Comments (5)
owulveryck
commented on June 19, 2024
1
The plan is:
- to write a (red) test in
onnx-gobased 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.
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owulveryck
commented on June 19, 2024
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.
from onnx-go.
bezineb5
commented on June 19, 2024
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)
from onnx-go.
owulveryck
commented on June 19, 2024
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,
}from onnx-go.
owulveryck
commented on June 19, 2024
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.
onnx-go/backend/x/gorgonnx/graph.go
Lines 17 to 18 in 7c482d5
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.
from onnx-go.
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- Can't import onnx model, converted from BigGAN-PyTorch HOT 2
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- Updated depens
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