Class: Google::Apis::MlV1::GoogleCloudMlV1Scheduling

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/ml_v1/classes.rb,
lib/google/apis/ml_v1/representations.rb,
lib/google/apis/ml_v1/representations.rb

Overview

All parameters related to scheduling of training jobs.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudMlV1Scheduling

Returns a new instance of GoogleCloudMlV1Scheduling.



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# File 'lib/google/apis/ml_v1/classes.rb', line 2398

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#max_running_time ⇒ String

Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by s. If not specified, this field defaults to 604800s (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the RUNNING state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to 7200s (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the gcloud tool, you can specify this field in a config. yaml file. For example: yaml trainingInput: scheduling: maxRunningTime: 7200s Corresponds to the JSON property maxRunningTime

Returns:

  • (String) 


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# File 'lib/google/apis/ml_v1/classes.rb', line 2364

def max_running_time
  @max_running_time
end

#max_wait_time ⇒ String

Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by s. If not specified, there is no limit to the wait time. The minimum for this field is 1800s (30 minutes). If the training job has not entered the RUNNING state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a VM restart , this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to 3600s (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the QUEUED or PREPARING state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the gcloud tool, you can specify this field in a config.yaml file. For example: yaml trainingInput: scheduling: maxWaitTime: 3600s Corresponds to the JSON property maxWaitTime

Returns:

  • (String) 


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# File 'lib/google/apis/ml_v1/classes.rb', line 2388

def max_wait_time
  @max_wait_time
end

#priority ⇒ Fixnum

Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority. Corresponds to the JSON property priority

Returns:

  • (Fixnum) 


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# File 'lib/google/apis/ml_v1/classes.rb', line 2396

def priority
  @priority
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/ml_v1/classes.rb', line 2403

def update!(**args)
  @max_running_time = args[:max_running_time] if args.key?(:max_running_time)
  @max_wait_time = args[:max_wait_time] if args.key?(:max_wait_time)
  @priority = args[:priority] if args.key?(:priority)
end