removing unused code / refactoring for coverage maximization

image_prediction/estimator/preprocessor/preprocessor.py

@@ -2,10 +2,11 @@ import abc
 
 
 class Preprocessor(abc.ABC):
+
     @staticmethod
     @abc.abstractmethod
     def preprocess(batch):
-        pass
+        raise NotImplementedError
 
     def __call__(self, batch):
         return self.preprocess(batch)

image_prediction/estimator/preprocessor/preprocessors/basic.py

@@ -8,6 +8,3 @@ class BasicPreprocessor(Preprocessor):
     @staticmethod
     def preprocess(images):
         return images_to_batch_tensor(images)
-
-    def __call__(self, images):
-        return self.preprocess(images)

image_prediction/extractor_classifier/extractor_classifier.py

@@ -15,10 +15,7 @@ class ExtractorClassifier:
         self.extractor = image_extractor
 
     def __process_batch(self, batch):
-        try:
-            images, metadata = zip(*batch)
-        except ValueError:
-            return []
+        images, metadata = zip(*batch)
 
         predictions = self.classifier(images)
         responses = ({"prediction": prd, **mdt} for prd, mdt in zip(predictions, metadata))

image_prediction/formatter/formatter.py

@@ -2,5 +2,7 @@ import abc
 
 
 class Formatter(abc.ABC):
+
+    @abc.abstractmethod
     def format(self, info: dict):
-        pass
+        raise NotImplementedError