Reference documentation and code samples for the Cloud AutoML V1 Client class OutputConfig.
- For Translation:
CSV file
translation.csv
, with each line in format: ML_USE,GCS_FILE_PATH GCS_FILE_PATH leads to a .TSV file which describes examples that have given ML_USE, using the following row format per line: TEXT_SNIPPET (in source language) \t TEXT_SNIPPET (in target language)- For Tables: Output depends on whether the dataset was imported from Google Cloud Storage or BigQuery.
Google Cloud Storage case: gcs_destination
must be set. Exported are CSV file(s) tables_1.csv
, tables_2.csv
,..., tables_N.csv
with each having as header line
the table's column names, and all other lines contain values for
the header columns.
BigQuery case: bigquery_destination
pointing to a BigQuery project must be set. In the given project a
new dataset will be created with name export_data_<automl-dataset-display-name>_<timestamp-of-export-call>
where
Generated from protobuf message google.cloud.automl.v1.OutputConfig
Namespace
Google \ Cloud \ AutoMl \ V1Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ gcs_destination
GcsDestination
Required. The Google Cloud Storage location where the output is to be written to. For Image Object Detection, Text Extraction, Video Classification and Tables, in the given directory a new directory will be created with name: export_data-
getGcsDestination
Required. The Google Cloud Storage location where the output is to be written to. For Image Object Detection, Text Extraction, Video Classification and Tables, in the given directory a new directory will be created with name: export_data-
hasGcsDestination
setGcsDestination
Required. The Google Cloud Storage location where the output is to be written to. For Image Object Detection, Text Extraction, Video Classification and Tables, in the given directory a new directory will be created with name: export_data-
$this
getDestination
string