Fix ruff & Add ignore style

netspresso_inference_package/__init__.py

@@ -1 +1 @@
-from .inference.inference_service import InferenceService
+from .inference.inference_service import InferenceService

netspresso_inference_package/enums.py

@@ -1,5 +1,6 @@
 from enum import Enum
 
+
 class Enums(Enum):
     FRAMEWORK = "framework"
     INPUTS = "inputs"
@@ -87,4 +88,4 @@ def _missing_(cls, value):
             return cls[value]
         except KeyError:
             msg = f"{cls.__name__} expected {', '.join(list(cls.__members__.keys()))} but got `{value}`"
-            raise KeyError(msg)
+            raise KeyError(msg)

netspresso_inference_package/exceptions.py

@@ -38,4 +38,4 @@ def __init__(self, message="Can not load this tflite file."):
 
 class WrongDatsetFile(BaseException):
     def __init__(self, message="Dataset file is a not archive file neither '.npy' file.",):
-        super().__init__(message)
+        super().__init__(message)

netspresso_inference_package/inference/abs.py

@@ -1,13 +1,11 @@
 import abc
-from typing import Any
-import os
 
 
-class Basemodel(metaclass=abc.ABCMeta):    
+class Basemodel(metaclass=abc.ABCMeta):
     @abc.abstractmethod
     def model_input_output_attributes(self):
         raise NotImplementedError()
-    
+
     @abc.abstractmethod
     def inference(self, **kwargs):
-        raise NotImplementedError()
+        raise NotImplementedError()

netspresso_inference_package/inference/data_loader.py

@@ -1,28 +1,24 @@
 import os
 from pathlib import Path
-from typing import Dict, Any, Union
+from typing import Any, Dict, Union
 
 import numpy as np
 from loguru import logger
 
 from ..enums import Enums
-from ..utils import extract_archive
 from ..exceptions import NumpyLoadError, WrongDatsetFile
+from ..utils import extract_archive
 
 
 class NumpyDataLoader:
     def __init__(self, dataset_file_path:str, inputs:Dict[Union[str, int], Any]):
         self.npy = self.load_datasets(dataset_file_path, inputs)
-
-    def load_datasets(
-        self, 
-        dataset_file_path:str, 
-        inputs:Dict[Union[str, int], Any]
-        )->Dict[Union[str, int], np.ndarray]:
+
+    def load_datasets(self, dataset_file_path:str, inputs:Dict[Union[str, int], Any])->Dict[Union[str, int], np.ndarray]:
         outputs = {}
         # for single numpy file case
         if Path(dataset_file_path).is_file() and Path(dataset_file_path).suffix == ".npy":
-            for key in inputs.keys():
+            for key in inputs:
                 try:
                     outputs[key]=np.load(dataset_file_path)
                 except ValueError:
@@ -33,7 +29,7 @@ def load_datasets(
             # Unzip dataset_file_path
             extract_archive(dataset_file_path, os.path.dirname(dataset_file_path))
             parent_directory = os.path.dirname(dataset_file_path)
-            for key in inputs.keys():
+            for key in inputs:
                 file_name = f"{key}.npy"
                 file_path = os.path.join(parent_directory, file_name)
                 if os.path.exists(file_path):
@@ -45,4 +41,4 @@ def load_datasets(
                     logger.warning(f"Warning: File {file_path} does not exist.")
             return outputs
         else:
-            raise WrongDatsetFile()
+            raise WrongDatsetFile()

netspresso_inference_package/inference/inference_service.py

@@ -1,15 +1,15 @@
 import os
 from pathlib import Path
-from typing import Dict, Any
+from typing import Any, Dict
 
 import numpy as np
 from loguru import logger
 
-from .tflite_inference import TFLITE
-from .onnx_inference import ONNX
-from .data_loader import NumpyDataLoader
-from ..utils import make_temp_dir, compress_files, delete_parent_directory
 from ..exceptions import NotSupportedFramework
+from ..utils import compress_files, make_temp_dir
+from .data_loader import NumpyDataLoader
+from .onnx_inference import ONNX
+from .tflite_inference import TFLITE
 
 
 class InferenceService:
@@ -33,7 +33,7 @@ def set_model_obj(self, model_file_path:str, num_threads:int):
         #     model_obj = TFLITE(model_file_path, kwargs["num_threads"])
         # elif model_info[Enums.FRAMEWORK] == Enums.ONNX:
         #     model_obj = ONNX(model_file_path)
-        
+
         if len(model_obj.inputs) > 1:
             logger.info(f'{self.model_file_path} has {len(model_obj.inputs)} nodes for input layer')
         if len(model_obj.outputs) > 1:
@@ -52,14 +52,14 @@ def postprocess(self, inference_results:Dict[Any, np.ndarray]):
         # save npy file for each layers result
         files_path = []
         result_file_path = os.path.join(self.result_save_path, "archive.zip")
-        for k, v in inference_results.items():
+        for k, _v in inference_results.items():
             npy_file_path = os.path.join(self.result_save_path, f"{k}.npy")
             np.save(npy_file_path, inference_results[k])
             files_path.append(npy_file_path)
         # zip npy files
         compress_files(files_path, result_file_path)
         self.result_file_path = result_file_path
-    
+
     def run(self, dataset_file_path):
         self.dataset_file_path = dataset_file_path
         inference_results = self.inference(dataset_file_path)
@@ -71,5 +71,5 @@ def run(self, dataset_file_path):
 
     inf_service = InferenceService(
         model_file_path="/app/tests/people_detection.onnx"
-        )
-    inf_service.run(dataset_file_path="/app/tests/dataset_for_onnx.npy")
+    )
+    inf_service.run(dataset_file_path="/app/tests/dataset_for_onnx.npy")

netspresso_inference_package/inference/onnx_inference.py

@@ -1,20 +1,20 @@
-from typing import Dict, Union, Any
+from typing import Any, Dict, Union
 
 import numpy as np
-import onnxruntime
 import onnx
+import onnxruntime
 
-from .abs import Basemodel
 from ..exceptions import NotLoadableONNX
+from .abs import Basemodel
 
 
 def create_outputs(outputs:Dict[Union[str, int], Any], results:Dict[Union[str, int], Any]):
     if len(outputs) != len(results):
         raise ValueError("The length of 'outputs' and 'results' must be the same.")
 
-    for (key, value), result in zip(outputs.items(), results):
+    for (key, _value), result in zip(outputs.items(), results):
         outputs[key] = result
-    
+
     return outputs
 
 
@@ -41,20 +41,20 @@ def model_input_output_attributes(self, model_file_path:str):
         for oup in model.graph.output:
             shape = str(oup.type.tensor_type.shape.dim)
             outputs[oup.name] = [int(s) for s in shape.split() if s.isdigit()]
-        
+
         return inputs, outputs
 
     def inference(self, preprocess_result: Dict[int, np.ndarray]) -> Dict[int, np.ndarray]:
         inputs = {}
-        for k, v in preprocess_result.items():
+        for k, _v in preprocess_result.items():
             ortvalue = onnxruntime.OrtValue.ortvalue_from_numpy(preprocess_result[k])
             inputs[k] = ortvalue
             # TODO: make function which return npy generator when len(preprocess_result[k]) > 1
-        
+
         outputs_list = []
-        for k in self.outputs.keys():
+        for k in self.outputs:
             outputs_list.append(k)
 
         results = self.model_obj.run(outputs_list, inputs)
         output_dict = create_outputs(self.outputs, results)
-        return output_dict
+        return output_dict

netspresso_inference_package/inference/tflite_inference.py

@@ -3,9 +3,9 @@
 
 import numpy as np
 
-from .abs import Basemodel
 from ..enums import EnumInputNodeShapeFormat, EnumNodeRawDataType
 from ..exceptions import NotLoadableTFLITE
+from .abs import Basemodel
 
 try:
     import tflite_runtime.interpreter as tflite
@@ -151,10 +151,10 @@ def model_input_output_attributes(self):
             output_data_attribute.quantization = output_detail.get("quantization")
             outputs[output_data_attribute.key] = output_data_attribute
 
-        return inputs, outputs    
+        return inputs, outputs
 
     def inference(self, preprocess_result: Dict[int, np.ndarray], **kwargs) -> Dict[int, np.ndarray]:
-        for k, v in self.inputs.items():
+        for _k, v in self.inputs.items():
             if v.dtype in [np.uint8, np.int8, "int8", "unit8"]:
                 pass
 
@@ -166,4 +166,4 @@ def inference(self, preprocess_result: Dict[int, np.ndarray], **kwargs) -> Dict[
         output_dict = {}
         for output_location in iter(self.outputs):
             output_dict[output_location] = self.interpreter_obj.get_tensor(output_location)
-        return output_dict
+        return output_dict

netspresso_inference_package/utils.py

@@ -1,9 +1,9 @@
 import os
+import shutil
+import tarfile
 import tempfile
-from pathlib import Path
 import zipfile
-import tarfile
-import shutil
+from pathlib import Path
 
 import py7zr
 import rarfile
@@ -50,4 +50,4 @@ def delete_parent_directory(file_path:str):
     except FileNotFoundError:
         logger.info(f"Directory {file_path} does not exist.")
     except PermissionError:
-        logger.info(f"Permission denied to delete {file_path}.")
+        logger.info(f"Permission denied to delete {file_path}.")

pyproject.toml

@@ -17,6 +17,8 @@ ignore = [
   "C901",
   "B008",
   "SIM115",
+  "E722",
+  "B904",
 ]
 
 [tool.ruff.per-file-ignores]