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 CreateInferenceExperiment. 
- StatusEquals (string) – Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment. 
- 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 - NextTokenwill 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 - NextTokenfrom 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.