Version 0.23.0

Major Features and Improvements

Added TFX DSL IR compiler that encodes a TFX pipeline into a DSL proto.
Supported feature based split partition in ExampleGen.
Added the ConcatPlaceholder to tfx.dsl.component.experimental.placeholders.
Changed Span information as a property of ExampleGen's output artifact. Deprecated ExampleGen input (external) artifact.
Added ModelRun artifact for Trainer for storing training related files, e.g., Tensorboard logs. Trainer's Model artifact now only contain pure models (check tfx/utils/path_utils.py for details).
Added support for tf.train.SequenceExample in ExampleGen:
- ImportExampleGen now supports tf.train.SequenceExample importing.
- base_example_gen_executor now supports tf.train.SequenceExample as output payload format, which can be utilized by custom ExampleGen.
Added Tuner component and its integration with Google Cloud Platform as the execution and hyperparemeter optimization backend.
Switched Transform component to use the new TFXIO code path. Users may potentially notice large performance improvement.
Added support for primitive artifacts to InputValuePlaceholder.
Supported multiple artifacts for Trainer and Tuner's input example Channel.
Supported split configuration for Trainer and Tuner.
Supported split configuration for Evaluator.
Supported split configuration for StatisticsGen, SchemaGen and ExampleValidator. SchemaGen will now use all splits to generate schema instead of just using train split. ExampleValidator will now validate all splits against given schema instead of just validating eval split.
Component authors now can create a TFXIO instance to get access to the data through tfx.components.util.tfxio_utils. As TFX is going to support more data payload formats and data container formats, using tfxio_utils is encouraged to avoid dealing directly with each combination. TFXIO is the interface of Standardized TFX Inputs.
Added experimental BaseStubExecutor and StubComponentLauncher to test TFX pipelines.
Added experimental TFX Pipeline Recorder to record output artifacts of the pipeline.
Supported multiple artifacts in an output Channel to match a certain input Channel's artifact count. This enables Transform component to process multiple artifacts.
Transform component's transformed examples output is now optional (enabled by default). This can be disabled by specifying parameter materialize=False when constructing the component.
Supported Version spec in input config for file based ExampleGen.
Added custom config to Transform component and made it available to pre-processing fn.
Supported custom extractors in Evaluator.
Deprecated tensorflow dependency from MLMD python client.
Supported Date spec in input config for file based ExampleGen.

Bug fixes and other changes

Added Tuner component to Iris e2e example.
Relaxed the rule that output artifact uris must be newly created. This is a temporary workaround to make retry work. We will introduce a more comprehensive solution for idempotent execution.
Made evaluator output optional (while still recommended) for pusher.
Moved BigQueryExampleGen to tfx.extensions.google_cloud_big_query.
Moved BigQuery ML Pusher to tfx.extensions.google_cloud_big_query.pusher.
Removed Tuner from custom_components/ as it's supported under components/ now.
Added support of non tf.train.Example protos as internal data payload format by ImportExampleGen.
Used thread local storage for label_utils.scoped_labels() to make it thread safe.
Requires Bazel to build TFX source code.
Upgraded python version in TFX docker images to 3.7. Older version of python (2.7/3.5/3.6) is not available anymore in tensorflow/tfx images on docker hub. Virtualenv is not used anymore.
Stopped requiring avro-python3.
Depends on absl-py>=0.7,<0.9.
Depends on apache-beam[gcp]>=2.23,<3.
Depends on pyarrow>=0.17,<0.18.
Depends on attrs>=19.3.0,<20.
Depends on ml-metadata>=0.23,<0.24.
Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,<3.
- Note: Dependency like tensorflow-transform might impose a narrower range of tensorflow.
Depends on tensorflow-data-validation>=0.23,<0.24.
Depends on tensorflow-model-analysis>=0.23,<0.24.
Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,<3.
Depends on tensorflow-transform>=0.23,<0.24.
Depends on tfx-bsl>=0.23,<0.24.

Breaking changes

Changed the URIs of the value artifacts to point to files.

For pipeline authors

Moved BigQueryExampleGen to tfx.extensions.google_cloud_big_query. The previous module path from tfx.components is not available anymore. This is a breaking change.
Moved BigQuery ML Pusher to tfx.extensions.google_cloud_big_query.pusher. The previous module path from tfx.extensions.google_cloud_big_query_ml is not available anymore.
Updated beam pipeline args, users now need to set both direct_running_mode and direct_num_workers explicitly for multi-processing.
Added required 'output_data_format' execution property to FileBaseExampleGen.
Changed ExampleGen to take a string as input source directly instead of a Channel of external artifact:
- Previously deprecated input_base Channel is changed to string type instead of Channel. This is a breaking change, users should pass string directly to input_base.
Fully removed csv_input and tfrecord_input in dsl_utils. This is a breaking change, users should pass string directly to input_base.

For component authors

Changed GetInputSourceToExamplePTransform interface by removing input_dict. This is a breaking change, custom ExampleGens need to follow the interface change.
Changed ExampleGen to take a string as input source directly instead of a Channel of external artifact:
- input Channel is deprecated. The use of input is valid but should change to string type input_base ASAP.

Documentation updates

N/A

Deprecations

ExternalArtifact and external_input function are deprecated. The use of external_input with ExampleGen input is still valid but should change to use input_base ASAP.
Note: We plan to remove Python 3.5 support after this release.

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