Add tests for decoders on empty inputs.

tests/icosagon/test_decode.py

@@ -158,3 +158,55 @@ def test_is_inner_product_symmetric_01():
 
     for i in range(len(res_1)):
         assert torch.all(res_1[i] - res_2[i] < 0.000001)
+
+
+def test_empty_dedicom_decoder_01():
+    repr_ = torch.rand(0, 32)
+    dec = DEDICOMDecoder(32, 7, keep_prob=1.,
+        activation=torch.sigmoid)
+
+    res = [ dec(repr_, repr_, k) for k in range(7) ]
+
+    assert isinstance(res, list)
+
+    for i in range(len(res)):
+        assert res[i].shape == (0,)
+
+
+def test_empty_dist_mult_decoder_01():
+    repr_ = torch.rand(0, 32)
+    dec = DistMultDecoder(32, 7, keep_prob=1.,
+        activation=torch.sigmoid)
+
+    res = [ dec(repr_, repr_, k) for k in range(7) ]
+
+    assert isinstance(res, list)
+
+    for i in range(len(res)):
+        assert res[i].shape == (0,)
+
+
+def test_empty_bilinear_decoder_01():
+    repr_ = torch.rand(0, 32)
+    dec = BilinearDecoder(32, 7, keep_prob=1.,
+        activation=torch.sigmoid)
+
+    res = [ dec(repr_, repr_, k) for k in range(7) ]
+
+    assert isinstance(res, list)
+
+    for i in range(len(res)):
+        assert res[i].shape == (0,)
+
+
+def test_empty_inner_product_decoder_01():
+    repr_ = torch.rand(0, 32)
+    dec = InnerProductDecoder(32, 7, keep_prob=1.,
+        activation=torch.sigmoid)
+
+    res = [ dec(repr_, repr_, k) for k in range(7) ]
+
+    assert isinstance(res, list)
+
+    for i in range(len(res)):
+        assert res[i].shape == (0,)