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RELEASE.md

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Current Version (not yet released; still in development)

Major Features and Improvements

Bug Fixes and Other Changes

Breaking Changes

Deprecations

Version 1.15.1

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Bumped the mininum bazel version required to build tfx_bsl to 6.1.0.
  • Bump the macOS version on which TFX-BSL is tested to Ventura (previously was Monterey).
  • Bumps the pybind11 version to 2.11.1
  • Depends on tensorflow 2.15
  • Depends on apache-beam[gcp]>=2.53.0,<3 for Python 3.11 and on apache-beam[gcp]>=2.47.0,<3 for 3.9 and 3.10.
  • Depends on protobuf>=4.25.2,<5 for Python 3.11 and on protobuf>3.20.3,<5 for 3.9 and 3.10.
  • Deprecated Windows support.

Breaking Changes

  • N/A

Deprecations

Version 1.15.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Bumped the mininum bazel version required to build tfx_bsl to 6.1.0.
  • Bump the macOS version on which TFX-BSL is tested to Ventura (previously was Monterey).
  • Bumps the pybind11 version to 2.11.1
  • Depends on tensorflow~=2.15
  • Depends on apache-beam[gcp]>=2.53.0,<3 for Python 3.11 and on apache-beam[gcp]>=2.47.0,<3 for 3.9 and 3.10.
  • Depends on protobuf>=4.25.2,<5 for Python 3.11 and on protobuf>3.20.3,<5 for 3.9 and 3.10.
  • Deprecated Windows support.

Breaking Changes

  • N/A

Deprecations

  • Deprecated python 3.8 support.

Version 1.14.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Bumped the Ubuntu version on which TFX-BSL is tested to 20.04 (previously 16.04).
  • Adds order_on_tie parameter to MisraGriesSketch to specify the order of items in case their counts are tied.
  • Use @platforms instead of @bazel_tools//platforms to specify constraints in OSS build.
  • Depends on pyarrow>=10,<11.
  • Depends on apache-beam>=2.47,<3.
  • Depends on numpy>=1.22.0.
  • Depends on tensorflow>=2.13,<3

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.13.0

Major Features and Improvements

  • RaggedTensors can now be automatically inferred for variable length features by setting represent_variable_length_as_ragged=true in TFMD schema.

Bug Fixes and Other Changes

  • Bumped the mininum bazel version required to build tfx_bsl to 5.3.0.
  • RecordBatchToExamplesEncoder now encodes arrays representing RaggedTensors in a way that is consistent with tf.io.parse_example. Note that this change is backwards compatible with ExamplesToRecordBatchDecoder and the decoding workflow as well.
  • Added utility functions for interacting with Arrow arrays and record batches.
  • Depends on numpy~=1.22.0.

Breaking Changes

  • N/A

Deprecations

  • Deprecated python 3.7 support.

Version 1.12.0

Major Features and Improvements

  • InferTensorRepresentationsFromSchema, TensorAdapter and TensorsToRecordBatchConverter now support SparseTensors with unknown dense_shape.

Bug Fixes and Other Changes

  • Depends on tensorflow>=2.11,<3

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.11.0

Major Features and Improvements

  • TensorAdapter now processes tf.RaggedTensors in TF 2 ~10x faster.

  • InferTensorRepresentationsFromSchema now infers RaggedTensors for STRUCT features.

  • TFSequenceExampleRecord now supports schemas with features not covered or partially covered by TensorRepresentations.

  • This is the last version that supports TensorFlow 1.15.x. TF 1.15.x support will be removed in the next version. Please check the TF2 migration guide to migrate to TF2.

Bug Fixes and Other Changes

  • Depends on tensorflow>=1.15.5,<2 or tensorflow>=2.10,<3
  • Depends on protobuf>=3.13,<4
  • Various TFXIO implementations now infer TensorRepresentations for provided schema Features even if some TensorRepresentations are provided as well.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.10.0

Major Features and Improvements

  • ExamplesToRecordBatchDecoder is now picklable.
  • ParquetTFXIO can now be used as RecordBasedTFXIO.
  • Introduces CreateTfSequenceExampleParserConfig that takes TFMD schema as input and produces configs for tf.SequenceExample parsing.
  • TFSequenceExampleRecord can now produce an equivalent tf.data.Dataset.
  • Introduces an api: CreateModelHandler that produces a model handler suitable for apache_beam.ml.inference.
  • Quantiles sketch supports GetQuantilesAndCumulativeWeights, which returns the sum of weights in each quantiles bin along with boundaries.

Bug Fixes and Other Changes

  • Depends on apache-beam[gcp]>=2.40,<3.
  • Depends on pyarrow>=6,<7.
  • Depends on tensorflow-metadata>=1.10,<1.11.
  • Depends on tensorflow>=1.15.5,<2 or tensorflow>=2.9,<3.

Breaking Changes

  • GenerateQuantiles removed from weighted_quantiles_summary.h and replaced with GenerateQuantilesAndCumulativeWeights.

Deprecations

  • N/A

Version 1.9.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Depends on tensorflow-metadata>=1.9,<1.10.
  • Depends on tensorflow>=1.15.5,<2 or tensorflow>=2.9,<3.
  • Depends on protobuf>=3.13,<3.21.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.8.0

Major Features and Improvements

  • Introduced RunInferencePerModel PTransform, which is a vectorized variant of RunInference (useful for ensembles).
  • Introduced ParquetTFXIO that allows reading data from Parquet files in pyarrow.RecordBatch format.
  • From this version we will be releasing python 3.9 wheels.
  • Depends on apache-beam[gcp]>=2.38,<3.

Bug Fixes and Other Changes

  • Depends on tensorflow-metadata>=1.8,<1.9.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.7.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Depends on apache-beam[gcp]>=2.36,<3.
  • Depends on tensorflow-metadata>=1.7,<1.8.
  • 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 tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.
  • Added a TFXIO where the user defines the beam source.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.6.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Fixes a bug when TensorsToRecordBatchConverter could not handle tf.RaggedTensors with uniform inner dimensions in TF 1.15.
  • Depends on apache-beam[gcp]>=2.35,<3.
  • Depends on tensorflow-metadata>=1.6,<1.7.
  • 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.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.5.0

Major Features and Improvements

  • TensorsToRecordBatchConverter can now handle tf.RaggedTensors with uniform inner dimensions.

Bug Fixes and Other Changes

  • 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 tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,<3.
  • Depends on tensorflow-metadata>=1.5,<1.6.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.4.0

Major Features and Improvements

  • Introduces RecordBatchToExamplesEncoder that supports encoding nested pyarrow.large_list()s representing tf.RaggedTensors.

Bug Fixes and Other Changes

  • Register s2t ops before loading decoder in record_to_tensor_tfxio if struct2tensor is installed.
  • Depends on pyarrow>=1,<6.
  • Depends on tensorflow-metadata>=1.4,<1.5.

Breaking Changes

  • N/A

Deprecations

  • Deprecated python 3.6 support.

Version 1.3.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • QuantilesSketch now ignores NaNs in input values and weights. Previously, NaNs would lead to incorrect quantiles calculation.
  • Fixes a bug when MisraGriesSketch would discard excessive number of elements during AddValues and Compress and output fewer elements than requested.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<3.
  • Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<3.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.2.0

Major Features and Improvements

  • Added support for converting tf.compat.v1.ragged.RaggedTensorValues to TensorsToRecordBatchConverter.
  • Depends on apache-beam[gcp]>=2.31,<3.
  • Depends on tensorflow-metadata>=1.2,<1.3.

Bug Fixes and Other Changes

  • N/A

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.1.1

Major Features and Improvements

  • N/A

Bug fixes and other Changes

  • Depends on google-cloud-bigquery>>=1.28.0,<2.21.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 1.1.0

Major Features and Improvements

  • Provided the SQL query ability for Apache Arrow RecordBatch. It's not available under Windows.

Bug Fixes and Other Changes

  • Depends on protobuf>=3.13,<4.
  • Upgraded the protobuf (com_google_protobuf) to 3.13.0.
  • Upgraded the bazel_skylib to 1.0.2 due to the upgrading of protobuf.
  • Depends on tensorflow-metadata>=1.1,<1.2.
  • More documentation is added for the SequenceExample decoder. It's available at tfx_bsl/coders/README.md.

Breaking Changes

  • The minimum required OS version for the macOS is 10.14 now.

Deprecations

  • N/A

Version 1.0.0

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • 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 tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,<3.
  • Depends on tensorflow-metadata>=1.0,<1.1.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 0.30.0

Major Features and Improvements

  • Misra-Gries sketch: added support for replacing large string blobs with a configurable placeholder, and replacing invalid utf-8 sequences with a configurable placeholder.

Bug Fixes and Other Changes

  • Depends on tensorflow-metadata>=0.30,<0.31.

Breaking Changes

  • Removed tfx_bsl.beam.shared. It is now available in Apache Beam. Use apache_beam.utils.shared instead.

Deprecations

  • N/A

Version 0.29.0

Major Features and Improvements

  • Add RawRecordTensorFlowDataset interface to record based tfxios.
  • TensorToArrowConverter now can handle generic SparseTensors (>=3-d).
  • Added RecordToTensorTFXIO.DecodeFunction() to get the decoder as a TF function.

Bug Fixes and Other Changes

  • Depends on absl-py>=0.9,<0.13.
  • Depends on tensorflow-metadata>=0.29,<0.30.
  • Bumped the mininum bazel version required to build tfx_bsl to 3.7.2.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 0.28.1

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Depends on apache-beam[gcp]>=2.28,<3.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 0.28.0

Major Features and Improvements

  • RunInference can now be applied on serialized tf.train.{Example, SequenceExample} for all methods as well as any other kind of serialized structure for the Predict method.
  • RunInference can now operate on PCollection[K, V] in a key-forwarding mode (whereby the key is left unchanged while inference is performed on the value).
  • RunInference is now more performant.

Bug Fixes and Other Changes

  • Depends on numpy>=1.16,<1.20.
  • Depends on tensorflow-metadata>=0.28,<0.29.

Breaking Changes

  • N/A

Deprecations

  • N/A

Version 0.27.1

  • This is a bug fix only version, which modified the dependencies.

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Fix in the tensorflow-serving-api version constraint.

Breaking changes

  • N/A

Deprecations

  • N/A

Version 0.27.0

Major Features and Improvements

  • tfx_bsl.public.tfxio.TFGraphRecordDecoder is now a public API.

Bug Fixes and Other Changes

  • 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,<0.28.
  • Depends on tensorflow-serving>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,<3.

Breaking changes

  • N/A

Deprecations

  • N/A

Version 0.26.1

  • This is a bug fix only version, which modified the dependencies.

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Depends on apache-beam[gcp]>=2.25,!=2.26.*,<3.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.4.*,<3.
  • Depends on tensorflow-serving>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.4.*,<3.

Breaking changes

  • N/A

Deprecations

  • N/A

Version 0.26.0

Major Features and Improvements

  • .TensorFlowDataset interface is available in RawTfRecord TFXIO.

Bug Fixes and Other Changes

  • Fix TFExampleRecord TFXIO's TensorFlowDataset output key's to match the tensor representation's tensor name (Previously this assumed the user provided a tensor name that is the same as the feature name).
  • Add utility in tensor_representation_util.py to get source columns from a tensor representation.
  • Depends on tensorflow-metadata>=0.26,<0.27.

Breaking changes

  • N/A

Deprecations

  • N/A

Version 0.25.0

Major Features and Improvements

  • Add RecordBatches interface to TFXIO. This interface returns an iterable of record batches, which can be used outside of Apache Beam or TensorFlow to access data.

  • From this release TFX-BSL will also be hosting nightly packages on https://pypi-nightly.tensorflow.org. To install the nightly package use the following command:

    pip install --extra-index-url https://pypi-nightly.tensorflow.org/simple tfx-bsl

    Note: These nightly packages are unstable and breakages are likely to happen. The fix could often take a week or more depending on the complexity involved for the wheels to be available on the PyPI cloud service. You can always use the stable version of TFX-BSL available on PyPI by running the command pip install tfx-bsl .

Bug Fixes and Other Changes

  • TensorToArrow returns LargeListArray/LargeBinaryArray in place of ListArray/BinaryArray.
  • array_util.IndexIn now supports LargeBinaryArray inputs.
  • Depends on apache-beam[gcp]>=2.25,<3.
  • Depends on tensorflow-metadata>=0.25,<0.26.

Breaking changes

  • Coders (Example, CSV) do not support outputting ListArray/BinaryArray any more. They can only output LargeListArray/LargeBinaryArray.

Deprecations

  • N/A

Version 0.24.1

Major Features and Improvements

  • N/A

Bug Fixes and Other Changes

  • Depends on apache-beam[gcp]>=2.24,<3.

Breaking changes

  • N/A

Deprecations

  • N/A

Version 0.24.0

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.

Version 0.23.0

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.

Version 0.22.1

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)

Release 0.22.0

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

Release 0.21.4

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.RecordBatches.
  • 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

Release 0.21.3

Major Features and Improvements

Bug Fixes and Other Changes

  • Requires apache-beam>=2.17,<2.18

Breaking Changes

Deprecations

Release 0.21.2

Major Features and Improvements

Bug Fixes and Other Changes

  • Fixed a bug in tfx_bsl.arrow.array_util.GetFlattenedArrayParentIndices that could cause memory corruption.

Breaking Changes

Deprecations

Release 0.21.1

Major Features and Improvements

  • Defined an abstract subclass of TFXIO, RecordBasedTFXIO to model record based file formats.

Bug Fixes and Other Changes

  • Utilities in tfx_bsl.arrow.array_util that:

    • previously takes ListArray now can also accept LargeListArray.
    • previously takes StringArray/BinaryArray now can also accept LargeStringArray and LargeBinaryArray.

    As a result: GetElementLengths now returns an Int64Array. GetFlattenedArrayParentIndices may return an Int64Array or an Int32Array depending on the input type.

Breaking Changes

Deprecations

Release 0.21.0

Major Features and Improvements

  • Introduced TFXIO, the interface for Standardized TFX Inputs

  • Added the first implementation of TFXIO, for tf.Example on TFRecords.

Bug Fixes and Other Changes

  • Added a test_util sub-package that contains a tool to discover and run all the absltests in a dir (like python's unittest discovery).
  • Requires apache-beam>=2.17,<3
  • Requires pyarrow>=0.15,<0.16
  • Requires tensorflow>=1.15,<3
  • Requires tensorflow-metadata>=0.21,<0.22.

Breaking Changes

Deprecations

Release 0.15.3

Major Features and Improvements

  • Requires apache-beam>=2.16,<2.17 as 2.17 requires a pyarrow version that we don't support yet.

Bug Fixes and Other Changes

Breaking Changes

  • Behavior of csv_decoder.ColumnTypeInferrer was changed. A new column type, ColumnType.UNKNOWN was added to denote that the inferrer could not determine the type of that column (instead of making a guess of FLOAT). Summary of behavior change (values in the examples are from the same column):

    • <int>, <empty>: before: FLOAT; after: INT
    • <empty>, ... , <empty>: before: FLOAT; after: UNKNOWN

Deprecations

Release 0.15.2

Major Features and Improvements

  • Added a (beam) utility to infer column types from a PCollection[CSVLine].
  • Added a utility to parse a CSVLine into cells (conforming to RFC4180).

Bug Fixes and Other Changes

Breaking Changes

Deprecations

Release 0.15.1

Major Features and Improvements

  • Added dependency on tensorflow>=1.15,<2.2. Starting from 1.15, package tensorflow comes with GPU support. Users won't need to choose between tensorflow and tensorflow-gpu.
    • Caveat: tensorflow 2.0.0 is an exception and does not have GPU support. If tensorflow-gpu 2.0.0 is installed before installing tfx-bsl, it will be replaced with tensorflow 2.0.0. Re-install tensorflow-gpu 2.0.0 if needed.
  • Added dependency on tensorflow-serving-api>=1.15,<3.
  • Added a python PTransform, tfx_bsl.beam.RunInference that enables batch inference.

Bug Fixes and Other Changes

Breaking Changes

Deprecations

Release 0.15.0

Major Features and Improvements

  • Added a tf.Example <-> Arrow coder.
  • Added a tf.Example -> Dict[str, np.ndarray] coder (this is a legacy format used by some TFX components).
  • Added some common Arrow utilities (tfx_bsl.arrow.array_util).
  • Added a python class, tfx_bsl.beam.Shared that helps sharing a single instance of object across multiple threads.
  • Added dependency on apache-beam[gcp]>=2.16,<3.
  • Added dependency on tensorflow-metadata>=0.15,<0.16.

Bug Fixes and Other Changes

Breaking Changes

Deprecations