com.google.cloud.discoveryengine.v1alpha

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 and 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.MessageOrBuilder

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

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

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.