Added storage compression / decompression functions to prepare for sets of 1M samples.

[pysvrt.git] / test-svrt.py

diff --git a/test-svrt.py b/test-svrt.py
index cd98f21..5f38fa9 100755 (executable)
--- a/test-svrt.py
+++ b/test-svrt.py
@@ -34,13 +34,15 @@ from torch.nn import functional as fn
 
 from torchvision import datasets, transforms, utils
 
-from _ext import svrt
+import svrt
 
 labels = torch.LongTensor(12).zero_()
 labels.narrow(0, 0, labels.size(0)//2).fill_(1)
 
 x = svrt.generate_vignettes(4, labels)
 
+print('compression factor {:f}'.format(x.storage().size() / svrt.compress(x.storage()).size()))
+
 x = x.view(x.size(0), 1, x.size(1), x.size(2))
 
 x.div_(255)