Implements a modular and easily extensible evaluation framework for both TFLite and TFjs. The evaluation framework has the following features:
* It is easy to add new Modules of examples since each Module is specified using a few lines of code (see `examples.py`).
* It is easy to add new converters since each converter is represented as a function (see `converters.py`). For instance, we could add the MLIR-based converter that the TFLite team is currently working on.
* The framework outputs a Markdown table (see `README.md`).
The framework has the following limitations:
* We only evaluate whether a Module converts, we do not compare any outputs between the converted model and the original model. This will require more effort, and it seems like we can do this as a follow-up if necessary (once a good fraction of ops are converted).
* If an example is missing multiple ops, then only the first missing op is reported. We could improve this by implementing mocked versions of non-working ops, which only output the right shapes. We could also consider doing this as a follow-up.
PiperOrigin-RevId: 399373571