Exports data from a Dataset.
HTTP request
POST https://{service-endpoint}/v1beta1/{name}:export
Where {service-endpoint}
is one of the supported service endpoints.
Path parameters
Parameters | |
---|---|
name |
Required. The name of the Dataset resource. Format: |
Request body
The request body contains data with the following structure:
JSON representation |
---|
{
"exportConfig": {
object ( |
Fields | |
---|---|
exportConfig |
Required. The desired output location. |
Response body
If successful, the response body contains an instance of Operation
.
Authorization scopes
Requires the following OAuth scope:
https://www.googleapis.com/auth/cloud-platform
For more information, see the Authentication Overview.
IAM Permissions
Requires the following IAM permission on the name
resource:
aiplatform.datasets.export
For more information, see the IAM documentation.
ExportDataConfig
Describes what part of the Dataset is to be exported, the destination of the export and how to export.
JSON representation |
---|
{ "annotationsFilter": string, // Union field |
Fields | |
---|---|
annotationsFilter |
An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in |
Union field destination . The destination of the output. destination can be only one of the following: |
|
gcsDestination |
The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: |
Union field split . The instructions how the export data should be split between the training, validation and test sets. split can be only one of the following: |
|
fractionSplit |
Split based on fractions defining the size of each set. |
ExportFractionSplit
Assigns the input data to training, validation, and test sets as per the given fractions. Any of trainingFraction
, validationFraction
and testFraction
may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.
JSON representation |
---|
{ "trainingFraction": number, "validationFraction": number, "testFraction": number } |
Fields | |
---|---|
trainingFraction |
The fraction of the input data that is to be used to train the Model. |
validationFraction |
The fraction of the input data that is to be used to validate the Model. |
testFraction |
The fraction of the input data that is to be used to evaluate the Model. |