SageMaker.Client.
list_training_jobs
(**kwargs)¶Lists training jobs.
Note
When StatusEquals
and MaxResults
are set at the same time, the MaxResults
number of training jobs are first retrieved ignoring the StatusEquals
parameter and then they are filtered by the StatusEquals
parameter, which is returned as a response.
For example, if ListTrainingJobs
is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress
, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress
are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
See also: AWS API Documentation
Request Syntax
response = client.list_training_jobs(
NextToken='string',
MaxResults=123,
CreationTimeAfter=datetime(2015, 1, 1),
CreationTimeBefore=datetime(2015, 1, 1),
LastModifiedTimeAfter=datetime(2015, 1, 1),
LastModifiedTimeBefore=datetime(2015, 1, 1),
NameContains='string',
StatusEquals='InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
SortBy='Name'|'CreationTime'|'Status',
SortOrder='Ascending'|'Descending',
WarmPoolStatusEquals='Available'|'Terminated'|'Reused'|'InUse'
)
ListTrainingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.CreationTime
.Ascending
.dict
Response Syntax
{
'TrainingJobSummaries': [
{
'TrainingJobName': 'string',
'TrainingJobArn': 'string',
'CreationTime': datetime(2015, 1, 1),
'TrainingEndTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'TrainingJobStatus': 'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
'WarmPoolStatus': {
'Status': 'Available'|'Terminated'|'Reused'|'InUse',
'ResourceRetainedBillableTimeInSeconds': 123,
'ReusedByJob': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
TrainingJobSummaries (list) --
An array of TrainingJobSummary
objects, each listing a training job.
(dict) --
Provides summary information about a training job.
TrainingJobName (string) --
The name of the training job that you want a summary for.
TrainingJobArn (string) --
The Amazon Resource Name (ARN) of the training job.
CreationTime (datetime) --
A timestamp that shows when the training job was created.
TrainingEndTime (datetime) --
A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses ( Completed
, Failed
, or Stopped
).
LastModifiedTime (datetime) --
Timestamp when the training job was last modified.
TrainingJobStatus (string) --
The status of the training job.
WarmPoolStatus (dict) --
The status of the warm pool associated with the training job.
Status (string) --
The status of the warm pool.
InUse
: The warm pool is in use for the training job.Available
: The warm pool is available to reuse for a matching training job.Reused
: The warm pool moved to a matching training job for reuse.Terminated
: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds
.ResourceRetainedBillableTimeInSeconds (integer) --
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds
by the number of instances ( InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount
.
ReusedByJob (string) --
The name of the matching training job that reused the warm pool.
NextToken (string) --
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.