Not all models can be converted for the desired RVC Platform. We outline here some common issues that might arise during the conversion process.
Common Issues
Incorrect Conversion Parameters
Typically, mismatches occur in input/output tensor shapes, names, or types.SOLUTION: Thoroughly check your model and the meaning of all conversion parameters and adjust them accordingly. You can help yourself with the Netron tool to study the characteristics of an ONNX model.
Incompatible Model Formats
The source model format might not be supported by the conversion platform or the target format might not be compatible with certain features of the model.SOLUTION: It is advised to first convert the source model to ONNX format as it opens up the most options at conversion for the appropriate RVC Platform.
Unsupported Operations
The source model might contain operations that the conversion tool or the target model format do not support.SOLUTION: Consult the supported operations for the target platform you aim to run the conversion for. If the operation is not supported, consider replacing it with a supported alternative. If no alternative is available, consider breaking down the model into simpler components that can be converted separately and offload the problematic parts to on-host processing. You can help yourself with the onnx-modifier tool to introduce modifications to an ONNX model.
Model Architecture Issues
Complex or non-standard model architectures might cause conversion issues.SOLUTION: Simplify the model architecture if possible. Consider using the onnx.checker tool to identify potential issues in an ONNX model.