Major Features and Improvements
- Added experimental exit_handler support for KubeflowDagRunner.
- Enabled custom labels to be submitted to CAIP training jobs.
- Enabled custom Python function-based components to share pipeline Beam
configuration by [inheriting from BaseBeamComponent]
(https://www.tensorflow.org/tfx/guide/custom_function_component)
Breaking Changes
For Pipeline Authors
- N/A
For Component Authors
- N/A
Deprecations
- N/A
Bug Fixes and Other Changes
LatestBlessedModelStrategy
gracefully handles the case where there are no
blessed model at all (e.g. first run).- Fix that the resolver with custom
ResolverStrategy
(assume correctly
packaged) fails. - Fixed
ElwcBigQueryExampleGen
data serializiation error that was causing an
assertion failure on Beam. - Added dark mode styling support for InteractiveContext notebook formatters.
- (Python 3.9+) Supports
list
anddict
in type definition of execution
properties. - Populate Artifact proto
name
field when name is set on the Artifact python
object. - Temporarily capped
apache-airflow
version to 2.2.x to avoid dependency
conflict. We will rollback this change oncekfp
releases a new version. - Fixed a compatibility issue with apache-airflow 2.3.0 that is failing with
"unexpected keyword argument 'default_args'". - StatisticsGen will raise an error if unsupported StatsOptions (i.e.,
generators or experimental_slice_functions) are passed.
Dependency Updates
Package Name | Version Constraints | Previously (in v1.7.0 )
| Comments |
---|---|---|---|
apache-beam[gcp]
| >=2.38,<3
| >=2.36,<3
| Synced release train |
Documentation Updates
- N/A