Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::Scheduling (v0.38.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::Scheduling.

All parameters related to queuing and scheduling of custom jobs.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#disable_retries

def disable_retries() -> ::Boolean
Returns
  • (::Boolean) — Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.

#disable_retries=

def disable_retries=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
Returns
  • (::Boolean) — Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.

#restart_job_on_worker_restart

def restart_job_on_worker_restart() -> ::Boolean
Returns
  • (::Boolean) — Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.

#restart_job_on_worker_restart=

def restart_job_on_worker_restart=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
Returns
  • (::Boolean) — Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.

#timeout

def timeout() -> ::Google::Protobuf::Duration
Returns

#timeout=

def timeout=(value) -> ::Google::Protobuf::Duration
Parameter
Returns