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Releases: tensorflow/tfx

TFX 1.5.0

14 Dec 19:05
cd546f7
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Major Features and Improvements

  • Added support for partial pipeline run. Users can now run a subset of nodes
    in a pipeline while reusing artifacts generated in previous pipeline runs.
    This is supported in LocalDagRunner and BeamDagRunner, and is exposed via
    the TfxRunner API.

Breaking Changes

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Increased docker timeout to 5 minutes for image building in CLI.
  • Fixed KeyError when multiple Examples artifacts were used in Transform
    without materialization.
  • Fixed error where Vertex Endpoints of the same name is not deduped
  • 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.*,<2.8.
  • Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,<3.
  • Depends on ml-metadata>=1.5.0,<1.6.0.
  • Depends on struct2tensor>=0.36.0,<0.37.0.
  • Depends on tensorflow-data-validation>=1.5.0,<1.6.0.
  • Depends on tensorflow-model-analysis>=0.36.0,<0.37.0.
  • Depends on tensorflow-transform>=1.5.0,<1.6.0.
  • Depends on tfx-bsl>=1.5.0,<1.6.0.

Documentation Updates

  • N/A

TFX 1.3.4

07 Dec 02:05
7fa8695
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Major Features and Improvements

  • N/A

Breaking Changes

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Fixed error where Vertex Endpoints of the same name is not deduped

Documentation Updates

  • N/A

TFX 1.5.0-rc0

06 Dec 21:19
0a85fad
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TFX 1.5.0-rc0 Pre-release
Pre-release

Major Features and Improvements

  • Added support for partial pipeline run. Users can now run a subset of nodes
    in a pipeline while reusing artifacts generated in previous pipeline runs.
    This is supported in LocalDagRunner and BeamDagRunner, and is exposed via
    the TfxRunner API.

Breaking Changes

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Increased docker timeout to 5 minutes for image building in CLI.
  • Fixed KeyError when multiple Examples artifacts were used in Transform
    without materialization.
  • Fixed error where Vertex Endpoints of the same name is not deduped
  • 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.*,<2.8.
  • Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,<3.
  • Depends on ml-metadata>=1.5.0,<1.6.0.
  • Depends on struct2tensor>=0.36.0,<0.37.0.
  • Depends on tensorflow-data-validation>=1.5.0,<1.6.0.
  • Depends on tensorflow-model-analysis>=0.36.0,<0.37.0.
  • Depends on tensorflow-transform>=1.5.0,<1.6.0.
  • Depends on tfx-bsl>=1.5.0,<1.6.0.

Documentation Updates

  • N/A

TFX 1.4.0

17 Nov 02:01
5ebbbd8
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Major Features and Improvements

  • Supported endpoint overwrite for CAIP BulkInferrer.
  • Added support for outputting and encoding tf.RaggedTensors in TFX
    Transform component.
  • Added conditional for TFX running on KFPv2 (Vertex).
  • Supported component level beam pipeline args for Vertex (KFPV2DagRunner).
  • Support exit handler for TFX running on KFPv2 (Vertex).
  • Added RangeConfig for QueryBasedExampleGen to select date using query
    pattern.
  • Added support for union of Channels as input to standard TFX components.
    Users can use channel.union() to combine multiple Channels and use as input
    to these compnents. Artfacts resolved from these channels are expected to
    have the same type, and passed to components in no particular order.

Breaking Changes

  • Calling TfxRunner.run(pipeline) with the Pipeline IR proto will no longer
    be supported. Please switch to TfxRunner.run_with_ir(pipeline) instead.
    If you are calling TfxRunner.run(pipeline) with the Pipeline object, this
    change should not affect you.

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • Deprecated python3.6 support.

Bug Fixes and Other Changes

  • Depends on google-cloud-aiplatform>=1.5.0,<2.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<2.7.
  • Depends on pyarrow>=1,<6.
  • Fixed FileBasedExampleGen driver for Kubeflow v2 (Vertex). Driver can
    update exec_properties for its executor now, which enables {SPAN} feature.
  • example_gen.utils.dict_to_example now accepts Numpy types
  • Updated pytest to include v6.x
  • Depends on apache-beam[gcp]>=2.33,<3.
  • Depends on ml-metadata>=1.4.0,<1.5.0.
  • Depends on struct2tensor>=0.35.0,<0.36.0.
  • Depends on tensorflow-data-validation>=1.4.0,<1.5.0.
  • Depends on tensorflow-model-analysis>=0.35.0,<0.36.0.
  • Depends on tensorflow-transform>=1.4.0,<1.5.0.
  • Depends on tfx-bsl>=1.4.0,<1.5.0.
  • Fixed error where Vertex Endpoints of the same name is not deduped

Documentation Updates

  • N/A

TFX 1.4.0-rc0

10 Nov 07:15
17ef159
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TFX 1.4.0-rc0 Pre-release
Pre-release

Major Features and Improvements

  • Supported endpoint overwrite for CAIP BulkInferrer.
  • Added support for outputting and encoding tf.RaggedTensors in TFX
    Transform component.
  • Added conditional for TFX running on KFPv2 (Vertex).
  • Supported component level beam pipeline args for Vertex (KFPV2DagRunner).
  • Support exit handler for TFX running on KFPv2 (Vertex).
  • Added RangeConfig for QueryBasedExampleGen to select date using query
    pattern.
  • Added support for union of Channels as input to standard TFX components.
    Users can use channel.union() to combine multiple Channels and use as input
    to these compnents. Artfacts resolved from these channels are expected to
    have the same type, and passed to components in no particular order.

Breaking Changes

  • Calling TfxRunner.run(pipeline) with the Pipeline IR proto will no longer
    be supported. Please switch to TfxRunner.run_with_ir(pipeline) instead.
    If you are calling TfxRunner.run(pipeline) with the Pipeline object, this
    change should not affect you.

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • Deprecated python3.6 support.

Bug Fixes and Other Changes

  • Depends on google-cloud-aiplatform>=1.5.0,<2.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<2.7.
  • Depends on pyarrow>=1,<6.
  • Fixed FileBasedExampleGen driver for Kubeflow v2 (Vertex). Driver can
    update exec_properties for its executor now, which enables {SPAN} feature.
  • example_gen.utils.dict_to_example now accepts Numpy types
  • Updated pytest to include v6.x
  • Depends on apache-beam[gcp]>=2.33,<3.
  • Depends on ml-metadata>=1.4.0,<1.5.0.
  • Depends on struct2tensor>=0.35.0,<0.36.0.
  • Depends on tensorflow-data-validation>=1.4.0,<1.5.0.
  • Depends on tensorflow-model-analysis>=0.35.0,<0.36.0.
  • Depends on tensorflow-transform>=1.4.0,<1.5.0.
  • Depends on tfx-bsl>=1.4.0,<1.5.0.

Documentation Updates

  • N/A

TFX 1.3.3

08 Nov 22:03
b55ab2e
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Major Features and Improvements

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<2.7.

Documentation Updates

  • N/A

TFX 1.2.1

03 Nov 02:32
1657315
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Major Features and Improvements

  • N/A

Breaking Changes

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Added support for a custom metadata-ui-json filename in KubeflowDagRunner.
  • Fixed missing type information marker file 'py.typed'.

Documentation Updates

  • N/A

TFX 1.3.2

01 Nov 02:56
e7b1e7d
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Major Features and Improvements

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Fixed endless waiting for Vertex Trainer.

Documentation Updates

  • N/A

TFX 1.3.1

20 Oct 23:34
907cf0d
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Major Features and Improvements

  • N/A

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • N/A

Bug Fixes and Other Changes

  • Fixed Vertex Pusher by passing enable_vertex flag for deploying model.

Documentation Updates

  • N/A

TFX 1.3.0

06 Oct 16:50
b77c06e
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Major Features and Improvements

  • TFX CLI now supports runtime parameter on Kubeflow, Vertex, and Airflow.
    Use it with '--runtime_parameter=<parameter_name>=<parameter_value>' flag.
    In the case of multiple runtime parameters, format is as follows:
    '--runtime_parameter=<parameter_name>=<parameter_value> --runtime_parameter
    =<parameter_name>=<parameter_value>'
  • Added Manual node in the experimental orchestrator.
  • Placeholders support index access and JSON serialization for list type execution properties.
  • Added ImportSchemaGen which is a dedicated component to import a
    pre-defined schema file. ImportSchemaGen will replace Importer with
    simpler syntax and less constraints. You have to pass the file path to the
    schema file instead of the parent directory unlike Importer.

Breaking Changes

For Pipeline Authors

  • N/A

For Component Authors

  • N/A

Deprecations

  • The import name of KerasTuner has been changed from kerastuner
    to keras_tuner. The import name of kerastuner is still supported.
    A warning will occur when import from kerastuner, but does not affect
    the usage.

Bug Fixes and Other Changes

  • The default job name for Google Cloud AI Training jobs was changed from
    'tfx_YYYYmmddHHMMSS' to 'tfx_YYYYmmddHHMMSS_xxxxxxxx', where 'xxxxxxxx' is
    a random 8 digit hexadecimal string.
  • Fix component to raise error if its input required channel (specified from
    ComponentSpec) has no artifacts in it.
  • Fixed an issue where ClientOptions with regional endpoint was
    incorrectly left out in Vertex AI pusher.
  • CLI now hides passed flags from user python files in "--pipeline-path". This
    will prevent errors when user python file tries reading and parsing flags.
  • Fixed missing type information marker file 'py.typed'.
  • Depends on apache-beam[gcp]>=2.32,<3.
  • Depends on google-cloud-bigquery>=1.28.0,<3.
  • Depends on google-cloud-aiplatform>=0.5.0,<2.
  • Depends on jinja2>=2.7.3,<4, i.e. now supports Jinja 3.x.
  • Depends on keras-tuner>=1.0.4,<2.
  • Depends on kfp>=1.6.1,!=1.7.2,<1.8.2 in [kfp] extra.
  • Depends on kfp-pipeline-spec>=>=0.1.10,<0.2.
  • Depends on ml-metadata>=1.3.0,<1.4.0.
  • Depends on struct2tensor>=0.34.0,<0.35.0.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<3.
  • Depends on tensorflow-data-validation>=1.3.0,<1.4.0.
  • Depends on tensorflow-model-analysis>=0.34.1,<0.35.0.
  • Depends on tensorflow-serving-api>=1.15,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<3.
  • Depends on tensorflow-transform>=1.3.0,<1.4.0.
  • Depends on tfx-bsl>=1.3.0,<1.4.0.

Documentation Updates

  • N/A