Google Cloud Discovery Engine V1beta Client - Class GcsTrainingInput (0.11.3)

Version 0.11.3

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• 0.11.3
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• 0.1.1

Beta

This library is covered by the Pre-GA Offerings Terms of the Terms of Service. Pre-GA libraries might have limited support, and changes to pre-GA libraries might not be compatible with other pre-GA versions. For more information, see the launch stage descriptions.

Reference documentation and code samples for the Google Cloud Discovery Engine V1beta Client class GcsTrainingInput.

Cloud Storage training data input.

Generated from protobuf message google.cloud.discoveryengine.v1beta.TrainCustomModelRequest.GcsTrainingInput

Namespace

Google \ Cloud \ DiscoveryEngine \ V1beta \ TrainCustomModelRequest

Methods

__construct

Constructor.

Parameters
Name	Description
data	array Optional. Data for populating the Message object.
↳ corpus_data_path	string 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"}
↳ query_data_path	string 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"}
↳ train_data_path	string 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
↳ test_data_path	string 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.

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"}

Returns
Type	Description
string

setCorpusDataPath

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"}

Parameter
Name	Description
var	string

Returns
Type	Description
$this

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"}

Returns
Type	Description
string

setQueryDataPath

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"}

Parameter
Name	Description
var	string

Returns
Type	Description
$this

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

Returns
Type	Description
string

setTrainDataPath

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

Parameter
Name	Description
var	string

Returns
Type	Description
$this

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.

Returns
Type	Description
string

setTestDataPath

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.

Parameter
Name	Description
var	string

Returns
Type	Description
$this