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public static final class TrainCustomModelRequest.GcsTrainingInput.Builder extends GeneratedMessageV3.Builder<TrainCustomModelRequest.GcsTrainingInput.Builder> implements TrainCustomModelRequest.GcsTrainingInputOrBuilderCloud 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.BuilderStatic 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 |
|
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 |
|
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 |
|
clearOneof(Descriptors.OneofDescriptor oneof)
public TrainCustomModelRequest.GcsTrainingInput.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
TrainCustomModelRequest.GcsTrainingInput.Builder |
|
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\tscorequery1\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 |
|
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 |
|
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\tscorequery1\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\tscorequery1\tdoc1\t1
string train_data_path = 3;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for trainDataPath. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
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 |
|
| 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 |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final TrainCustomModelRequest.GcsTrainingInput.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
TrainCustomModelRequest.GcsTrainingInput.Builder |
|
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 |
StringThe 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 |
ByteStringThe 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 |
|
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 |
StringThe 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 |
ByteStringThe 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 |
|
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 |
StringThe 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 |
ByteStringThe 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\tscorequery1\tdoc1\t1
string train_data_path = 3;
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe 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\tscorequery1\tdoc1\t1
string train_data_path = 3;
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe 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 |
|