ONNX models used in practice often violate some of the contraints specified by the ONNX standard. Examples include the following:

• The standard specifies that identifiers must be valid C identifiers, but use of numbers such as "23" as tensor-names is common.
• ONNX has a more complex shape-specification that uses symbolic identifiers to denote unknown dimensions, but occasionally models use a number such as -1 to indicate an unknown dimension (common in some other frameworks).

A sanitizer tool that fixes such violations (where a simple fix exists) would be useful. It would take in an input ONNX model and produce a sanitized ONNX model as output with such obvious violations repaired.