fix bench.py

Author: itearsl

cuml_bench/tsne.py

@@ -5,7 +5,7 @@
 parser = argparse.ArgumentParser(description='cuml tsne')
 
 parser.add_argument('--n-components', type=int, default=2,
-                    help='Dimension of the embedded space.')
+                    help='The dimension of the embedded space.')
 parser.add_argument('--early-exaggeration', type=float, default=12.0,
                     help='This factor increases the attractive forces between points '
                     'and allows points to move around more freely, '
@@ -16,7 +16,7 @@
                     help='Angular size. This is the trade-off between speed and accuracy.')
 parser.add_argument('--min-grad-norm', type=float, default=1e-7,
                     help='If the gradient norm is below this threshold,'
-                    'the optimization will be stopped.')
+                    'the optimization is stopped.')
 parser.add_argument('--random-state', type=int, default=1234)
 params = bench.parse_args(parser)
 

datasets/load_datasets.py

@@ -85,11 +85,11 @@ def try_load_dataset(dataset_name: str, output_directory: Path) -> bool:
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(
         description='Use \'-d\' or \'--datasets\' option to enumerate '
-                    'dataset(s) which should be downloaded')
+                    'dataset(s) that should be downloaded')
     parser.add_argument('-l', '--list', action='store_const',
-                        const=True, help='list of available datasets')
+                        const=True, help='The list of available datasets')
     parser.add_argument('-d', '--datasets', type=str, nargs='*',
-                        help='datasets which should be downloaded')
+                        help='The datasets that should be downloaded.')
     args = parser.parse_args()
 
     if args.list:
@@ -104,4 +104,4 @@ def try_load_dataset(dataset_name: str, output_directory: Path) -> bool:
             val(root_dir)
     else:
         logging.warning(
-            'Warning: Enumerate dataset(s) which should be downloaded')
+            'Warning: Enumerate dataset(s) that should be downloaded')

sklearn_bench/tsne.py

@@ -51,7 +51,7 @@ def main():
                                      'regression benchmark')
 
     parser.add_argument('--n-components', type=int, default=2,
-                        help='Dimension of the embedded space.')
+                        help='The dimension of the embedded space.')
     parser.add_argument('--early-exaggeration', type=float, default=12.0,
                         help='This factor increases the attractive forces between points '
                         'and allows points to move around more freely, '
@@ -62,7 +62,7 @@ def main():
                         help='Angular size. This is the trade-off between speed and accuracy.')
     parser.add_argument('--min-grad-norm', type=float, default=1e-7,
                         help='If the gradient norm is below this threshold,'
-                        'the optimization will be stopped.')
+                        'the optimization is stopped.')
     parser.add_argument('--random-state', type=int, default=1234)
 
     params = bench.parse_args(parser)