fix pep8

Author: itearsl

bench.py

@@ -505,8 +505,8 @@ def gen_basic_dict(library, algorithm, stage, params, data, alg_instance=None,
             alg_instance_params = dict(alg_instance.get_params())
             print(alg_instance_params)
             if ('min_samples_split' in alg_instance_params
-            and 'handle' in alg_instance_params
-            and 'cuml' in str(alg_instance_params['handle'])):
+                    and 'handle' in alg_instance_params
+                    and 'cuml' in str(alg_instance_params['handle'])):
                 print(str(alg_instance_params['dtype']))
                 alg_instance_params['dtype'] = str(alg_instance_params['dtype'])
         result['algorithm_parameters'].update(alg_instance_params)

cuml_bench/tsne.py

@@ -8,7 +8,8 @@
                     help='Dimension of the embedded space.')
 parser.add_argument('--early-exaggeration', type=float, default=12.0,
                     help='Controls how tight natural clusters in the '
-                    'original space are in the embedded space and how much space will be between them.')
+                    'original space are in the embedded space and how much '
+                    'space will be between them.')
 parser.add_argument('--learning-rate', type=float, default=200.0,
                     help='The learning rate for t-SNE is usually in the range [10.0, 1000.0].')
 parser.add_argument('--angle', type=float, default=0.5,

sklearn_bench/tsne.py

@@ -54,7 +54,8 @@ def main():
                         help='Dimension of the embedded space.')
     parser.add_argument('--early-exaggeration', type=float, default=12.0,
                         help='Controls how tight natural clusters in the'
-                        'original space are in the embedded space and how much space will be between them.')
+                        'original space are in the embedded space and how '
+                        'much space will be between them.')
     parser.add_argument('--learning-rate', type=float, default=200.0,
                         help='The learning rate for t-SNE is usually in the range [10.0, 1000.0].')
     parser.add_argument('--angle', type=float, default=0.5,