Package com.google.cloud.discoveryengine.v1beta

Interface TrainCustomModelRequest.GcsTrainingInputOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
TrainCustomModelRequest.GcsTrainingInput, TrainCustomModelRequest.GcsTrainingInput.Builder
Enclosing class:
TrainCustomModelRequest
public static interface TrainCustomModelRequest.GcsTrainingInputOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Summary

    Modifier and Type
    Method
    Description
    String
    getCorpusDataPath()
    The Cloud Storage corpus data which could be associated in train data.
    com.google.protobuf.ByteString
    getCorpusDataPathBytes()
    The Cloud Storage corpus data which could be associated in train data.
    String
    getQueryDataPath()
    The gcs query data which could be associated in train data.
    com.google.protobuf.ByteString
    getQueryDataPathBytes()
    The gcs query data which could be associated in train data.
    String
    getTestDataPath()
    Cloud Storage test data.
    com.google.protobuf.ByteString
    getTestDataPathBytes()
    Cloud Storage test data.
    String
    getTrainDataPath()
    Cloud Storage training data path whose format should be `gs://<bucket_to_data>/<tsv_file_name>`.
    com.google.protobuf.ByteString
    getTrainDataPathBytes()
    Cloud Storage training data path whose format should be `gs://<bucket_to_data>/<tsv_file_name>`.

    Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

    isInitialized

    Methods inherited from interface com.google.protobuf.MessageOrBuilder

    findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

  • Method Details

    • getCorpusDataPath

      String getCorpusDataPath()
       The Cloud Storage corpus data which could be associated in train data.
 The data path format is `gs://<bucket_to_data>/<jsonl_file_name>`.
 A newline delimited jsonl/ndjson file.

 For search-tuning model, each line should have the _id, title
 and text. Example:
 `{"_id": "doc1", title: "relevant doc", "text": "relevant text"}`
      string corpus_data_path = 1;
      Returns:
      The corpusDataPath.

    • getCorpusDataPathBytes

      com.google.protobuf.ByteString getCorpusDataPathBytes()
       The Cloud Storage corpus data which could be associated in train data.
 The data path format is `gs://<bucket_to_data>/<jsonl_file_name>`.
 A newline delimited jsonl/ndjson file.

 For search-tuning model, each line should have the _id, title
 and text. Example:
 `{"_id": "doc1", title: "relevant doc", "text": "relevant text"}`
      string corpus_data_path = 1;
      Returns:
      The bytes for corpusDataPath.

    • getQueryDataPath

      String getQueryDataPath()
       The gcs query data which could be associated in train data.
 The data path format is `gs://<bucket_to_data>/<jsonl_file_name>`.
 A newline delimited jsonl/ndjson file.

 For search-tuning model, each line should have the _id
 and text. Example: {"_id": "query1",  "text": "example query"}
      string query_data_path = 2;
      Returns:
      The queryDataPath.

    • getQueryDataPathBytes

      com.google.protobuf.ByteString getQueryDataPathBytes()
       The gcs query data which could be associated in train data.
 The data path format is `gs://<bucket_to_data>/<jsonl_file_name>`.
 A newline delimited jsonl/ndjson file.

 For search-tuning model, each line should have the _id
 and text. Example: {"_id": "query1",  "text": "example query"}
      string query_data_path = 2;
      Returns:
      The bytes for queryDataPath.

    • getTrainDataPath

      String getTrainDataPath()
       Cloud Storage training data path whose format should be
 `gs://<bucket_to_data>/<tsv_file_name>`. The file should be in tsv
 format. Each line should have the doc_id and query_id and score (number).

 For search-tuning model, it should have the query-id corpus-id
 score as tsv file header. The score should be a number in `[0, inf+)`.
 The larger the number is, the more relevant the pair is. Example:

 * `query-id\tcorpus-id\tscore`
 * `query1\tdoc1\t1`
      string train_data_path = 3;
      Returns:
      The trainDataPath.

    • getTrainDataPathBytes

      com.google.protobuf.ByteString getTrainDataPathBytes()
       Cloud Storage training data path whose format should be
 `gs://<bucket_to_data>/<tsv_file_name>`. The file should be in tsv
 format. Each line should have the doc_id and query_id and score (number).

 For search-tuning model, it should have the query-id corpus-id
 score as tsv file header. The score should be a number in `[0, inf+)`.
 The larger the number is, the more relevant the pair is. Example:

 * `query-id\tcorpus-id\tscore`
 * `query1\tdoc1\t1`
      string train_data_path = 3;
      Returns:
      The bytes for trainDataPath.

    • getTestDataPath

      String getTestDataPath()
       Cloud Storage test data. Same format as train_data_path. If not provided,
 a random 80/20 train/test split will be performed on train_data_path.
      string test_data_path = 4;
      Returns:
      The testDataPath.

    • getTestDataPathBytes

      com.google.protobuf.ByteString getTestDataPathBytes()
       Cloud Storage test data. Same format as train_data_path. If not provided,
 a random 80/20 train/test split will be performed on train_data_path.
      string test_data_path = 4;
      Returns:
      The bytes for testDataPath.