Tfx-bsl

Major Features and Improvements

* You can now build `tfx_bsl` wheel with `python setup.py bdist_wheel`. Note:
* If you want to build a manylinux2010 wheel you'll still need to use
Docker.
* Bazel is still required.
* You can now build manylinux2010 `tfx_bsl` wheel for Python 3.8.
* From this version we will be releasing python 3.8 wheels.

Bug Fixes and Other Changes

* Stopped depending on `six`.
* Depends on `absl-py>=0.9,<0.11`.
* Depends on `pandas>=1.0,<2`.
* Depends on `protobuf>=3.9.2,<4`.
* Depends on `tensorflow-metadata>=0.24,<0.25`.

Breaking changes

* N/A

Deprecations

* Deprecated py3.5 support.

Major Features and Improvements
* Several TFXIO symbols are made public, which means:
* TFX users (both pipeline and component authors), and TFX libraries
(TFDV, TFMA, TFT) users may start using these symbols.
* We will be subject to semantic versioning once tfx_bsl goes beyond 1.0.
* TFRecord based TFXIO implementations now support reading from multiple file
patterns.
* Implemented the TensorFlowDataset() interface for TFExampleRecord TFXIO.
* Starting from this version, `tfx_bsl` has no binary dependency on `pyarrow`
(`libarrow.so`). As a result:
- Package `tfx_bsl` will be able to work with a wider range of pyarrow
versions. We will relax the version requirements in setup.py in the next
release.
- Custom built `tfx_bsl` does not have to maintain ABI compatiblity with
a specific `pyarrow` installation. Custom builds don't need to be
manylinux-conformant.

Bug Fixes and Other Changes

* Starting from this version, the windows wheel will be built with VS 2015.
* `run_all_tests` will fail with exit code -2 if no tests are discovered.
* Stopped requiring `avro-python3`.
* Example coders will ignore duplicate feature names in the TFMD schema (only
the first one counts). It is a temporary measure until TFDV can check and
prevent duplications. DO NOT rely on this behavior.
* CsvTFXIO now allows skipping CSV headers (`set skip_header_lines`).
* CsvTFXIO now requires `telemetry_descriptors` to construct.
* Depends on `apache-beam[gcp]>=2.23,<3`.
* Depends on `pyarrow>=0.17,<0.18`.
* Depends on `tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,<3`.
* Depends on `tensorflow-metadata>=0.23,<0.24`.
* Depends on `tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,<3`.

Breaking changes

* N/A

Deprecations

* Dropped Python 2.x support.
* Note: We plan to remove Python 3.5 support after this release.

Major Features and Improvements

* Added SequenceExamplesToRecordBatchDecoder.
* Added a TFXIO implementation for SequenceExmaples on TFRecord.
* Added support for TensorAdapter to output tf.RaggedTensors.
* Improved performance of tf.Example and tf.SequenceExample coders.

Bug Fixes and Other Changes

* Depends on `pandas>=0.24,<2`.
* Depends on `tensorflow>=1.15,!=2.0.*,<3`.
* Depends on `tensorflow-metadata>=0.22.2,<0.23`.
* Removed tensor_to_arrow_test for TF 1.x as it does not support TF 1.x.

Breaking changes

Deprecations
* Removed `arrow.table_util.SliceTableByRowIndices` (in favor of
`RecordBatchTake`)
* Removed `arrow.table_util.MergeTables` (in favor of `MergeRecordBatches`)

Major Features and Improvements

* Moved RunInference API and related protos to tfx_bsl/public directory.
* CSV coder support for multivalent columns.
* tf.Exmaple coder support for producing large types (LargeList, LargeBinary).
* Added TFXIO for CSV

Bug Fixes and Other Changes

* Depends on `apache-beam[gcp]>=2.20,<3`.
* Depends on `pyarrow>=0.16,<0.17`
* Depends on `tensorflow-metadata>=0.22,<0.23`

Breaking Changes

* Renamed ModelEndpointSpec to AIPlatformPredictionModelSpec to specify remote
model endpoint on Google Cloud Platform.
* Renamed InferenceEndpoint to InferenceSpecType.

Deprecations

Major Features and Improvements

* Added a tfxio.telemetry.ProfileRecordBatches, a PTransform to collect
telemetry from Arrow RecordBatches.
* Added remote model inference on Google Cloud Platform.

Bug Fixes and Other Changes

* Added `arrow.table_util.MergeRecordBatches`: similar to `MergeTables` but
operates against `pa.RecordBatch`es.
* Added `arrow.table_util.RecordBatchTake`: similar to
`SliceTableByRowIndices` but operates against a `pa.RecordBatch`.
* Requires `apache-beam>=2.17,<3`
* Only requires `avro-python3>=1.8.1,!=1.9.2.*,<2.0.0` on Python 3.5 + MacOS
* Requires `google-api-python-client>=1.7.11,<2`

Breaking Changes

Deprecations

Major Features and Improvements

Bug Fixes and Other Changes

* Requires `apache-beam>=2.17,<2.18`

Breaking Changes

Deprecations