test

Author: EdisonLeeeee

test/nn/conv/test_gin_conv.py

@@ -26,9 +26,9 @@ def test_gin_conv():
         '))')
     out = conv(x1, edge_index)
     assert out.size() == (4, 32)
-    assert conv(x1, edge_index, size=(4, 4)).tolist() == out.tolist()
-    assert conv(x1, adj.t()).tolist() == out.tolist()
-    assert conv(x1, adj2.t()).tolist() == out.tolist()
+    assert torch.allclose(conv(x1, edge_index, size=(4, 4)), out, atol=1e-6)
+    assert torch.allclose(conv(x1, adj.t()), out, atol=1e-6)
+    assert torch.allclose(conv(x1, adj2.t()), out, atol=1e-6)
 
     if is_full_test():
         t = '(Tensor, Tensor, Size) -> Tensor'
@@ -46,11 +46,11 @@ def test_gin_conv():
     out2 = conv((x1, None), edge_index, (4, 2))
     assert out1.size() == (2, 32)
     assert out2.size() == (2, 32)
-    assert conv((x1, x2), edge_index, (4, 2)).tolist() == out1.tolist()
-    assert conv((x1, x2), adj.t()).tolist() == out1.tolist()
-    assert conv((x1, None), adj.t()).tolist() == out2.tolist()
-    assert conv((x1, x2), adj2.t()).tolist() == out1.tolist()
-    assert conv((x1, None), adj2.t()).tolist() == out2.tolist()
+    assert torch.allclose(conv((x1, x2), edge_index, (4, 2)), out1, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj.t()), out1, atol=1e-6)
+    assert torch.allclose(conv((x1, None), adj.t()), out2, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj2.t()), out1, atol=1e-6)
+    assert torch.allclose(conv((x1, None), adj2.t()), out2, atol=1e-6)
 
     if is_full_test():
         t = '(OptPairTensor, Tensor, Size) -> Tensor'

test/nn/conv/test_graph_conv.py

@@ -20,15 +20,16 @@ def test_graph_conv():
     assert conv.__repr__() == 'GraphConv(8, 32)'
     out11 = conv(x1, edge_index)
     assert out11.size() == (4, 32)
-    assert conv(x1, edge_index, size=(4, 4)).tolist() == out11.tolist()
-    assert conv(x1, adj1.t()).tolist() == out11.tolist()
-    assert conv(x1, adj3.t()).tolist() == out11.tolist()
+    assert torch.allclose(conv(x1, edge_index, size=(4, 4)), out11, atol=1e-6)
+    assert torch.allclose(conv(x1, adj1.t()), out11, atol=1e-6)
+    assert torch.allclose(conv(x1, adj3.t()), out11, atol=1e-6)
 
     out12 = conv(x1, edge_index, value)
     assert out12.size() == (4, 32)
-    assert conv(x1, edge_index, value, size=(4, 4)).tolist() == out12.tolist()
-    assert conv(x1, adj2.t()).tolist() == out12.tolist()
-    assert conv(x1, adj4.t()).tolist() == out12.tolist()
+    assert torch.allclose(conv(x1, edge_index, value, size=(4, 4)), out12,
+                          atol=1e-6)
+    assert torch.allclose(conv(x1, adj2.t()), out12, atol=1e-6)
+    assert torch.allclose(conv(x1, adj4.t()), out12, atol=1e-6)
 
     if is_full_test():
         t = '(Tensor, Tensor, OptTensor, Size) -> Tensor'
@@ -58,12 +59,14 @@ def test_graph_conv():
     assert out22.size() == (2, 32)
     assert out23.size() == (2, 32)
     assert out24.size() == (2, 32)
-    assert conv((x1, x2), edge_index, size=(4, 2)).tolist() == out21.tolist()
-    assert conv((x1, x2), edge_index, value, (4, 2)).tolist() == out22.tolist()
-    assert conv((x1, x2), adj1.t()).tolist() == out21.tolist()
-    assert conv((x1, x2), adj2.t()).tolist() == out22.tolist()
-    assert conv((x1, x2), adj3.t()).tolist() == out21.tolist()
-    assert conv((x1, x2), adj4.t()).tolist() == out22.tolist()
+    assert torch.allclose(conv((x1, x2), edge_index, size=(4, 2)), out21,
+                          atol=1e-6)
+    assert torch.allclose(conv((x1, x2), edge_index, value, (4, 2)), out22,
+                          atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj1.t()), out21, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj2.t()), out22, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj3.t()), out21, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj4.t()), out22, atol=1e-6)
 
     if is_full_test():
         t = '(OptPairTensor, Tensor, OptTensor, Size) -> Tensor'

test/nn/conv/test_sage_conv.py

@@ -20,20 +20,20 @@ def test_sage_conv(project, aggr):
     assert str(conv) == f'SAGEConv(8, 32, aggr={aggr})'
     out = conv(x1, edge_index)
     assert out.size() == (4, 32)
-    assert conv(x1, edge_index, size=(4, 4)).tolist() == out.tolist()
-    assert conv(x1, adj.t()).tolist() == out.tolist()
+    assert torch.allclose(conv(x1, edge_index, size=(4, 4)), out, atol=1e-6)
+    assert torch.allclose(conv(x1, adj.t()), out, atol=1e-6)
     if aggr == 'sum':
-        assert conv(x1, adj2.t()).tolist() == out.tolist()
+        assert torch.allclose(conv(x1, adj2.t()), out, atol=1e-6)
 
     if is_full_test():
         t = '(Tensor, Tensor, Size) -> Tensor'
         jit = torch.jit.script(conv.jittable(t))
-        assert jit(x1, edge_index).tolist() == out.tolist()
-        assert jit(x1, edge_index, size=(4, 4)).tolist() == out.tolist()
+        assert torch.allclose(jit(x1, edge_index), out, atol=1e-6)
+        assert torch.allclose(jit(x1, edge_index, size=(4, 4)), out, atol=1e-6)
 
         t = '(Tensor, SparseTensor, Size) -> Tensor'
         jit = torch.jit.script(conv.jittable(t))
-        assert jit(x1, adj.t()).tolist() == out.tolist()
+        assert torch.allclose(jit(x1, adj.t()), out, atol=1e-6)
 
     adj = adj.sparse_resize((4, 2))
     adj2 = adj.to_torch_sparse_coo_tensor()
@@ -43,25 +43,26 @@ def test_sage_conv(project, aggr):
     out2 = conv((x1, None), edge_index, (4, 2))
     assert out1.size() == (2, 32)
     assert out2.size() == (2, 32)
-    assert conv((x1, x2), edge_index, (4, 2)).tolist() == out1.tolist()
-    assert conv((x1, x2), adj.t()).tolist() == out1.tolist()
-    assert conv((x1, None), adj.t()).tolist() == out2.tolist()
+    assert torch.allclose(conv((x1, x2), edge_index, (4, 2)), out1, atol=1e-6)
+    assert torch.allclose(conv((x1, x2), adj.t()), out1, atol=1e-6)
+    assert torch.allclose(conv((x1, None), adj.t()), out2, atol=1e-6)
     if aggr == 'sum':
-        assert conv((x1, x2), adj2.t()).tolist() == out1.tolist()
-        assert conv((x1, None), adj2.t()).tolist() == out2.tolist()
+        assert torch.allclose(conv((x1, x2), adj2.t()), out1, atol=1e-6)
+        assert torch.allclose(conv((x1, None), adj2.t()), out2, atol=1e-6)
 
     if is_full_test():
         t = '(OptPairTensor, Tensor, Size) -> Tensor'
         jit = torch.jit.script(conv.jittable(t))
-        assert jit((x1, x2), edge_index).tolist() == out1.tolist()
-        assert jit((x1, x2), edge_index, size=(4, 2)).tolist() == out1.tolist()
-        assert jit((x1, None), edge_index,
-                   size=(4, 2)).tolist() == out2.tolist()
+        assert torch.allclose(jit((x1, x2), edge_index), out1, atol=1e-6)
+        assert torch.allclose(jit((x1, x2), edge_index, size=(4, 2)), out1,
+                              atol=1e-6)
+        assert torch.allclose(jit((x1, None), edge_index, size=(4, 2)), out2,
+                              atol=1e-6)
 
         t = '(OptPairTensor, SparseTensor, Size) -> Tensor'
         jit = torch.jit.script(conv.jittable(t))
-        assert jit((x1, x2), adj.t()).tolist() == out1.tolist()
-        assert jit((x1, None), adj.t()).tolist() == out2.tolist()
+        assert torch.allclose(jit((x1, x2), adj.t()), out1, atol=1e-6)
+        assert torch.allclose(jit((x1, None), adj.t()), out2, atol=1e-6)
 
 
 def test_lstm_aggr_sage_conv():