Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tfx.extensions.google_cloud_ai_platform.runner.start_aip_training

View source on GitHub

Start a trainer job on AI Platform (AIP).

tfx.extensions.google_cloud_ai_platform.runner.start_aip_training(
    input_dict, output_dict, exec_properties, executor_class_path, training_inputs,
    job_id
)

This is done by forwarding the inputs/outputs/exec_properties to the tfx.scripts.run_executor module on a AI Platform training job interpreter.

Args:

  • input_dict: Passthrough input dict for tfx.components.Trainer.executor.
  • output_dict: Passthrough input dict for tfx.components.Trainer.executor.
  • exec_properties: Passthrough input dict for tfx.components.Trainer.executor.
  • executor_class_path: class path for TFX core default trainer.
  • training_inputs: Training input argument for AI Platform training job. 'pythonModule', 'pythonVersion' and 'runtimeVersion' will be inferred. For the full set of parameters, refer to https://cloud.google.com/ml-engine/reference/rest/v1/projects.jobs#TrainingInput
  • job_id: Job ID for AI Platform Training job. If not supplied, system-determined unique ID is given. Refer to https://cloud.google.com/ml-engine/reference/rest/v1/projects.jobs#resource-job

Returns:

None

Raises:

  • RuntimeError: if the Google Cloud AI Platform training job failed.