Version 1.8.0

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)

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 and dict 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 once kfp 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.

Package Name	Version Constraints	Previously (in `v1.7.0`)	Comments
`apache-beam[gcp]`	`>=2.38,<3`	`>=2.36,<3`	Synced release train