introduced estimator-adapter and estimator-adapter-patch

image_prediction/estimator/adapter/adapter.py

@@ -0,0 +1,10 @@
+import abc
+
+
+class EstimatorAdapter(abc.ABC):
+    def __init__(self, estimator):
+        self.estimator = estimator
+
+    @abc.abstractmethod
+    def predict(self, batch):
+        pass

image_prediction/estimator/adapter/patch.py

@@ -0,0 +1,20 @@
+from image_prediction.estimator.adapter.adapter import EstimatorAdapter
+from image_prediction.estimator.estimator import Estimator
+
+
+class EstimatorAdapterPatch(EstimatorAdapter):
+    def __init__(self, estimator: Estimator):
+        super().__init__(estimator=estimator)
+        self.__output_batch = None
+
+    @property
+    def output_batch(self):
+        return self.__output_batch
+
+    @output_batch.setter
+    def output_batch(self, output_batch):
+        self.__output_batch = output_batch
+
+    def predict(self, batch):
+        self.estimator.predict(batch)
+        return self.__output_batch

image_prediction/estimator/estimator.py

@@ -0,0 +1,10 @@
+import abc
+
+
+class Estimator(abc.ABC):
+    def __init__(self, estimator):
+        self.estimator = estimator
+
+    @abc.abstractmethod
+    def predict(self, batch):
+        pass

image_prediction/estimator/estimators/mock.py

@@ -0,0 +1,10 @@
+from image_prediction.estimator.estimator import Estimator
+
+
+class EstimatorMock(Estimator):
+
+    def __init__(self, estimator=lambda x: x):
+        super().__init__(estimator=estimator)
+
+    def predict(self, batch):
+        return self.estimator(batch)

image_prediction/estimator/mock.py

@@ -1,14 +0,0 @@
-class EstimatorMock:
-    def __init__(self):
-        self.__output_batch = None
-
-    @property
-    def output_batch(self):
-        return self.__output_batch
-
-    @output_batch.setter
-    def output_batch(self, output_batch):
-        self.__output_batch = output_batch
-
-    def predict(self, batch):
-        return self.__output_batch

image_prediction/service_estimator/mock.py

@@ -1,6 +0,0 @@
-from image_prediction.service_estimator.service_estimator import ServiceEstimator
-
-
-class ServiceEstimatorMock(ServiceEstimator):
-    def __init__(self, estimator, classes):
-        super().__init__(estimator=estimator, classes=classes)

image_prediction/service_estimator/service_estimator.py

@@ -1,14 +1,12 @@
-import abc
+from typing import Mapping, List
+
+from image_prediction.estimator.adapter.adapter import EstimatorAdapter
 
 
-class ServiceEstimator(abc.ABC):
+class ServiceEstimator:
-    def __init__(self, estimator, classes):
+    def __init__(self, estimator_adapter: EstimatorAdapter, classes: Mapping[int, str]):
-        self.__estimator = estimator
+        self.__estimator_adapter = estimator_adapter
         self.__classes = classes
 
-    @property
+    def predict(self, batch) -> List[str]:
-    def estimator(self):
+        return [self.__classes[numeric_label] for numeric_label in self.__estimator_adapter.predict(batch)]
-        return self.__estimator
-
-    def predict(self, batch):
-        return [self.__classes[numeric_label] for numeric_label in self.estimator.predict(batch)]

test/unit_tests/service_estimator_test.py

@@ -3,8 +3,9 @@ import logging
 import numpy as np
 import pytest
 
-from image_prediction.estimator.mock import EstimatorMock
+from image_prediction.estimator.estimators.mock import EstimatorMock
-from image_prediction.service_estimator.mock import ServiceEstimatorMock
+from image_prediction.estimator.adapter.patch import EstimatorAdapterPatch
+from image_prediction.service_estimator.service_estimator import ServiceEstimator
 from image_prediction.utils import get_logger
 
 logger = get_logger()
@@ -12,10 +13,16 @@ logger.setLevel(logging.DEBUG)
 
 
 @pytest.fixture(scope="session")
-def estimator(output_batch):
+def estimator(estimator_type):
-    estimator = EstimatorMock()
+    if estimator_type == "mock":
-    estimator.output_batch = output_batch
+        return EstimatorMock()
-    return estimator
+
+
+@pytest.fixture(scope="session")
+def estimator_adapter(output_batch, estimator):
+    estimator_adapter = EstimatorAdapterPatch(estimator)
+    estimator_adapter.output_batch = output_batch
+    return estimator_adapter
 
 
 @pytest.fixture(scope="session")
@@ -43,12 +50,11 @@ def map_labels(numeric_labels, classes):
 
 
 @pytest.fixture(scope="session")
-def service_estimator(model_type, estimator, classes):
+def service_estimator(estimator_adapter, classes):
-    if model_type == "mock":
+    return ServiceEstimator(estimator_adapter, classes)
-        return ServiceEstimatorMock(estimator, classes)
 
 
-@pytest.mark.parametrize("model_type", ["mock"], scope="session")
+@pytest.mark.parametrize("estimator_type", ["mock"], scope="session")
 @pytest.mark.parametrize("batch_size", [0, 1, 2, 16, 32, 64], scope="session")
 def test_predict(service_estimator, input_batch, expected_predictions):
     predictions = service_estimator.predict(input_batch)