Add a parameter soft_target_loss to softmax_cross_entropy test

chainer · Jul 16, 2019 · f847214 · f847214
1 parent 4d50de1
commit f847214
Showing 1 changed file with 7 additions and 3 deletions.
diff --git a/tests/chainer_tests/functions_tests/loss_tests/test_softmax_cross_entropy.py b/tests/chainer_tests/functions_tests/loss_tests/test_softmax_cross_entropy.py
@@ -585,6 +585,7 @@ def test_backward_gpu(self):
     'shape': [(3,), (3, 2), (3, 2, 2)],
     'dtype': [numpy.float16, numpy.float32, numpy.float64],
     'reduce': ['mean', 'no'],
+    'soft_target_loss': ['cross-entropy', 'kl-divergence'],
 })))
 class TestSoftTargetCompareToHard(BaseSoftTarget, unittest.TestCase):
 
@@ -603,8 +604,9 @@ def check_forward(self, xp):
         x = xp.asarray(self.x)
         t = xp.asarray(self.t)
         loss = functions.softmax_cross_entropy(x, t, reduce=self.reduce)
-        expect = functions.softmax_cross_entropy(x, xp.asarray(self.t_hard),
-                                                 reduce=self.reduce)
+        expect = functions.softmax_cross_entropy(
+            x, xp.asarray(self.t_hard), reduce=self.reduce,
+            soft_target_loss=self.soft_target_loss)
         testing.assert_allclose(loss.data, expect.data,
                                 **self.check_forward_options)
 
@@ -614,6 +616,7 @@ def check_forward(self, xp):
     'shape': [(3,), (3, 2), (3, 2, 2)],
     'dtype': [numpy.float16, numpy.float32, numpy.float64],
     'reduce': ['mean', 'no'],
+    'soft_target_loss': ['cross-entropy', 'kl-divergence'],
 })))
 class TestSoftTargetExpectNearZero(BaseSoftTarget, unittest.TestCase):
 
@@ -624,7 +627,8 @@ def setUp(self):
     def check_forward(self, xp):
         x = xp.asarray(self.x)
         t = xp.asarray(self.t)
-        loss = functions.softmax_cross_entropy(x, t, reduce=self.reduce)
+        loss = functions.softmax_cross_entropy(
+            x, t, reduce=self.reduce, soft_target_loss=self.soft_target_loss)
         if self.reduce == 'mean':
             expect = 0.
         else: