Errors sending to UI

notifying client of AI model conversion

Azaion.Inference/inference.pyx

@@ -32,7 +32,7 @@ cdef class Inference:
         self.engine = None
         self.is_building_engine = False
 
-    cdef build_tensor_engine(self):
+    cdef build_tensor_engine(self, object updater_callback):
         is_nvidia = HardwareService.has_nvidia_gpu()
         if not is_nvidia:
             return
@@ -40,18 +40,22 @@ cdef class Inference:
         engine_filename = TensorRTEngine.get_engine_filename(0)
         key = Security.get_model_encryption_key()
         models_dir = constants.MODELS_FOLDER
-        if not os.path.exists(os.path.join(<str> models_dir, f'{engine_filename}.big')):
-            #TODO: Check cdn on engine exists, if there is, download
-            self.is_building_engine = True
-            time.sleep(8) # prevent simultaneously loading dll and models
-            onnx_model = self.api_client.load_big_small_resource(constants.AI_ONNX_MODEL_FILE, models_dir, key)
-            model_bytes = TensorRTEngine.convert_from_onnx(onnx_model)
-            self.api_client.upload_big_small_resource(model_bytes, <str> engine_filename, models_dir, key)
-            print('uploaded ')
-            self.is_building_engine = False
-        else:
-            print('tensor rt engine is here, no need to build')
 
+        self.is_building_engine = True
+        updater_callback('downloading')
+        if self.api_client.load_big_small_resource(engine_filename, models_dir, key):
+            print('tensor rt engine is here, no need to build')
+            self.is_building_engine = False
+            return
+
+        # time.sleep(8) # prevent simultaneously loading dll and models
+        updater_callback('converting')
+        onnx_model = self.api_client.load_big_small_resource(constants.AI_ONNX_MODEL_FILE, models_dir, key)
+        model_bytes = TensorRTEngine.convert_from_onnx(onnx_model)
+        updater_callback('uploading')
+        self.api_client.upload_big_small_resource(model_bytes, <str> engine_filename, models_dir, key)
+        print(f'uploaded {engine_filename} to CDN and API')
+        self.is_building_engine = False
 
     cdef init_ai(self):
         if self.engine is not None:
@@ -161,7 +165,6 @@ cdef class Inference:
         self.stop_signal = False
         self.init_ai()
 
-        print(ai_config.paths)
         for m in ai_config.paths:
             if self.is_video(m):
                 videos.append(m)