linter

external/anomaly/ote_anomalib/nncf_task.py

@@ -127,7 +127,7 @@ def load_model(self, ote_model: Optional[ModelEntity]) -> AnomalyModule:
             for key in model_data["model"].keys():
                 if key.startswith("model."):
                     new_key = key.replace("model.", "")
-                    res = re.search("nncf_module\.(\w+)_backbone\.(.*)", new_key)
+                    res = re.search(r"nncf_module\.(\w+)_backbone\.(.*)", new_key)
                     if res:
                         new_key = f"nncf_module.{res.group(1)}_model.backbone.{res.group(2)}"
                     nncf_modules[new_key] = model_data["model"][key]

ote_sdk/ote_sdk/configuration/elements/parameter_group.py

@@ -170,10 +170,10 @@ def __eq__(self, other):
         return False
 
 
-TParameterGroup = TypeVar("TParameterGroup", bound=ParameterGroup)
+_ParameterGroup = TypeVar("_ParameterGroup", bound=ParameterGroup)
 
 
-def add_parameter_group(group: Type[TParameterGroup]) -> TParameterGroup:
+def add_parameter_group(group: Type[_ParameterGroup]) -> _ParameterGroup:
     """
     Wrapper to attr.ib to add nested parameter groups to a configuration.
     """

ote_sdk/ote_sdk/configuration/elements/primitive_parameters.py

@@ -44,7 +44,7 @@
 
 # pylint:disable=too-many-arguments
 
-TConfigurableEnum = TypeVar("TConfigurableEnum", bound=ConfigurableEnum)
+_ConfigurableEnum = TypeVar("_ConfigurableEnum", bound=ConfigurableEnum)
 
 
 def set_common_metadata(
@@ -350,7 +350,7 @@ class for more details. Defaults to NullUIRules.
 
 
 def selectable(
-    default_value: TConfigurableEnum,
+    default_value: _ConfigurableEnum,
     header: str,
     description: str = "Default selectable description",
     warning: str = None,
@@ -360,7 +360,7 @@ def selectable(
     ui_rules: UIRules = NullUIRules(),
     auto_hpo_state: AutoHPOState = AutoHPOState.NOT_POSSIBLE,
     auto_hpo_value: Optional[str] = None,
-) -> TConfigurableEnum:
+) -> _ConfigurableEnum:
     """
     Constructs a selectable attribute from a pre-defined Enum, with the appropriate metadata. The list of options for
     display in the UI is inferred from the type of the ConfigurableEnum instance passed in as default_value.
@@ -408,8 +408,8 @@ class for more details. Defaults to NullUIRules.
     type_validator = attr.validators.instance_of(ConfigurableEnum)
     value_validator = construct_attr_enum_selectable_onsetattr(default_value)
 
-    # The Attribute returned by attr.ib is not compatible with the return typevar TConfigurableEnum. However, as the
-    # class containing the Attribute is instantiated the selectable type will correspond to the TConfigurableEnum, so
+    # The Attribute returned by attr.ib is not compatible with the return typevar _ConfigurableEnum. However, as the
+    # class containing the Attribute is instantiated the selectable type will correspond to the _ConfigurableEnum, so
     # mypy can ignore the error.
     return attr.ib(
         default=default_value,

ote_sdk/ote_sdk/entities/metrics.py

@@ -558,11 +558,11 @@ def __repr__(self):
         )
 
 
-MetricType = TypeVar("MetricType", bound=MetricEntity)
-VisualizationInfoType = TypeVar("VisualizationInfoType", bound=VisualizationInfo)
+_MetricType = TypeVar("_MetricType", bound=MetricEntity)
+_VisualizationInfoType = TypeVar("_VisualizationInfoType", bound=VisualizationInfo)
 
 
-class MetricsGroup(Generic[MetricType, VisualizationInfoType]):
+class MetricsGroup(Generic[_MetricType, _VisualizationInfoType]):
     """
     This class aggregates a list of metric entities and defines how this group will be
     visualized on the UI. This class is the parent class to the different types of
@@ -571,7 +571,7 @@ class MetricsGroup(Generic[MetricType, VisualizationInfoType]):
     :example: An accuracy as a metrics group
 
     >>> acc = ScoreMetric("Accuracy", 0.5)
-    >>> visual_info = BarChartInfo("Accuracy", visualization_type=VisualizationInfoType.BAR)  # show it as radial bar
+    >>> visual_info = BarChartInfo("Accuracy", visualization_type=_VisualizationInfoType.BAR)  # show it as radial bar
     >>> metrics_group = BarMetricsGroup([acc], visual_info)
 
     Loss curves as a metrics group
@@ -583,7 +583,7 @@ class MetricsGroup(Generic[MetricType, VisualizationInfoType]):
     """
 
     def __init__(
-        self, metrics: Sequence[MetricType], visualization_info: VisualizationInfoType
+        self, metrics: Sequence[_MetricType], visualization_info: _VisualizationInfoType
     ):
         if metrics is None or len(metrics) == 0:
             raise ValueError("Metrics cannot be None or empty")

ote_sdk/ote_sdk/usecases/exportable_code/streamer/streamer.py

@@ -331,6 +331,7 @@ def __init__(self, path: str) -> None:
         self.media_type = MediaType.IMAGE
         self.filenames = _get_filenames(path=path, media_type=MediaType.IMAGE)
 
+    #pylint: disable=arguments-differ
     @staticmethod
     def get_stream(stream_input: str) -> Iterable[np.ndarray]:
         image = cv2.imread(stream_input)

ote_sdk/ote_sdk/utils/shape_drawer.py

@@ -40,10 +40,10 @@
 
 CvTextSize = NewType("CvTextSize", Tuple[Tuple[int, int], int])
 
-AnyType = TypeVar("AnyType")
+_AnyType = TypeVar("_AnyType")
 
 
-class DrawerEntity(Generic[AnyType]):
+class DrawerEntity(Generic[_AnyType]):
     """
     An interface to draw a shape of type ``T`` onto an image.
     """
@@ -52,7 +52,7 @@ class DrawerEntity(Generic[AnyType]):
 
     @abc.abstractmethod
     def draw(
-        self, image: np.ndarray, entity: AnyType, labels: List[ScoredLabel]
+        self, image: np.ndarray, entity: _AnyType, labels: List[ScoredLabel]
     ) -> np.ndarray:
         """
         Draw an entity to a given frame