applied black

image_prediction/estimator/preprocessor/preprocessor.py

@@ -2,7 +2,6 @@ import abc
 
 
 class Preprocessor(abc.ABC):
-
     @abc.abstractmethod
     def preprocess(self, batch):
         raise NotImplementedError

image_prediction/estimator/preprocessor/preprocessors/identity.py

@@ -2,7 +2,6 @@ from image_prediction.estimator.preprocessor.preprocessor import Preprocessor
 
 
 class IdentityPreprocessor(Preprocessor):
-
     @staticmethod
     def preprocess(images):
         return images

image_prediction/formatter/formatter.py

@@ -2,7 +2,6 @@ import abc
 
 
 class Formatter(abc.ABC):
-
     @abc.abstractmethod
     def format(self, info: dict):
         raise NotImplementedError

image_prediction/formatter/formatters/info_formatter.py

@@ -5,7 +5,6 @@ from image_prediction.formatter.formatter import Formatter
 
 
 class EnumFormatter(Formatter):
-
     def format(self, metadata: dict):
         return {key.value if isinstance(key, Enum) else key: val for key, val in metadata.items()}
 

image_prediction/image_extractor/extractor.py

@@ -6,7 +6,6 @@ ImageMetadataPair = namedtuple("ImageMetadataPair", ["image", "metadata"])
 
 
 class ImageExtractor(abc.ABC):
-
     @abc.abstractmethod
     def extract(self, obj) -> Iterable[ImageMetadataPair]:
         raise NotImplementedError

image_prediction/label_mapper/mapper.py

@@ -2,7 +2,6 @@ import abc
 
 
 class LabelMapper(abc.ABC):
-
     @abc.abstractmethod
     def map_labels(self, items):
         raise NotImplementedError

image_prediction/label_mapper/mappers/numeric.py

@@ -10,9 +10,7 @@ class IndexMapper(LabelMapper):
 
     def __validate_index_label_format(self, index_label: int) -> None:
         if not 0 <= index_label < len(self.__labels):
-            raise UnexpectedLabelFormat(
-                f"Received index label  '{index_label}' that has no associated string label."
-            )
+            raise UnexpectedLabelFormat(f"Received index label  '{index_label}' that has no associated string label.")
 
     def __map_label(self, index_label: int) -> str:
         self.__validate_index_label_format(index_label)

image_prediction/label_mapper/mappers/probability.py

@@ -24,7 +24,9 @@ class ProbabilityMapper(LabelMapper):
 
     def __map_array(self, probabilities: np.ndarray) -> dict:
         self.__validate_array_label_format(probabilities)
-        cls2prob = dict(sorted(zip(self.__labels, list(map(self.__rounder, probabilities))), key=itemgetter(1), reverse=True))
+        cls2prob = dict(
+            sorted(zip(self.__labels, list(map(self.__rounder, probabilities))), key=itemgetter(1), reverse=True)
+        )
         most_likely = [*cls2prob][0]
         return {"label": most_likely, "probabilities": cls2prob}
 

image_prediction/model_loader/database/connector.py

@@ -2,7 +2,6 @@ import abc
 
 
 class DatabaseConnector(abc.ABC):
-
     @abc.abstractmethod
     def get_object(self, identifier):
         raise NotImplementedError

image_prediction/model_loader/database/connectors/mock.py

@@ -2,7 +2,6 @@ from image_prediction.model_loader.database.connector import DatabaseConnector
 
 
 class DatabaseConnectorMock(DatabaseConnector):
-
     def __init__(self, store: dict):
         self.store = store
 

image_prediction/model_loader/loader.py

@@ -4,7 +4,6 @@ from image_prediction.model_loader.database.connector import DatabaseConnector
 
 
 class ModelLoader:
-
     def __init__(self, database_connector: DatabaseConnector):
         self.database_connector = database_connector
 

image_prediction/model_loader/loaders/mlflow.py

@@ -3,7 +3,6 @@ from image_prediction.redai_adapter.mlflow import MlflowModelReader
 
 
 class MlflowConnector(DatabaseConnector):
-
     def __init__(self, mlflow_reader: MlflowModelReader):
         self.mlflow_reader = mlflow_reader
 

image_prediction/pipeline.py

@@ -48,7 +48,6 @@ def get_formatter():
 
 
 class Pipeline:
-
     def __init__(self):
         self.pipe = rcompose(get_extractor_classifier(), get_formatter())
 

image_prediction/redai_adapter/mlflow.py

@@ -9,7 +9,6 @@ from image_prediction.redai_adapter.model import PredictionModelHandle
 
 
 class MlflowModelReader:
-
     def __init__(self, mlruns_dir=None):
         self.mlruns_dir = mlruns_dir
         mlflow.set_tracking_uri(self.mlruns_dir)