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Class GoogleCloudDiscoveryengineV1alphaTrainCustomModelRequestGcsTrainingInput

Cloud Storage training data input.

Inheritance
object
GoogleCloudDiscoveryengineV1alphaTrainCustomModelRequestGcsTrainingInput
Implements
IDirectResponseSchema
Inherited Members
object.Equals(object)
object.Equals(object, object)
object.GetHashCode()
object.GetType()
object.MemberwiseClone()
object.ReferenceEquals(object, object)
object.ToString()
Namespace: Google.Apis.DiscoveryEngine.v1alpha.Data
Assembly: Google.Apis.DiscoveryEngine.v1alpha.dll
Syntax
public class GoogleCloudDiscoveryengineV1alphaTrainCustomModelRequestGcsTrainingInput : IDirectResponseSchema

Properties

CorpusDataPath

The Cloud Storage corpus data which could be associated in train data. The data path format is gs:///. 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"}

Declaration
[JsonProperty("corpusDataPath")]
public virtual string CorpusDataPath { get; set; }
Property Value
Type Description
string

ETag

The ETag of the item.

Declaration
public virtual string ETag { get; set; }
Property Value
Type Description
string

QueryDataPath

The gcs query data which could be associated in train data. The data path format is gs:///. A newline delimited jsonl/ndjson file. For search-tuning model, each line should have the _id and text. Example: {"_id": "query1", "text": "example query"}

Declaration
[JsonProperty("queryDataPath")]
public virtual string QueryDataPath { get; set; }
Property Value
Type Description
string

TestDataPath

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.

Declaration
[JsonProperty("testDataPath")]
public virtual string TestDataPath { get; set; }
Property Value
Type Description
string

TrainDataPath

Cloud Storage training data path whose format should be gs:///. 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

Declaration
[JsonProperty("trainDataPath")]
public virtual string TrainDataPath { get; set; }
Property Value
Type Description
string

Implements

IDirectResponseSchema
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