github tensorflow/tfx v1.0.0-rc1
TFX 1.0.0-rc1

latest releases: v1.15.1, v1.15.0, v1.15.0-rc0...
pre-release3 years ago

Major Features and Improvements

  • Added tfx.v1 Public APIs, please refer to
    API doc for details.
  • Transform component now computes pre-transform and post-transform statistics
    and stores them in new, indvidual outputs ('pre_transform_schema',
    'pre_transform_stats', 'post_transform_schema', 'post_transform_stats',
    'post_transform_anomalies'). This can be disabled by setting
    disable_statistics=True in the Transform component.
  • BERT cola and mrpc examples now demonstrate how to calculate statistics for
    NLP features.

Breaking Changes

For Pipeline Authors

  • N/A

For Component Authors

  • Apache Beam support is migrated from TFX Base Components and Executors to
    dedicated Beam Components and Executors. BaseExecutor will no longer embed
    beam_pipeline_args. Custom executors for Beam powered components should
    now extend BaseBeamExecutor instead of BaseExecutor.

Deprecations

  • N/A

Bug Fixes and Other Changes

  • TFX CLI now supports
    Vertex Pipelines.
    use it with --engine=vertex flag.
  • Forces keyword arguments for AirflowComponent to make it compatible with
    Apache Airflow 2.1.0 and later.
  • Removed six dependency.
  • Depends on apache-beam[gcp]>=2.29,<3.
  • Depends on ml-metadata>=1.0.0,<1.1.0.
  • Depends on struct2tensor>=0.31.0,<0.32.0.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,<3.
  • Depends on tensorflow-data-validation>=1.0.0,<1.1.0.
  • Depends on tensorflowjs>=3.6.0,<4.
  • Depends on tensorflow-model-analysis>=0.31.0,<0.32.0.
  • Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,<3.
  • Depends on tensorflow-transform>=1.0.0,<1.1.0.
  • Depends on tfx-bsl>=1.0.0,<1.1.0.

Documentation Updates

  • Update the Guide of TFX to adopt 1.0 API.
  • TFT and TFDV component documentation now describes how to
    configure pre-transform and post-transform statistics, which can be used for
    validating text features.

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