Tensorflow-metadata

Latest version: v1.15.0

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1.15.0

Major Features and Improvements

* N/A

Bug Fixes and Other Changes

* Bump the Ubuntu version on which TFMD is tested to 20.04 (previously
was 16.04).
* Bumped the minimum bazel version required to build `tfmd` to 6.1.0.
* Depends on `protobuf>=4.25.2,<5` for Python 3.11 and on
`protobuf>3.20.3,<4.21` for 3.9 and 3.10.
* Depends on `googleapis-common-protos>=1.56.4,<2` for Python 3.11 and on
`googleapis-common-protos>=1.52.0,<2` for 3.9 and 3.10.
* Relax dependency on `absl-py` to include version 2.

Breaking Changes

* Removed `NaturalLanguageDomain.location_constraint_regex`.
It was documented as "please do not use" and never implemented.

Deprecations

* Deprecated Python 3.8 support.

1.14.0

Major Features and Improvements

* N/A

Bug Fixes and Other Changes
* Add `joint_group` to `SequenceMetadata` to specify which group this sequence
feature belongs to so that they can be modeled jointly.
* Add `BOOL_TYPE_INVALID_CONFIG` anomaly type.
* Add `embedding_dim` to `FloatDomain` to specify the embedding dimension,
which is useful for use cases such as restoring shapes for flattened
sequence of embeddings.
* Add `sequence_truncation_limit` to `SequenceMetadata` to specify the maximum
sequence length that should be processed.
* Depends on `protobuf>=3.20.3,<4.21`. Upper bound is required to avoid
breaking changes.
* Add `embedding_type` to `FloatDomain` to specify the semantic type of the
embedding. This is useful for use cases where the embedding dimension is
inferred from the embedding type.

Breaking Changes

* N/A

Deprecations

* N/A

1.13.1

Major Features and Improvements

* N/A

Bug Fixes and Other Changes

* Depends on `protobuf>=3.20.3,<5`.

Breaking Changes

* N/A

Deprecations

* N/A

1.13.0

Major Features and Improvements

* Introduce `Schema.represent_variable_length_as_ragged` knob to automatically
generate `RaggedTensor`s for variable length features.
* Introduces a Schema option `HistogramSelection` to allow numeric drift/skew
calculations to use QUANTILES histograms, which are more robust to outliers.

Bug Fixes and Other Changes

* N/A

Breaking Changes

* N/A

Deprecations

* Deprecated Python 3.7 support.

1.12.0

Major Features and Improvements

* N/A

Bug Fixes and Other Changes

* N/A

Breaking Changes

* N/A

Deprecations

* N/A

1.11.0

Major Features and Improvements

* N/A

Bug Fixes and Other Changes

* Add a categorical indicator to the schema for `StringDomain`.
* Add ProblemStatement Task.is_auxiliary field to allow specifying auxiliary
tasks in multi-task learning problems.
* Add the SequenceMetadata field to the schema to specify if this feature
could be treated as a sequence feature.
* Add a `CUSTOM_VALIDATION` Type in anomalies.proto.

Breaking Changes

* Histogram Buckets include their upper bound instead of their lower bound.

Deprecations

* N/A

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