Optimize tensor loading

lora.hpp

@@ -115,7 +115,7 @@ struct LoraModel : public GGMLRunner {
         return "lora";
     }
 
-    bool load_from_file(bool filter_tensor = false) {
+    bool load_from_file(bool filter_tensor = false, int n_threads = 0) {
         LOG_INFO("loading LoRA from '%s'", file_path.c_str());
 
         if (load_failed) {
@@ -131,15 +131,14 @@ struct LoraModel : public GGMLRunner {
                 // LOG_INFO("skipping LoRA tesnor '%s'", name.c_str());
                 return true;
             }
-            // LOG_INFO("lora_tensor %s", name.c_str());
-            for (int i = 0; i < LORA_TYPE_COUNT; i++) {
-                if (name.find(type_fingerprints[i]) != std::string::npos) {
-                    type = (lora_t)i;
-                    break;
-                }
-            }
 
             if (dry_run) {
+                for (int i = 0; i < LORA_TYPE_COUNT; i++) {
+                    if (name.find(type_fingerprints[i]) != std::string::npos) {
+                        type = (lora_t)i;
+                        break;
+                    }
+                }
                 struct ggml_tensor* real = ggml_new_tensor(params_ctx,
                                                            tensor_storage.type,
                                                            tensor_storage.n_dims,
@@ -153,11 +152,11 @@ struct LoraModel : public GGMLRunner {
             return true;
         };
 
-        model_loader.load_tensors(on_new_tensor_cb);
+        model_loader.load_tensors(on_new_tensor_cb, 1);
         alloc_params_buffer();
-        // exit(0);
+
         dry_run = false;
-        model_loader.load_tensors(on_new_tensor_cb);
+        model_loader.load_tensors(on_new_tensor_cb, n_threads);
 
         LOG_DEBUG("lora type: \"%s\"/\"%s\"", lora_downs[type].c_str(), lora_ups[type].c_str());