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# FXE0016:find-operator-overloads-in-onnx-registry

The operator overload name serves the purpose of verifying whether a PyTorch operator is registered in the ONNX registry. If it’s not found, the dispatcher takes a fallback approach and tries to locate the default overload of the PyTorch operator in the registry. If even the default overload is absent, it signifies that the operator is officially unsupported.

There are three types of level that can be triggered in this rule:

1. NOTE: The op overload is supported.

2. WARNING: The op overload is not supported, but it’s default overload is supported.

3. ERROR: The op overload is not supported, and it’s default overload is also not supported.

Here are some suggestions based on the WARNING situation:

1. If there are NO errors or mismatches in the results, it is safe to disregard this warning.

2. If there are errors or mismatches in the results, it is recommended to: (a) Enable op_level_debugging to determine if the OnnxFunction might be incorrect. (b) Report the unsupported overload to the PyTorch-ONNX team. (c) Create/register a custom symbolic function to replace the default one.

Here are some suggestions based on the ERROR situation:

1. Report the unsupported operator to the PyTorch-ONNX team.

2. Create/register a custom symbolic function to replace the default one.

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