Class TrainCustomModelRequest.GcsTrainingInput.Builder (0.29.0)

public static final class TrainCustomModelRequest.GcsTrainingInput.Builder extends GeneratedMessageV3.Builder<TrainCustomModelRequest.GcsTrainingInput.Builder> implements TrainCustomModelRequest.GcsTrainingInputOrBuilder

Gcs training data input.

Protobuf type google.cloud.discoveryengine.v1alpha.TrainCustomModelRequest.GcsTrainingInput

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TrainCustomModelRequest.GcsTrainingInput.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

build()

public TrainCustomModelRequest.GcsTrainingInput build()
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput

buildPartial()

public TrainCustomModelRequest.GcsTrainingInput buildPartial()
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput

clear()

public TrainCustomModelRequest.GcsTrainingInput.Builder clear()
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

clearCorpusDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearCorpusDataPath()

The gcs 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
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public TrainCustomModelRequest.GcsTrainingInput.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public TrainCustomModelRequest.GcsTrainingInput.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

clearQueryDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearQueryDataPath()

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
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

clearTestDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearTestDataPath()

Gcs 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
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

clearTrainDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearTrainDataPath()

Gcs 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
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

clone()

public TrainCustomModelRequest.GcsTrainingInput.Builder clone()
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

getCorpusDataPath()

public String getCorpusDataPath()

The gcs 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
TypeDescription
String

The corpusDataPath.

getCorpusDataPathBytes()

public ByteString getCorpusDataPathBytes()

The gcs 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
TypeDescription
ByteString

The bytes for corpusDataPath.

getDefaultInstanceForType()

public TrainCustomModelRequest.GcsTrainingInput getDefaultInstanceForType()
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getQueryDataPath()

public 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
TypeDescription
String

The queryDataPath.

getQueryDataPathBytes()

public 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
TypeDescription
ByteString

The bytes for queryDataPath.

getTestDataPath()

public String getTestDataPath()

Gcs 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
TypeDescription
String

The testDataPath.

getTestDataPathBytes()

public ByteString getTestDataPathBytes()

Gcs 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
TypeDescription
ByteString

The bytes for testDataPath.

getTrainDataPath()

public String getTrainDataPath()

Gcs 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
TypeDescription
String

The trainDataPath.

getTrainDataPathBytes()

public ByteString getTrainDataPathBytes()

Gcs 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
TypeDescription
ByteString

The bytes for trainDataPath.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(TrainCustomModelRequest.GcsTrainingInput other)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(TrainCustomModelRequest.GcsTrainingInput other)
Parameter
NameDescription
otherTrainCustomModelRequest.GcsTrainingInput
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides
Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TrainCustomModelRequest.GcsTrainingInput.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

setCorpusDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setCorpusDataPath(String value)

The gcs 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;

Parameter
NameDescription
valueString

The corpusDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setCorpusDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setCorpusDataPathBytes(ByteString value)

The gcs 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;

Parameter
NameDescription
valueByteString

The bytes for corpusDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

setQueryDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setQueryDataPath(String value)

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;

Parameter
NameDescription
valueString

The queryDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setQueryDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setQueryDataPathBytes(ByteString value)

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;

Parameter
NameDescription
valueByteString

The bytes for queryDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides

setTestDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTestDataPath(String value)

Gcs 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;

Parameter
NameDescription
valueString

The testDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setTestDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTestDataPathBytes(ByteString value)

Gcs 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;

Parameter
NameDescription
valueByteString

The bytes for testDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setTrainDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTrainDataPath(String value)

Gcs 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;

Parameter
NameDescription
valueString

The trainDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setTrainDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTrainDataPathBytes(ByteString value)

Gcs 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;

Parameter
NameDescription
valueByteString

The bytes for trainDataPath to set.

Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TrainCustomModelRequest.GcsTrainingInput.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TrainCustomModelRequest.GcsTrainingInput.Builder
Overrides