rope_freq_scale),
         ext_factor       (cparams.yarn_ext_factor),
@@ -14433,7 +14434,7 @@ static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const
 
     llm_build_cb cb = [&](struct ggml_tensor * , const char * , int ) { };
 
-    struct llm_build_context llm(lctx, dummy, cb, false);
+    struct llm_build_context llm(lctx, dummy, cb, false, false);
 
     llm.init();
 
@@ -14450,7 +14451,7 @@ static struct ggml_cgraph * llama_build_graph_k_shift(llama_context & lctx) {
 
     llm_build_cb cb = [&](struct ggml_tensor * , const char * , int ) { };
 
-    struct llm_build_context llm(lctx, dummy, cb, false);
+    struct llm_build_context llm(lctx, dummy, cb, false, false);
 
     llm.init();
 
@@ -14467,7 +14468,7 @@ static struct ggml_cgraph * llama_build_graph_s_copy(llama_context & lctx) {
 
     llm_build_cb cb = [&](struct ggml_tensor * , const char * , int ) { };
 
-    struct llm_build_context llm(lctx, dummy, cb, false);
+    struct llm_build_context llm(lctx, dummy, cb, false, false);
 
     llm.init();
 
@@ -14517,7 +14518,11 @@ static struct ggml_cgraph * llama_build_graph(
 
     struct ggml_cgraph * result = NULL;
 
-    struct llm_build_context llm(lctx, batch, cb, worst_case);
+    const llama_vocab * vocab = llama_get_vocab(&lctx);
+    llama_token bos = llama_token_bos_impl(*vocab);
+    llama_token eos = llama_token_eos_impl(*vocab);
+    bool is_warming_up = (batch.n_tokens == 1 && batch.token[0] == bos);
+    struct llm_build_context llm(lctx, batch, cb, worst_case, is_warming_up);
 
     llm.init();