Fix cugraph tests (#6907)

need more tolerance for cugraph-ops
also for cugraph conversion, we NEED to put the cugraph tensor on cpu or
tests fail. this is recommended and required by the cugraph engineers
```
>       assert torch.equal(edge_index, cu_edge_index)
E       RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument other in method wrapper_CUDA__equal)
```

test/nn/conv/cugraph/test_cugraph_gat_conv.py

@@ -39,17 +39,17 @@ def test_gat_conv_equality(bias, bipartite, concat, heads, max_num_neighbors):
 
     csc = CuGraphGATConv.to_csc(edge_index, size)
     out2 = conv2(x, csc, max_num_neighbors=max_num_neighbors)
-    assert torch.allclose(out1, out2, atol=1e-6)
+    assert torch.allclose(out1, out2, atol=1e-3)
 
     grad_output = torch.rand_like(out1)
     out1.backward(grad_output)
     out2.backward(grad_output)
 
     assert torch.allclose(conv1.lin_src.weight.grad, conv2.lin.weight.grad,
-                          atol=1e-6)
+                          atol=1e-3)
     assert torch.allclose(conv1.att_src.grad.flatten(),
-                          conv2.att.grad[:heads * out_channels], atol=1e-6)
+                          conv2.att.grad[:heads * out_channels], atol=1e-3)
     assert torch.allclose(conv1.att_dst.grad.flatten(),
-                          conv2.att.grad[heads * out_channels:], atol=1e-6)
+                          conv2.att.grad[heads * out_channels:], atol=1e-3)
     if bias:
-        assert torch.allclose(conv1.bias.grad, conv2.bias.grad, atol=1e-6)
+        assert torch.allclose(conv1.bias.grad, conv2.bias.grad, atol=1e-3)

test/nn/conv/cugraph/test_cugraph_rgcn_conv.py

@@ -43,19 +43,19 @@ def test_rgcn_conv_equality(aggr, bias, bipartite, max_num_neighbors,
 
     csc, edge_type = CuGraphRGCNConv.to_csc(edge_index, size, edge_type)
     out2 = conv2(x, csc, edge_type, max_num_neighbors=max_num_neighbors)
-    assert torch.allclose(out1, out2, atol=1e-4)
+    assert torch.allclose(out1, out2, atol=1e-3)
 
     grad_out = torch.rand_like(out1)
     out1.backward(grad_out)
     out2.backward(grad_out)
 
     end = -1 if root_weight else None
     assert torch.allclose(conv1.weight.grad, conv2.weight.grad[:end],
-                          atol=1e-4)
+                          atol=1e-3)
 
     if root_weight:
         assert torch.allclose(conv1.root.grad, conv2.weight.grad[-1],
-                              atol=1e-4)
+                              atol=1e-3)
 
     if num_bases is not None:
-        assert torch.allclose(conv1.comp.grad, conv2.comp.grad, atol=1e-4)
+        assert torch.allclose(conv1.comp.grad, conv2.comp.grad, atol=1e-3)

test/utils/test_convert.py

@@ -436,9 +436,9 @@ def test_to_cugraph(edge_weight, directed, relabel_nodes):
     cu_edge_index, cu_edge_weight = sort_edge_index(cu_edge_index,
                                                     cu_edge_weight)
 
-    assert torch.equal(edge_index, cu_edge_index)
+    assert torch.equal(edge_index, cu_edge_index.cpu())
     if edge_weight is not None:
-        assert torch.allclose(edge_weight, cu_edge_weight)
+        assert torch.allclose(edge_weight, cu_edge_weight.cpu())
 
 
 @withPackage('cudf')
@@ -476,8 +476,8 @@ def test_from_cugraph(edge_weight, directed, relabel_nodes):
     cu_edge_index, cu_edge_weight = sort_edge_index(cu_edge_index,
                                                     cu_edge_weight)
 
-    assert torch.equal(edge_index, cu_edge_index)
+    assert torch.equal(edge_index, cu_edge_index.cpu())
     if edge_weight is not None:
-        assert torch.allclose(edge_weight, cu_edge_weight)
+        assert torch.allclose(edge_weight, cu_edge_weight.cpu())
     else:
         assert cu_edge_weight is None