Class TrainCustomModelRequest.GcsTrainingInput.Builder (0.40.0)

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

Cloud Storage training data input.

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

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TrainCustomModelRequest.GcsTrainingInput.Builder

Implements

TrainCustomModelRequest.GcsTrainingInputOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TrainCustomModelRequest.GcsTrainingInput.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public TrainCustomModelRequest.GcsTrainingInput build()

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput

buildPartial()

public TrainCustomModelRequest.GcsTrainingInput buildPartial()

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput

clear()

public TrainCustomModelRequest.GcsTrainingInput.Builder clear()

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearCorpusDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearCorpusDataPath()

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
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public TrainCustomModelRequest.GcsTrainingInput.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearOneof(Descriptors.OneofDescriptor oneof)

public TrainCustomModelRequest.GcsTrainingInput.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

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
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

clearTestDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearTestDataPath()

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
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

clearTrainDataPath()

public TrainCustomModelRequest.GcsTrainingInput.Builder clearTrainDataPath()

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
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

clone()

public TrainCustomModelRequest.GcsTrainingInput.Builder clone()

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getCorpusDataPath()

public 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
Type	Description
String	The corpusDataPath.

getCorpusDataPathBytes()

public 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
Type	Description
ByteString	The bytes for corpusDataPath.

getDefaultInstanceForType()

public TrainCustomModelRequest.GcsTrainingInput getDefaultInstanceForType()

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

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
Type	Description
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
Type	Description
ByteString	The bytes for queryDataPath.

getTestDataPath()

public 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
Type	Description
String	The testDataPath.

getTestDataPathBytes()

public 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
Type	Description
ByteString	The bytes for testDataPath.

getTrainDataPath()

public 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
Type	Description
String	The trainDataPath.

getTrainDataPathBytes()

public 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
Type	Description
ByteString	The bytes for trainDataPath.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(TrainCustomModelRequest.GcsTrainingInput other)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(TrainCustomModelRequest.GcsTrainingInput other)

Parameter
Name	Description
other	TrainCustomModelRequest.GcsTrainingInput

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public TrainCustomModelRequest.GcsTrainingInput.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TrainCustomModelRequest.GcsTrainingInput.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

setCorpusDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setCorpusDataPath(String value)

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;

Parameter
Name	Description
value	String The corpusDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setCorpusDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setCorpusDataPathBytes(ByteString value)

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;

Parameter
Name	Description
value	ByteString The bytes for corpusDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

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
Name	Description
value	String The queryDataPath to set.

Returns
Type	Description
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
Name	Description
value	ByteString The bytes for queryDataPath to set.

Returns
Type	Description
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
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setTestDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTestDataPath(String value)

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;

Parameter
Name	Description
value	String The testDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setTestDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTestDataPathBytes(ByteString value)

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;

Parameter
Name	Description
value	ByteString The bytes for testDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setTrainDataPath(String value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTrainDataPath(String value)

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;

Parameter
Name	Description
value	String The trainDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setTrainDataPathBytes(ByteString value)

public TrainCustomModelRequest.GcsTrainingInput.Builder setTrainDataPathBytes(ByteString value)

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;

Parameter
Name	Description
value	ByteString The bytes for trainDataPath to set.

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TrainCustomModelRequest.GcsTrainingInput.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
TrainCustomModelRequest.GcsTrainingInput.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)