Flake8 fixes

DLHub-Argonne · Jul 25, 2019 · a6cb035 · a6cb035
1 parent 02dbbd1
commit a6cb035
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Showing 3 changed files with 18 additions and 10 deletions.
diff --git a/dlhub_sdk/models/servables/keras.py b/dlhub_sdk/models/servables/keras.py
@@ -9,6 +9,7 @@
 _keras_version_tuple = tuple(int(i) for i in keras_version.split("."))
 _summary_limit = 10000
 
+
 def _detect_backend(output):
     """Add the backend
 
@@ -90,7 +91,7 @@ def capture_summary(x):
 
         model.summary(print_fn=capture_summary)
         output.summary = (output.summary[:_summary_limit] + '<<TRUNCATED>>') \
-                            if  len(output.summary) > _summary_limit else output.summary
+            if len(output.summary) > _summary_limit else output.summary
 
         output['servable']['model_summary'] = output.summary
         output['servable']['model_type'] = 'Deep NN'

diff --git a/dlhub_sdk/models/servables/pytorch.py b/dlhub_sdk/models/servables/pytorch.py
@@ -10,7 +10,8 @@ class TorchModel(BasePythonServableModel):
     Assumes that the model has been saved to a pt or a pth file"""
 
     @classmethod
-    def create_model(cls, model_path, input_shape, output_shape, input_type='float', output_type='float'):
+    def create_model(cls, model_path, input_shape, output_shape,
+                     input_type='float', output_type='float'):
         """Initialize a PyTorch model.
 
         Args:
@@ -33,8 +34,10 @@ def create_model(cls, model_path, input_shape, output_shape, input_type='float',
             raise ValueError('File type for architecture not recognized')
 
         # Get the inputs of the model
-        output['servable']['methods']['run']['input'] = output.format_layer_spec(input_shape, input_type)
-        output['servable']['methods']['run']['output'] = output.format_layer_spec(output_shape, output_type)
+        output['servable']['methods']['run']['input'] =\
+            output.format_layer_spec(input_shape, input_type)
+        output['servable']['methods']['run']['output'] =\
+            output.format_layer_spec(output_shape, output_type)
 
         output['servable']['model_summary'] = str(model)
         output['servable']['model_type'] = 'Deep NN'
@@ -54,7 +57,8 @@ def format_layer_spec(self, layers, datatypes):
             (dict) Description of the inputs / outputs
         """
         if isinstance(layers, tuple):
-            return compose_argument_block("ndarray", "Tensor", shape=list(layers), item_type=datatypes)
+            return compose_argument_block("ndarray", "Tensor",
+                                          shape=list(layers), item_type=datatypes)
         else:
             if isinstance(datatypes, str):
                 datatypes = [datatypes] * len(layers)

diff --git a/dlhub_sdk/models/servables/tests/test_pytorch.py b/dlhub_sdk/models/servables/tests/test_pytorch.py
@@ -105,16 +105,19 @@ def test_multinetwork(self):
             # Test the output shapes
             self.assertEqual(metadata['servable']['methods']['run']['input'],
                              {'type': 'tuple', 'description': 'Tuple of tensors',
-                              'element_types': [{'type': 'ndarray', 'description': 'Tensor', 'shape': [None, 4],
+                              'element_types': [{'type': 'ndarray',
+                                                 'description': 'Tensor', 'shape': [None, 4],
                                                  'item_type': {'type': 'float'}},
-                                                {'type': 'ndarray', 'description': 'Tensor', 'shape': [None, 4],
+                                                {'type': 'ndarray',
+                                                 'description': 'Tensor', 'shape': [None, 4],
                                                  'item_type': {'type': 'float'}}]})
             self.assertEqual(metadata['servable']['methods']['run']['output'],
                              {'type': 'tuple', 'description': 'Tuple of tensors',
-                              'element_types': [{'type': 'ndarray', 'description': 'Tensor', 'shape': [None, 1],
+                              'element_types': [{'type': 'ndarray',
+                                                 'description': 'Tensor', 'shape': [None, 1],
                                                  'item_type': {'type': 'float'}},
-                                                {'type': 'ndarray', 'description': 'Tensor', 'shape': [None, 1],
+                                                {'type': 'ndarray',
+                                                 'description': 'Tensor', 'shape': [None, 1],
                                                  'item_type': {'type': 'float'}}]})
 
             validate_against_dlhub_schema(metadata.to_dict(), 'servable')
-