LookoutforVision / Paginator / ListModels
ListModels#
- class LookoutforVision.Paginator.ListModels#
paginator = client.get_paginator('list_models')
- paginate(**kwargs)#
Creates an iterator that will paginate through responses from
LookoutforVision.Client.list_models()
.See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate( ProjectName='string', PaginationConfig={ 'MaxItems': 123, 'PageSize': 123, 'StartingToken': 'string' } )
- Parameters:
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model versions that you want to list.
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
{ 'Models': [ { 'CreationTimestamp': datetime(2015, 1, 1), 'ModelVersion': 'string', 'ModelArn': 'string', 'Description': 'string', 'Status': 'TRAINING'|'TRAINED'|'TRAINING_FAILED'|'STARTING_HOSTING'|'HOSTED'|'HOSTING_FAILED'|'STOPPING_HOSTING'|'SYSTEM_UPDATING'|'DELETING', 'StatusMessage': 'string', 'Performance': { 'F1Score': ..., 'Recall': ..., 'Precision': ... } }, ], }
Response Structure
(dict) –
Models (list) –
A list of model versions in the specified project.
(dict) –
Describes an Amazon Lookout for Vision model.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the model was created.
ModelVersion (string) –
The version of the model.
ModelArn (string) –
The Amazon Resource Name (ARN) of the model.
Description (string) –
The description for the model.
Status (string) –
The status of the model.
StatusMessage (string) –
The status message for the model.
Performance (dict) –
Performance metrics for the model. Not available until training has successfully completed.
F1Score (float) –
The overall F1 score metric for the trained model.
Recall (float) –
The overall recall metric value for the trained model.
Precision (float) –
The overall precision metric value for the trained model.