Improve code style

MLStructFP_benchmarks/ml/model/architectures/_fp_base.py

@@ -144,6 +144,7 @@ def _custom_save_session(self, filename: str, data: dict) -> None:
             if self._get_session_data('train_samples') is None:
                 self._register_session_data('train_samples', os.path.join(_PATH_SESSION, f'samples_{random.getrandbits(64)}.npz'))
             samples_f = self._get_session_data('train_samples')
+            # noinspection PyTypeChecker
             np.savez_compressed(samples_f, data=self._samples)
 
     def _custom_load_session(

MLStructFP_benchmarks/ml/model/architectures/_fp_pix2pix.py

@@ -56,8 +56,8 @@ def __init__(
         :param image_shape: Input shape
         :param kwargs: Optional keyword arguments
         """
-
         # Create base model
+        # noinspection PyArgumentList
         BaseFloorPhotoModel.__init__(self, data, name, image_shape, **kwargs.get('path', ''))
         self._output_layers = ['discriminator', 'generator']
 

MLStructFP_benchmarks/ml/model/core/_model.py

@@ -2176,12 +2176,12 @@ def load_session(
         assert data['version'] == _SESSION_EXPORT_VERSION, _ver
 
         # Assert object class
-        _class = 'Session model class <{0}> is different than current ' \
+        _class = 'Session model class <{0}> is different from current ' \
                  'model class <{1}>'.format(data['class'], self.__class__.__name__)
         assert data['class'] == self.__class__.__name__, _class
 
         # Assert class version
-        _classv = 'Session class version <{0}> is different than current ' \
+        _classv = 'Session class version <{0}> is different from current ' \
                   'model class version <{1}>'.format(data['class_version'], self._version)
         assert data['class_version'] == self._version, _classv
 
@@ -2267,7 +2267,7 @@ def load_session(
         current_compile_config: Dict[str, Any] = self._get_compile_config()
         if current_compile_config != data['compile_config'] and len(current_compile_config.keys()) > 0 \
                 and self._check_compilation:
-            _compile_msg = 'Compile configuration from session is different than the current model'
+            _compile_msg = 'Compile configuration from session is different from the current model'
             # warnings.warn(_compile_msg)
             self._print(_compile_msg + ':')
             for k in current_compile_config.keys():

MLStructFP_benchmarks/ml/model/core/_utils.py

@@ -19,6 +19,7 @@
 import tensorflow as tf
 
 
+# noinspection PyTypeChecker
 def load_model_from_session(
         filename: str,
         enable_memory_growth: Optional[bool] = None,

MLStructFP_benchmarks/ml/utils/callbacks/_tensorboardv2.py

@@ -189,7 +189,7 @@ def _configure_embeddings(self) -> None:
             from tensorboard.plugins import projector
         except ImportError:
             raise ImportError('Failed to import TensorBoard. Please make sure that '
-                              'TensorBoard integration is complete."')
+                              'TensorBoard integration is complete.')
         config = projector.ProjectorConfig()
         for layer in self.model.layers:
             if isinstance(layer, embeddings.Embedding):

MLStructFP_benchmarks/utils/_fp_db.py

@@ -170,7 +170,7 @@ def _process_floor(
         :param floor: Floor to process
         :param kwargs: Keyword optional arguments
         :param rotation_angles: Which rotation angles are applied to the floor plan
-        :returns: Number of (added, ignored) patches
+        :return: Number of (added, ignored) patches
         """
         if floor.id in self._processed_floor:
             raise ValueError(f'Floor ID {floor.id} already processed')

dvec/util_files/data/transforms/degradation_models.py

@@ -100,7 +100,7 @@ def do_degrade(self, image):
 
         :param image: input image
         :type image: numpy.ndarray of shape [h, w] with values in range [0, 255)
-        :returns: degraded image
+        :return: degraded image
         :rtype: numpy.ndarray of shape [h, w] with values in range [0, 255)
         """
         degradations = self.degradations[np.random.choice(len(self.degradations))]