update v0.4.1

README.md

@@ -25,8 +25,8 @@ pip install pytorch-gan-metrics
 |                   |Train IS  |Test IS   |Train(50k) vs Test(10k)<br>FID|
 |-------------------|:--------:|:--------:|:----------------------------:|
 |Official           |11.24±0.20|10.98±0.22|3.1508                        |
-|pytorch-gan-metrics|11.26±0.27|10.97±0.33|3.1517                        |
-|pytorch-gan-metrics<br>`use_torch=True`|11.26±0.21|10.97±0.34|3.1377                        |
+|pytorch-gan-metrics|11.26±0.08|10.97±0.32|3.1517                        |
+|pytorch-gan-metrics<br>`use_torch=True`|11.26±0.08|10.97±0.34|3.1455                        |
 
 The results are slightly different from official implementations due to the framework difference between PyTorch and TensorFlow.
 

pytorch_gan_metrics/calc_metrics.py

@@ -11,10 +11,12 @@
                         help='path to image directory')
     parser.add_argument('--stats', type=str, required=True,
                         help='precalculated reference statistics')
+    parser.add_argument('--use_torch', action='store_true',
+                        help='using pytorch as the matrix operations backend')
     args = parser.parse_args()
 
     dataset = ImageDataset(args.path, exts=['png', 'jpg'])
     loader = DataLoader(dataset, batch_size=50, num_workers=4)
     (IS, IS_std), FID = get_inception_score_and_fid(
-        loader, args.stats, verbose=True)
+        loader, args.stats, use_torch=args.use_torch, verbose=True)
     print(IS, IS_std, FID)

setup.py

@@ -11,7 +11,7 @@ def read(rel_path):
 if __name__ == '__main__':
     setuptools.setup(
         name='pytorch_gan_metrics',
-        version='0.4.0',
+        version='0.4.1',
         author='Yi-Lun Wu',
         author_email='[email protected]',
         description=('Package for calculating GAN metrics using Pytorch'),