WeightedDirectedGraph doesn't support multiple edges from one node to another

[bezineb5]

Context I have a graph which contains the following "Sub" operation: => It subracts a value from itself (why is it like that? It's the conversion of Tensorflow's Maximum/Minimum in ONNX 7 which is translated like that in order to support broadcast - however I would expect the behaviour to be the same on a square X*X operation)

Problem When running the model, I get the following error: bad arity for operation (have 1, want 2)

Cause When looking at the implementation of WeightedDirectedGraph.SetWeightedEdge, it seems that it's not possible to have 2 identical edges from one node to another.

Solution It's not clear how to fix that without big changes. However, it means that it can happen in other cases and prevent correct execution of many ONNX models.

Any idea on a fix?

[owulveryck]

Hello, Many thanks for submitting this issue and for your investigation. I will have a closer look at the bug as soon as.possible. First step is to write a simple test to reproduce this. It will ease the analysis and the debugging process.

[bezineb5]

Hi, Thanks for this. I attached an example model and source code: example_mul.zip The graph just squares the input:

Expected output (with input = 2.0): 4.0 Actual output: bad arity for operation (have 1, want 2)

[owulveryck]

Thanks a lot. I've created a branch for tracking this issue.

I think the solution would be to play with the self edge (cf godoc).

I've dumped the content of your onnx file for info. I will work on it tomorrow evening CEST, but from what I see, the solution would be to add a self edge when two inputs are listed and equal.

The main problem is that we are losing the order of inputs as the self-edge must have a fixed weight within the current implementation.

pb.ModelProto{
        IrVersion: 5,
        OpsetImport: []*pb.OperatorSetIdProto{
                &pb.OperatorSetIdProto{
                        Domain:  "",
                        Version: 7,
                },
        },
        ProducerName:    "tf2onnx",
        ProducerVersion: "1.5.3",
        Domain:          "",
        ModelVersion:    0,
        DocString:       "",
        Graph: &pb.GraphProto{
                Node: []*pb.NodeProto{
                        &pb.NodeProto{
                                Input: []string{
                                        "x:0",
                                        "x:0",
                                },
                                Output: []string{
                                        "mul:0",
                                },
                                Name:      "mul",
                                OpType:    "Mul",
                                Domain:    "",
                                Attribute: nil,
                                DocString: "",
                        },
                },
                Name:        "tf2onnx",
                Initializer: nil,
                DocString:   "converted from ./model_nowind_test/export/",
                Input: []*pb.ValueInfoProto{
                        &pb.ValueInfoProto{
                                Name: "x:0",
                                Type: &pb.TypeProto{
                                        Value: &pb.TypeProto_TensorType{
                                                TensorType: &pb.TypeProto_Tensor{
                                                        ElemType: 1,
                                                        Shape: &pb.TensorShapeProto{
                                                                Dim: []*pb.TensorShapeProto_Dimension{
                                                                        &pb.TensorShapeProto_Dimension{
                                                                                Value: &pb.TensorShapeProto_Dimension_DimValue{
                                                                                        DimValue: 1,
                                                                                },
                                                                                Denotation: "",
                                                                        },
                                                                },
                                                        },
                                                },
                                        },
                                        Denotation: "",
                                },
                                DocString: "",
                        },
                },
                Output: []*pb.ValueInfoProto{
                        &pb.ValueInfoProto{
                                Name: "mul:0",
                                Type: &pb.TypeProto{
                                        Value: &pb.TypeProto_TensorType{
                                                TensorType: &pb.TypeProto_Tensor{
                                                        ElemType: 1,
                                                        Shape: &pb.TensorShapeProto{
                                                                Dim: []*pb.TensorShapeProto_Dimension{
                                                                        &pb.TensorShapeProto_Dimension{
                                                                                Value: &pb.TensorShapeProto_Dimension_DimValue{
                                                                                        DimValue: 1,
                                                                                },
                                                                                Denotation: "",
                                                                        },
                                                                },
                                                        },
                                                },
                                        },
                                        Denotation: "",
                                },
                                DocString: "",
                        },
                },
                ValueInfo: nil,
        },
        MetadataProps: nil,
}

[owulveryck]

The plan is:

• to write a (red) test in onnx-go based on the structure in the comment
• make the test pass by modifying the onnx decoder
• write a similar test in gorgonnx
• make the test pass.

[owulveryck]

some update about this issue. The branch has the tests which is already something. At first, I thought it would be easy to implement the self-link, at least in the main graph (in the Model structure). The problem is that the simple graph implementation we use as a receiver for gorgonnx does not handle self links.

https://github.com/owulveryck/onnx-go/blob/7c482d53bd0be130658c8ba3bbe3891d83087c21/backend/x/gorgonnx/graph.go#L17-L18

From the godoc of gonum:

SetWeightedEdge adds a weighted edge from one node to another. If the nodes do not exist, they are added and are set to the nodes of the edge otherwise. It will panic if the IDs of the e.From and e.To are equal.

Therefore using a self-link is more difficult than expected. (On top of that, walking the graph in gorgonnx would not be trivial.)

Therefore, it may be safer to think about another implementation to solve this issue. By now, I am out-of-idea, but I am sure a solution exists. We just need to figure it out.