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'
}
)
[REQUIRED]
The name of the project that contains the model versions that you want to list.
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
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.