Apply suggestions from code review

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: constantinpape

bioimageio/core/__main__.py

@@ -267,8 +267,9 @@ def convert_keras_weights_to_tensorflow(
         ret_code = keras_converter.convert_weights_to_tensorflow_saved_model_bundle(model_rdf, output_path)
         sys.exit(ret_code)
 
-    convert_keras_weights_to_tensorflow.__doc__ =\
+    convert_keras_weights_to_tensorflow.__doc__ = (
         keras_converter.convert_weights_to_tensorflow_saved_model_bundle.__doc__
+    )
 
 
 if __name__ == "__main__":

bioimageio/core/build_spec/build_model.py

@@ -86,7 +86,7 @@ def _get_weights(
     model_kwargs=None,
     tensorflow_version=None,
     opset_version=None,
-    **kwargs
+    **kwargs,
 ):
     weight_path = resolve_source(original_weight_source, root)
     if weight_type is None:
@@ -769,8 +769,7 @@ def add_weights(
     opset_version: Optional[str] = None,
     **weight_kwargs,
 ):
-    """Add weight entry to bioimage.io model.
-    """
+    """Add weight entry to bioimage.io model."""
     # we need to pass the weight path as abs path to avoid confusion with different root directories
     new_weights, tmp_arch = _get_weights(
         Path(weight_uri).absolute(),

bioimageio/core/prediction_pipeline/_model_adapters/_keras_model_adapter.py

@@ -5,9 +5,11 @@
 try:
     from tensorflow import keras
     import tensorflow as tf
+
     TF_VERSION = tf.__version__
 except Exception:
     import keras
+
     TF_VERSION = None
 import xarray as xr
 

bioimageio/core/weight_converter/keras/tensorflow.py

@@ -20,14 +20,14 @@ def _convert_tf1(keras_weight_path, output_path, zip_weights):
 
     builder = saved_model.builder.SavedModelBuilder(output_path)
     signature = saved_model.signature_def_utils.predict_signature_def(
-        inputs={'input': keras_model.input}, outputs={'output': keras_model.output}
+        inputs={"input": keras_model.input}, outputs={"output": keras_model.output}
     )
 
     signature_def_map = {saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signature}
 
-    builder.add_meta_graph_and_variables(keras.backend.get_session(),
-                                         [saved_model.tag_constants.SERVING],
-                                         signature_def_map=signature_def_map)
+    builder.add_meta_graph_and_variables(
+        keras.backend.get_session(), [saved_model.tag_constants.SERVING], signature_def_map=signature_def_map
+    )
     builder.save()
 
     if zip_weights:

tests/conftest.py

@@ -200,8 +200,6 @@ def unet2d_multi_tensor_or_not(request):
     return pytest.model_packages[request.param]
 
 
-@pytest.fixture(
-    params=[] if skip_keras else ["unet2d_keras"]
-)
+@pytest.fixture(params=[] if skip_keras else ["unet2d_keras"])
 def unet2d_keras(request):
     return pytest.model_packages[request.param]

tests/weight_converter/keras/test_tensorflow.py

@@ -1,5 +1,3 @@
-
-
 def test_tensorflow_converter(any_keras_model, tmp_path):
     from bioimageio.core.weight_converter.keras import convert_weights_to_tensorflow_saved_model_bundle
 

tests/weight_converter/torch/test_torchscript.py

@@ -1,5 +1,3 @@
-
-
 def test_torchscript_converter(any_torch_model, tmp_path):
     from bioimageio.core.weight_converter.torch import convert_weights_to_pytorch_script