graph : avoid huge warm-up graphs for MoE models

ggml-ci

Author: ggerganov

src/llama-context.cpp

@@ -1312,7 +1312,7 @@ uint32_t llama_context::output_reserve(int32_t n_outputs) {
 //
 
 uint32_t llama_context::graph_max_nodes() const {
-    return std::max<uint32_t>(65536u, 5u*model.n_tensors());
+    return std::max<uint32_t>(1024u, 6u*model.n_tensors());
 }
 
 llm_graph_result * llama_context::get_gf_res_reserve() const {

src/llama-graph.cpp

@@ -907,7 +907,7 @@ ggml_tensor * llm_graph_context::build_moe_ffn(
 
     // aggregate experts
     ggml_tensor * moe_out = nullptr;
-    for (int i = 0; i < n_expert_used; ++i) {
+    for (uint32_t i = 0; i < hparams.n_expert_used; ++i) {
         ggml_tensor * cur_expert = ggml_view_2d(ctx0, experts, n_embd, n_tokens,
                 experts->nb[2], i*experts->nb[1]);
 
@@ -918,7 +918,7 @@ ggml_tensor * llm_graph_context::build_moe_ffn(
         }
     }
 
-    if (n_expert_used == 1) {
+    if (hparams.n_expert_used == 1) {
         // avoid returning a non-contiguous tensor
         moe_out = ggml_cont(ctx0, moe_out);
     }