SageMaker / Paginator / ListInferenceExperiments
ListInferenceExperiments#
- class SageMaker.Paginator.ListInferenceExperiments#
paginator = client.get_paginator('list_inference_experiments')
- paginate(**kwargs)#
Creates an iterator that will paginate through responses from
SageMaker.Client.list_inference_experiments()
.See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate( NameContains='string', Type='ShadowMode', StatusEquals='Creating'|'Created'|'Updating'|'Running'|'Starting'|'Stopping'|'Completed'|'Cancelled', CreationTimeAfter=datetime(2015, 1, 1), CreationTimeBefore=datetime(2015, 1, 1), LastModifiedTimeAfter=datetime(2015, 1, 1), LastModifiedTimeBefore=datetime(2015, 1, 1), SortBy='Name'|'CreationTime'|'Status', SortOrder='Ascending'|'Descending', PaginationConfig={ 'MaxItems': 123, 'PageSize': 123, 'StartingToken': 'string' } )
- Parameters:
NameContains (string) – Selects inference experiments whose names contain this name.
Type (string) – Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperimentRequest$Type.
StatusEquals (string) – Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperimentResponse$Status.
CreationTimeAfter (datetime) – Selects inference experiments which were created after this timestamp.
CreationTimeBefore (datetime) – Selects inference experiments which were created before this timestamp.
LastModifiedTimeAfter (datetime) – Selects inference experiments which were last modified after this timestamp.
LastModifiedTimeBefore (datetime) – Selects inference experiments which were last modified before this timestamp.
SortBy (string) – The column by which to sort the listed inference experiments.
SortOrder (string) – The direction of sorting (ascending or descending).
PaginationConfig (dict) –
A dictionary that provides parameters to control pagination.
MaxItems (integer) –
The total number of items to return. If the total number of items available is more than the value specified in max-items then a
NextToken
will be provided in the output that you can use to resume pagination.PageSize (integer) –
The size of each page.
StartingToken (string) –
A token to specify where to start paginating. This is the
NextToken
from a previous response.
- Return type:
dict
- Returns:
Response Syntax
{ 'InferenceExperiments': [ { 'Name': 'string', 'Type': 'ShadowMode', 'Schedule': { 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) }, 'Status': 'Creating'|'Created'|'Updating'|'Running'|'Starting'|'Stopping'|'Completed'|'Cancelled', 'StatusReason': 'string', 'Description': 'string', 'CreationTime': datetime(2015, 1, 1), 'CompletionTime': datetime(2015, 1, 1), 'LastModifiedTime': datetime(2015, 1, 1), 'RoleArn': 'string' }, ], }
Response Structure
(dict) –
InferenceExperiments (list) –
List of inference experiments.
(dict) –
Lists a summary of properties of an inference experiment.
Name (string) –
The name of the inference experiment.
Type (string) –
The type of the inference experiment.
Schedule (dict) –
The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
StartTime (datetime) –
The timestamp at which the inference experiment started or will start.
EndTime (datetime) –
The timestamp at which the inference experiment ended or will end.
Status (string) –
The status of the inference experiment.
StatusReason (string) –
The error message for the inference experiment status result.
Description (string) –
The description of the inference experiment.
CreationTime (datetime) –
The timestamp at which the inference experiment was created.
CompletionTime (datetime) –
The timestamp at which the inference experiment was completed.
LastModifiedTime (datetime) –
The timestamp when you last modified the inference experiment.
RoleArn (string) –
The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.