Major Features and Improvements
* Add F1, False positive rate, and Accuracy into the confusion matrix plot.
* Add support for setting top_k and class_id at the same time for confusion
matrix metrics.
* Add the false positive for semantic segmentation metrics.
* Add Mean Metric (experimental) which calculates the mean of any feature. *.
Adds support of `output_keypath` to ModelSignatureDoFn to explicitly set a
chain of output keys in the multi-level dict (extracts). Adds output_keypath
to common prediction extractors.
Bug fixes and other Changes
* Fix the bug that SetMatchRecall is always 1 when top_k is set.
* Depends on `pyarrow>=10,<11`.
* Depends on `apache-beam>=2.47,<3`.
* Depends on `numpy>=1.23.0`.
* Depends on `tensorflow>=2.13.0,<3`.
* Add 'tfma_eval' model_type in model_specs as the identifier for
eval_saved_model, allowing signature='eval' to now be used with other model
types.
* Add "materialized_prediction" model type to allow users bypassing model
inference explicitly.
Breaking Changes
* Depend on PIL for image related metrics.
* Separate extract_key from signature names in `ModelSignaturesDoFn`.
Deprecations
* N/A