[service] Add latency profiling support for single

- Let the ml service using single conf can set latency profiling option
Example:
```json
{  "single": { ... "profile": "true" } }
```
- To make it compatible with pipeline way `(... latency=1 ...)`,
key of "latency" and value of "1" will do the same thing.

Signed-off-by: Yongjoo Ahn <yongjoo1.ahn@samsung.com>

Author: anyj0527

c/include/nnstreamer-tizen-internal.h

@@ -51,7 +51,8 @@ typedef struct {
   int invoke_dynamic;            /**< True for supporting invoke with flexible output. */
   int invoke_async;              /**< The sub-plugin must support asynchronous output to use this option. If set to TRUE, the sub-plugin can generate multiple outputs asynchronously per single input. Otherwise, only synchronous single-output is expected and async callback is ignored. */
   ml_tensors_data_cb invoke_async_cb; /**< Callback function to be called when the sub-plugin generates an output asynchronously. This is only available when invoke_async is set to TRUE. */
-  void *invoke_async_pdata;           /**< Private data to be passed to async callback. */
+  void *invoke_async_pdata;      /**< Private data to be passed to async callback. */
+  int latency_mode;              /**< 1 - log invoke latency, 0 (default) - do not log */
 } ml_single_preset;
 
 /**

c/src/ml-api-inference-single.c

@@ -1162,7 +1162,7 @@ ml_single_open_custom (ml_single_h * single, ml_single_preset * info)
 
   g_object_set (filter_obj, "framework", fw_name, "accelerator", hw_name,
       "model", converted_models, "invoke-dynamic", single_h->invoke_dynamic,
-      "invoke-async", single_h->invoke_async, NULL);
+      "invoke-async", single_h->invoke_async, "latency", info->latency_mode, NULL);
   g_free (hw_name);
 
   if (info->custom_option) {
@@ -1318,6 +1318,15 @@ ml_single_open_with_option (ml_single_h * single, const ml_option_h option)
   if (ML_ERROR_NONE == ml_option_get (option, "async_data", &value)) {
     info.invoke_async_pdata = value;
   }
+  if (ML_ERROR_NONE == ml_option_get (option, "profile", &value)) {
+    if (g_ascii_strcasecmp ((gchar *) value, "true") == 0) {
+      info.latency_mode = 1;
+    } else if (g_ascii_strtoll ((gchar *) value, NULL, 10) > 0) {
+      info.latency_mode = 1;
+    } else {
+      info.latency_mode = 0;
+    }
+  }
 
   return ml_single_open_custom (single, &info);
 }

c/src/ml-api-service-extension.c

@@ -343,6 +343,22 @@ _ml_extension_conf_parse_single (ml_service_s * mls, JsonObject * single)
         _ml_extension_destroy_tensors_info);
   }
 
+  /* parse latency profiling option - "profile": "true" or "1" */
+  if (json_object_has_member (single, "profile")) {
+    const gchar *profile = json_object_get_string_member (single, "profile");
+
+    if (STR_IS_VALID (profile))
+      ml_option_set (option, "profile", g_strdup (profile), g_free);
+  }
+
+  /* parse latency profiling option - "latency": "true" or "1" */
+  if (json_object_has_member (single, "latency")) {
+    const gchar *latency = json_object_get_string_member (single, "latency");
+
+    if (STR_IS_VALID (latency))
+      ml_option_set (option, "profile", g_strdup (latency), g_free);
+  }
+
   if (json_object_has_member (single, "custom")) {
     const gchar *custom = json_object_get_string_member (single, "custom");