* Depends on `apache-beam[gcp]>=2.29,<3`. * Depends on `tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,<3`. * Depends on `tensorflowjs>=3.6.0,<4`. * Depends on `tensorflow-metadata>=1.0.0,<1.1.0`. * Depends on `tfx-bsl>=1.0.0,<1.1.0`.
Breaking Changes
* N/A
Deprecations
* N/A
0.30.0
Major Features and Improvements
* N/A
Bug fixes and other Changes
* Fix bug that `FeaturesExtractor` incorrectly handles RecordBatches that have only the raw input column but no other feature columns.
* Fix an issue that micro_average can get lost in MetricKey, which can cause threshold mismatch the metrics during validation.
Breaking Changes
* N/A
Deprecations
* N/A
0.29.0
Major Features and Improvements
* Added support for output aggregation.
Bug fixes and other Changes
* In Fairness Indicators UI, sort metrics list to show common metrics first * For lift metrics, support negative values in the Fairness Indicator UI bar chart. * Make legacy predict extractor also input/output batched extracts. * Updated to use new compiled_metrics and compiled_loss APIs for keras in-graph metric computations. * Add support for calling model.evaluate on keras models containing custom metrics. * Add CrossSliceMetricComputation metric type. * Add Lift metrics under addons/fairness. * Don't add metric config from config.MetricsSpec to baseline model spec by default. * Fix invalid calculations for metrics derived from tf.keras.losses. * Fixes following bugs related to CrossSlicingSpec based evaluation results. * metrics_plots_and_validations_writer was failing while writing cross slice comparison results to metrics file. * Fairness widget view was not compatible with cross slicing key type. * Fix support for exporting the UI from a notebook to a standalone HTML page. * Depends on `absl-py>=0.9,<0.13`. * Depends on `tensorflow-metadata>=0.29.0,<0.30.0`. * Depends on `tfx-bsl>=0.29.0,<0.30.0`.
Breaking Changes
* N/A
Deprecations
* N/A
0.28.0
Major Features and Improvements
* Add a new base computation for binary confusion matrix (other than based on calibration histogram). It also provides a sample of examples for the confusion matrix. * Adding two new metrics - Flip Count and Flip Rate to evaluate Counterfactual Fairness.
Bug fixes and other Changes
* Fixed division by zero error for diff metrics. * Depends on `apache-beam[gcp]>=2.28,<3`. * Depends on `numpy>=1.16,<1.20`. * Depends on `tensorflow-metadata>=0.28.0,<0.29.0`. * Depends on `tfx-bsl>=0.28.0,<0.29.0`.
Breaking Changes
* N/A
Deprecations
* N/A
0.27.0
Major Features and Improvements
* Created tfma.StandardExtracts with helper methods for common keys. * Updated StandardMetricInputs to extend from the tfma.StandardExtracts. * Created set of StandardMetricInputsPreprocessors for filtering extracts. * Introduced a `padding_options` config to ModelSpec to configure whether and how to pad the prediction and label tensors expected by the model's metrics.
Bug fixes and other changes
* Fixed issue with metric computation deduplication logic. * Depends on `apache-beam[gcp]>=2.27,<3`. * Depends on `pyarrow>=1,<3`. * Depends on `tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,<3`. * Depends on `tensorflow-metadata>=0.27.0,<0.28.0`. * Depends on `tfx-bsl>=0.27.0,<0.28.0`.
Breaking changes
* N/A
Deprecations
* N/A
0.26.1
Major Features and Improvements
* N/A
Bug fixes and other Changes
* Fix support for exporting the UI from a notebook to a standalone HTML page. * Depends on apache-beam[gcp]>=2.25,!=2.26,<2.29. * Depends on numpy>=1.16,<1.20.