delete_dataset
(**kwargs)¶Deletes an existing Amazon Lookout for Vision dataset
.
If your the project has a single dataset, you must create a new dataset before you can create a model.
If you project has a training dataset and a test dataset consider the following.
This operation requires permissions to perform the lookoutvision:DeleteDataset
operation.
See also: AWS API Documentation
Request Syntax
response = client.delete_dataset(
ProjectName='string',
DatasetType='string',
ClientToken='string'
)
[REQUIRED]
The name of the project that contains the dataset that you want to delete.
[REQUIRED]
The type of the dataset to delete. Specify train
to delete the training dataset. Specify test
to delete the test dataset. To delete the dataset in a single dataset project, specify train
.
ClientToken is an idempotency token that ensures a call to DeleteDataset
completes only once. You choose the value to pass. For example, An issue might prevent you from getting a response from DeleteDataset
. In this case, safely retry your call to DeleteDataset
by using the same ClientToken
parameter value.
If you don't supply a value for ClientToken
, the AWS SDK you are using inserts a value for you. This prevents retries after a network error from making multiple deletetion requests. You'll need to provide your own value for other use cases.
An error occurs if the other input parameters are not the same as in the first request. Using a different value for ClientToken
is considered a new call to DeleteDataset
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{}
Response Structure
Exceptions
LookoutforVision.Client.exceptions.AccessDeniedException
LookoutforVision.Client.exceptions.InternalServerException
LookoutforVision.Client.exceptions.ValidationException
LookoutforVision.Client.exceptions.ConflictException
LookoutforVision.Client.exceptions.ResourceNotFoundException
LookoutforVision.Client.exceptions.ThrottlingException