renaming

test/unit_tests/classifier_test.py

@@ -9,9 +9,9 @@ logger.setLevel(logging.DEBUG)
 
 
 @pytest.mark.parametrize("estimator_type", ["mock", "keras"])
-def test_predict(classifier, input_batch, expected_predictions):
+def test_predict(classifier, input_batch, expected_batch_string_labels):
     predictions = classifier.predict(input_batch)
-    assert predictions == expected_predictions
+    assert predictions == expected_batch_string_labels
 
 
 def test_batch_format(input_batch):

test/unit_tests/conftest.py

@@ -37,7 +37,7 @@ def image_extractor(extractor_type):
 
 
 @pytest.fixture
-def image_classifier(classifier, monkeypatch, expected_predictions):
+def image_classifier(classifier, monkeypatch, expected_batch_string_labels):
     return ImageClassifier(classifier, preprocessor=BasicPreprocessor())
 
 
@@ -129,18 +129,18 @@ def input_size(request):
 
 
 @pytest.fixture
-def expected_predictions(output_batch, classes):
-    return map_labels(output_batch, classes)
+def expected_batch_string_labels(expected_batch_numeric_labels, classes):
+    return map_labels(expected_batch_numeric_labels, classes)
 
 
 @pytest.fixture
-def output_batch(input_batch, classes):
+def expected_batch_numeric_labels(input_batch, classes):
     return random.choices(range(len(classes)), k=len(input_batch))
 
 
 @pytest.fixture
-def output_batch_generator(output_batch):
-    return iter(output_batch)
+def output_batch_generator(expected_batch_numeric_labels):
+    return iter(expected_batch_numeric_labels)
 
 
 @pytest.fixture

test/unit_tests/extractor_classifier_test.py

@@ -7,8 +7,8 @@ from image_prediction.extractor_classifier.extractor_classifier import Extractor
 
 @pytest.mark.parametrize("extractor_type", ["mock"])
 @pytest.mark.parametrize("estimator_type", ["mock", "keras"])
-def test_extractor_classifier(image_extractor, image_classifier, images, expected_predictions):
+def test_extractor_classifier(image_extractor, image_classifier, images, expected_batch_string_labels):
     extractor_classifier = ExtractorClassifier(image_extractor, image_classifier)
     results = extractor_classifier(images)
     labels = list(map(itemgetter("prediction"), results))
-    assert labels == expected_predictions
+    assert labels == expected_batch_string_labels

test/unit_tests/image_classifier_test.py

@@ -4,9 +4,9 @@ from image_prediction.utils import chunk_iterable
 
 
 @pytest.mark.parametrize("estimator_type", ["mock", "keras"])
-def test_predict(image_classifier, images, expected_predictions):
+def test_predict(image_classifier, images, expected_batch_string_labels):
     predictions = list(image_classifier.predict(images))
-    assert predictions == expected_predictions
+    assert predictions == expected_batch_string_labels
 
 
 def test_chunk_iterable_exact_split():