Check ONNX output equality (#5997)

CHANGELOG.md

@@ -19,7 +19,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `SparseTensor` support to `SuperGATConv` ([#5888](https://github.com/pyg-team/pytorch_geometric/pull/5888))
 - Added TorchScript support for `AttentiveFP `([#5868](https://github.com/pyg-team/pytorch_geometric/pull/5868))
 - Added `num_steps` argument to training and inference benchmarks ([#5898](https://github.com/pyg-team/pytorch_geometric/pull/5898))
-- Added `torch.onnx.export` support ([#5877](https://github.com/pyg-team/pytorch_geometric/pull/5877))
+- Added `torch.onnx.export` support ([#5877](https://github.com/pyg-team/pytorch_geometric/pull/5877), [#5997](https://github.com/pyg-team/pytorch_geometric/pull/5997))
 - Enable VTune ITT in inference and training benchmarks ([#5830](https://github.com/pyg-team/pytorch_geometric/pull/5830), [#5878](https://github.com/pyg-team/pytorch_geometric/pull/5878))
 - Add training benchmark ([#5774](https://github.com/pyg-team/pytorch_geometric/pull/5774))
 - Added a "Link Prediction on MovieLens" Colab notebook ([#5823](https://github.com/pyg-team/pytorch_geometric/pull/5823))

test/nn/models/test_basic_gnn.py

@@ -184,10 +184,12 @@ def forward(self, x, edge_index):
 
     model = MyModel()
     x = torch.randn(3, 8)
-    edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
+    edge_index = torch.tensor([[0, 1, 2], [1, 0, 2]])
+    expected = model(x, edge_index)
+    assert expected.size() == (3, 16)
 
     torch.onnx.export(model, (x, edge_index), 'model.onnx',
-                      input_names=('x', 'edge_index'))
+                      input_names=('x', 'edge_index'), opset_version=16)
 
     model = onnx.load('model.onnx')
     onnx.checker.check_model(model)
@@ -198,6 +200,7 @@ def forward(self, x, edge_index):
         'x': x.numpy(),
         'edge_index': edge_index.numpy()
     })[0]
-    assert out.shape == (3, 16)
+    out = torch.from_numpy(out)
+    assert torch.allclose(out, expected, atol=1e-6)
 
     os.remove('model.onnx')