fix types and ignored pattern

machine-learning/app/models/base.py

@@ -69,6 +69,7 @@ class InferenceModel(ABC):
 
     def _download(self) -> None:
         ignored_patterns: dict[ModelFormat, list[str]] = {
+            ModelFormat.ONNX: ["*.armnn", "*.rknn"],
             ModelFormat.ARMNN: ["*.rknn"],
             ModelFormat.RKNN: ["*.armnn"],
         }

machine-learning/app/test_main.py

@@ -355,7 +355,7 @@ class TestRknnSession:
         RknnSession(model_path)
 
         rknn_session.assert_called_once_with(
-            rknnModel=Path(str(model_path).replace("model", "rk3566")).as_posix(), TPEs=tpe, func=runInference
+            rknnModel=Path(str(model_path).replace("model", "rk3566")).as_posix(), tpes=tpe, func=runInference
         )
 
         info.assert_has_calls(

machine-learning/rknn/rknnpool.py

@@ -5,6 +5,7 @@ import os
 from concurrent.futures import ThreadPoolExecutor
 from queue import Queue
 import numpy as np
+from typing import Callable
 from numpy.typing import NDArray
 from app.config import log
 
@@ -31,7 +32,7 @@ except (FileNotFoundError, ImportError):
     soc_name = None
 
 
-def init_rknn(rknnModel, id) -> RKNNLite:
+def init_rknn(rknnModel, id) -> Callable:
     if not is_available:
         raise RuntimeError("rknn is not available!")
     rknn_lite = RKNNLite()
@@ -59,7 +60,7 @@ def init_rknn(rknnModel, id) -> RKNNLite:
     return rknn_lite
 
 
-def init_rknns(rknnModel, tpes) -> list[RKNNLite]:
+def init_rknns(rknnModel, tpes) -> list[Callable]:
     rknn_list = []
     for i in range(tpes):
         rknn_list.append(init_rknn(rknnModel, i % 3))