applied black

image_prediction/estimator/adapter/adapters/mock.py

@@ -8,7 +8,6 @@ class DummyEstimator:
 
 
 class EstimatorAdapterMock(EstimatorAdapter):
-
     def __init__(self, estimator):
         super().__init__(estimator=estimator)
 

image_prediction/estimator/preprocessor/preprocessor.py

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

test/unit_tests/conftest.py

@@ -45,14 +45,16 @@ def estimator_adapter(estimator_type, keras_model, output_batch_generator, monke
 @pytest.fixture
 def keras_model(input_size):
     import warnings
+
     warnings.filterwarnings("ignore", category=DeprecationWarning)
 
     import os
-    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+
+    os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 
     import tensorflow as tf
 
-    tf.keras.backend.set_image_data_format('channels_last')
+    tf.keras.backend.set_image_data_format("channels_last")
 
     inputs = tf.keras.Input(shape=input_size)
     conv = tf.keras.layers.Conv2D(3, 3)

test/unit_tests/estimator_test.py

@@ -17,7 +17,6 @@ def test_predict(estimator, input_batch, expected_predictions):
 
 @pytest.mark.parametrize("batch_size", [0, 1, 2, 16, 32, 64])
 def test_batch_format(input_batch):
-
     def channels_are_last(input_batch):
         return input_batch.shape[-1] == 3
 

test/unit_tests/predictor_test.py

@@ -24,7 +24,7 @@ def test_chunk_iterable_no_split():
 
 def test_chunk_iterable_last_partial():
     a, b, c, d = chunk_iterable(range(10), chunk_size=3)
-    assert d == (9, )
+    assert d == (9,)
 
 
 def test_chunk_iterable_empty():