Format Python code with psf/black push (#340)

There appear to be some python formatting errors in
392ddb3. This pull request
uses the [psf/black](https://github.com/psf/black) formatter to fix
these issues.

tests/fixtures/__init__.py

@@ -1,7 +1,16 @@
 from .db import options
-from .architectures import dummy_architecture, unet_architecture,unet_architecture_builder
+from .architectures import (
+    dummy_architecture,
+    unet_architecture,
+    unet_architecture_builder,
+)
 from .arrays import dummy_array, zarr_array, cellmap_array
-from .datasplits import dummy_datasplit, twelve_class_datasplit, six_class_datasplit, upsample_six_class_datasplit
+from .datasplits import (
+    dummy_datasplit,
+    twelve_class_datasplit,
+    six_class_datasplit,
+    upsample_six_class_datasplit,
+)
 from .evaluators import binary_3_channel_evaluator
 from .losses import dummy_loss
 from .post_processors import argmax, threshold

tests/fixtures/architectures.py

@@ -31,7 +31,6 @@ def unet_architecture():
     )
 
 
-
 def unet_architecture_builder(batch_norm, upsample, use_attention, three_d):
     name = "3d_unet" if three_d else "2d_unet"
     name = f"{name}_bn" if batch_norm else name
@@ -71,4 +70,3 @@ def unet_architecture_builder(batch_norm, upsample, use_attention, three_d):
             use_attention=use_attention,
             upsample_factors=[(1, 2, 2)] if upsample else [],
         )
-

tests/fixtures/datasplits.py

@@ -208,8 +208,6 @@ def six_class_datasplit(tmp_path):
     return six_class_distances_datasplit_config
 
 
-
-
 @pytest.fixture()
 def upsample_six_class_datasplit(tmp_path):
     """

tests/operations/test_train.py

@@ -68,10 +68,10 @@ def test_train(
 @pytest.mark.parametrize("datasplit", [lf("six_class_datasplit")])
 @pytest.mark.parametrize("task", [lf("distance_task")])
 @pytest.mark.parametrize("trainer", [lf("gunpowder_trainer")])
-@pytest.mark.parametrize("batch_norm", [ False])
+@pytest.mark.parametrize("batch_norm", [False])
 @pytest.mark.parametrize("upsample", [False])
-@pytest.mark.parametrize("use_attention", [ False])
-@pytest.mark.parametrize("three_d", [ False])
+@pytest.mark.parametrize("use_attention", [False])
+@pytest.mark.parametrize("three_d", [False])
 def test_train_unet(
     datasplit, task, trainer, batch_norm, upsample, use_attention, three_d
 ):
@@ -148,9 +148,6 @@ def test_train_unet(
     assert training_stats.trained_until() == run_config.num_iterations
 
 
-
-
-
 @pytest.mark.parametrize("upsample_datasplit", [lf("upsample_six_class_datasplit")])
 @pytest.mark.parametrize("task", [lf("distance_task")])
 @pytest.mark.parametrize("trainer", [lf("gunpowder_trainer")])

tests/operations/test_validate.py

@@ -101,15 +101,11 @@ def test_validate_run(
         os.chdir(old_path)
 
 
-
-
 @pytest.mark.parametrize("datasplit", [lf("six_class_datasplit")])
 @pytest.mark.parametrize("task", [lf("distance_task")])
 @pytest.mark.parametrize("trainer", [lf("gunpowder_trainer")])
 @pytest.mark.parametrize("architecture", [lf("unet_architecture")])
-def test_validate_unet(
-    datasplit, task, trainer, architecture
-):
+def test_validate_unet(datasplit, task, trainer, architecture):
     store = create_config_store()
     weights_store = create_weights_store()
 
@@ -132,4 +128,4 @@ def test_validate_unet(
 
     # -------------------------------------
     weights_store.store_weights(run, 0)
-    validate_run(run, 0)
+    validate_run(run, 0)