Reference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::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][google.cloud.automl.v1p1beta.OutputConfig.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][google.cloud.automl.v1p1beta.OutputConfig.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
(::Google::Cloud::AutoML::V1::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-
value (::Google::Cloud::AutoML::V1::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-
Returns
(::Google::Cloud::AutoML::V1::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-
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Cloud AutoML V1 API - Class Google::Cloud::AutoML::V1::OutputConfig (v1.3.1)\n\nVersion latestkeyboard_arrow_down\n\n- [1.3.1 (latest)](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-OutputConfig)\n- [1.3.0](/ruby/docs/reference/google-cloud-automl-v1/1.3.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [1.2.1](/ruby/docs/reference/google-cloud-automl-v1/1.2.1/Google-Cloud-AutoML-V1-OutputConfig)\n- [1.1.0](/ruby/docs/reference/google-cloud-automl-v1/1.1.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [1.0.1](/ruby/docs/reference/google-cloud-automl-v1/1.0.1/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.10.0](/ruby/docs/reference/google-cloud-automl-v1/0.10.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.9.2](/ruby/docs/reference/google-cloud-automl-v1/0.9.2/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.8.0](/ruby/docs/reference/google-cloud-automl-v1/0.8.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.7.0](/ruby/docs/reference/google-cloud-automl-v1/0.7.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.6.0](/ruby/docs/reference/google-cloud-automl-v1/0.6.0/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.5.1](/ruby/docs/reference/google-cloud-automl-v1/0.5.1/Google-Cloud-AutoML-V1-OutputConfig)\n- [0.4.8](/ruby/docs/reference/google-cloud-automl-v1/0.4.8/Google-Cloud-AutoML-V1-OutputConfig) \nReference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::OutputConfig.\n\n- For Translation:\n CSV file `translation.csv`, with each line in format:\n ML_USE,GCS_FILE_PATH\n GCS_FILE_PATH leads to a .TSV file which describes examples that have\n given ML_USE, using the following row format per line:\n TEXT_SNIPPET (in source language) \\\\t TEXT_SNIPPET (in target\n language)\n\n- For Tables: Output depends on whether the dataset was imported from Google Cloud Storage or BigQuery. Google Cloud Storage case: \\[gcs_destination\\]\\[google.cloud.automl.v1p1beta.OutputConfig.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\\]\\[google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination\\] pointing to a BigQuery project must be set. In the given project a new dataset will be created with name `export_data_\u003cautoml-dataset-display-name\u003e_\u003ctimestamp-of-export-call\u003e` where \n\nInherits\n--------\n\n- Object \n\nExtended By\n-----------\n\n- Google::Protobuf::MessageExts::ClassMethods \n\nIncludes\n--------\n\n- Google::Protobuf::MessageExts\n\nMethods\n-------\n\n### #gcs_destination\n\n def gcs_destination() -\u003e ::Google::Cloud::AutoML::V1::GcsDestination\n\n**Returns**\n\n- ([::Google::Cloud::AutoML::V1::GcsDestination](./Google-Cloud-AutoML-V1-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-\n\n### #gcs_destination=\n\n def gcs_destination=(value) -\u003e ::Google::Cloud::AutoML::V1::GcsDestination\n\n**Parameter**\n\n- **value** ([::Google::Cloud::AutoML::V1::GcsDestination](./Google-Cloud-AutoML-V1-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- \n**Returns**\n\n- ([::Google::Cloud::AutoML::V1::GcsDestination](./Google-Cloud-AutoML-V1-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-"]]
