Tensorflow-model-analysis

Major Features and Improvements

* Add COCO object detection metrics, object detection related utilities,
objection detection options in binary confusion matrix, Precision At Recall,
and AUC. Add MaxRecall metric.
* Add support for parsing sparse tensors with explicit tensor representations
via TFXIO.

Bug fixes and other Changes

* Add score_distribution_plot.
* Separate the Predictions Extractor into two extractors.
* Update PredictionsExtractor to support backwards compatibility with the
Materialized Predictions Extractor.
* Depends on `apache-beam[gcp]>=2.40,<3`.
* Depends on `pyarrow>=6,<7`.
* Update merge_extracts with an option to skip squeezing one-dim arrays.
Update split_extracts with an option to expand zero-dim arrays.
* Added experimental bulk inference implementation to PredictionsExtractor.
Currently only supports the RegressionAPI.

Breaking Changes

* Adds multi-index columns for view.experimental.metrics_as_dataframe util.
* Changes SymmetricPredictionDifference output type from array to scalar.

Deprecations

* N/A

Major Features and Improvements

* Add object detection related utilities.

Bug fixes and other Changes

* Depends on `tensorflow>=1.15.5,<2` or `tensorflow>=2.9,<3`
* Fix issue where labels with -1 values are one-hot encoded when they
shouldn't be Breaking Changes
* Depends on `tfx-bsl>=1.9.0,<1.10.0`.
* Depends on `tensorflow-metadata>=1.9.0,<1.10.0`.

Breaking Changes

* N/A

Deprecations

* N/A

Major Features and Improvements

* `SqlSliceKeyExtractor` now supports slicing on transformed features.

Bug fixes and other Changes

* Depends on `tfx-bsl>=1.8.0,<1.9.0`.
* Depends on `tensorflow-metadata>=1.8.0,<1.9.0`.
* Depends on `apache-beam[gcp]>=2.38,<3`.
* Fix the incorrect keras.metrics.serialization for AUCPrecisionRecall.

Breaking Changes

* N/A

Deprecations

* N/A

Major Features and Improvements

* Creates a VarLenTensorValue for storing batched, variable length extracts.
* Adds a load_metrics_as_dataframe util to load metrics file as dataframe.

Bug fixes and other Changes

* Fixes issue attempting to parse metrics, plots, and attributions without a
format suffix.

* Fixes the non-deterministic key ordering caused by proto string
serialization in metrics validator.

* Update variable name to respectful terminology, rebuild JS

* Fixes issues preventing standard preprocessors from being applied.

* Allow merging extracts including sparse tensors with different dense shapes.

* Allow counterfactual metrics to be calculated from predictions instead of
only features.

Breaking Changes

* MetricsPlotsAndValidationsWriter will now write files with an explicit
output format suffix (".tfrecord" by default). This should only affect
pipelines which directly construct `MetricsPlotsAndValidationWriter`
instances and do not set `output_file_format`. Those which use
`default_writers()` should be unchanged.
* Batched based extractors previously worked off of either lists of dicts of
single tensor values or arrow record batches. These have been updated to be
based on dicts with batched tensor values at the leaves.
* Depends on
`tensorflow>=1.15.5,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3`.
* Depends on `tfx-bsl>=1.7.0,<1.8.0`.
* Depends on `tensorflow-metadata>=1.7.0,<1.8.0`.
* Depends on `apache-beam[gcp]>=2.36,<3`.

Deprecations

* N/A

Major Features and Improvements

* N/A

Bug fixes and other Changes

* Fix Fairness Indicators UI bug with overlapping charts when comparing
EvalResults
* Fixed issue with aggregation type not being set properly in keys associated
with confusion matrix metrics.
* Enabled the sql_slice_key extractor when evaluating a model.
* Depends on `numpy>=1.16,<2`.
* Depends on `absl-py>=0.9,<2.0.0`.
* Depends on
`tensorflow>=1.15.5,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,<3`.
* Depends on `tfx-bsl>=1.6.0,<1.7.0`.
* Depends on `tensorflow-metadata>=1.6.0,<1.7.0`.
* Depends on `apache-beam[gcp]>=2.35,<3`.

Breaking Changes

* N/A

Deprecations

* N/A

Major Features and Improvements

* Replaced keras metrics with TFMA implementations. To use a keras metric in a
`tfma.MetricConfig` you must now specify a module (i.e. `tf.keras.metrics`).
* Added FixedSizeSample metric which can be used to extract a random,
per-slice, fixed-sized sample of values for a user-configured feature key.

Bug fixes and other Changes

* Updated QueryStatistics to support weighted examples.
* Replace confusion matrix based metrics with numpy counterparts, shifting
away from Keras metrics class.
* Depends on `apache-beam[gcp]>=2.34,<3`.
* Depends on
`tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,<3`.
* Depends on `tfx-bsl>=1.5.0,<1.6.0`.
* Depends on `tensorflow-metadata>=1.5.0,<1.6.0`.

Breaking Changes

* Removes register_metric from public API, as it is not intended to be public
facing. To use a custom metric, provide the module name in which the metric
is defined in the MetricConfig message, instead.

Deprecations