Shirley4042 opened a new issue, #20049: URL: https://github.com/apache/tvm/issues/20049
## Expected behavior I am trying to import NVIDIA BEVFusion ONNX models into TVM. [testcase.zip](https://github.com/user-attachments/files/30374145/testcase.zip) The ONNX models contain two custom sparse operators: - SparseConvolution - ScatterDense I expect the TVM ONNX frontend to either: 1. Directly import these operators into corresponding Relax operators, or 2. Provide a recommended extension mechanism for lowering these operators into TVM-compatible representations. ## Actual behavior Importing the ONNX models fails because the TVM ONNX frontend does not recognize these operators. Error: OpNotImplemented: The following operators are not supported for frontend ONNX: SparseConvolution, ScatterDense ## Environment - TVM: TVM v0.25.dev0 - OS: Ubuntu 22.04 - Python: 3.11 ## Model information Example: testcase [testcase.zip](https://github.com/user-attachments/files/30374155/testcase.zip) .onnx Graph structure: Input | SparseConvolution x21 | Add | Relu | ScatterDense | Output The operators are custom ONNX operators generated by NVIDIA sparse convolution implementation. ## Questions 1. Should SparseConvolution and ScatterDense be added as new Relax operators? 2. Does TVM have an existing recommended extension mechanism for importing non-standard ONNX sparse operators? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
