Parses the arguments for _run_executor() then invokes it.
tfx.orchestration.kubeflow.v2.container.kubeflow_v2_run_executor.main(
argv
)
Args |
|---|
argv
|
Unparsed arguments for run_executor.py. Known argument names include
--executor_class_path: Python class of executor in format of
..
--json_serialized_invocation_args: Full JSON-serialized parameters for
this execution. The remaining part of the arguments will be parsed as
the beam args used by each component executors. Some commonly used beam
args are as follows:
--runner: The beam pipeline runner environment. Can be DirectRunner (for
running locally) or DataflowRunner (for running on GCP Dataflow
service).
--project: The GCP project ID. Neede when runner==DataflowRunner
--direct_num_workers: Number of threads or subprocesses executing the
work load.
For more about the beam arguments please refer to:
https://cloud.google.com/dataflow/docs/guides/specifying-exec-params
|
View source on GitHub