bugfix

VERSION

@@ -1 +1 @@
-1.0.7
+1.0.8

gs_divergence/__init__.py

@@ -1,4 +1,4 @@
 from gs_divergence.geodesical_skew_divergence import gs_div
 from gs_divergence.symmetrized_geodesical_skew_divergence import symmetrized_gs_div
 
-__version__ = '1.0.7'
+__version__ = '1.0.8'

gs_divergence/geodesical_skew_divergence.py

@@ -30,7 +30,7 @@ def gs_div(
     assert lmd >= 0 and lmd <= 1
 
     skew_target = alpha_geodesic(input, target, alpha=alpha, lmd=lmd)
-    div = input * torch.log(input / skew_target)
+    div = input * torch.log(input / skew_target + 1e-12)
     if reduction == 'batchmean':
         div = div.sum() / input.size()[0]
     elif reduction == 'sum':

tests/test_alpha_geodesic.py

@@ -72,6 +72,7 @@ def test_value_inf(self):
         b = torch.Tensor([[0.4, 0.4, 0.2], [0.2, 0.1, 0.7]])
 
         g = alpha_geodesic(a, b, alpha=100, lmd=0.5)
+        print(g)
         res = torch.min(a, b)
 
         self.assertTrue(torch.all(torch.isclose(g, res)))

tests/test_gs_div.py

@@ -0,0 +1,21 @@
+import unittest
+import torch
+
+from gs_divergence import gs_div
+
+
+class TestGSDiv(unittest.TestCase):
+    def test_alpha_minus_1(self):
+        a = torch.Tensor([1, 2, 3])
+        b = torch.Tensor([4, 5, 6])
+        g = gs_div(a, b, alpha=-1, lmd=0.5)
+
+        self.assertIsNotNone(g)
+
+    def test_value_0_2d(self):
+        a = torch.Tensor([[0.1, 0.2, 0.7], [0.5, 0.5, 0.0]])
+        b = torch.Tensor([[0.4, 0.4, 0.2], [0.2, 0.1, 0.7]])
+
+        g = gs_div(a, b, alpha=1, lmd=0.5)
+
+        self.assertTrue(torch.isinf(g).sum() == 0)