Struct GcsTrainingInput 

#[non_exhaustive]
pub struct GcsTrainingInput {
    pub corpus_data_path: String,
    pub query_data_path: String,
    pub train_data_path: String,
    pub test_data_path: String,
    /* private fields */
}

Available on crate feature search-tuning-service only.

Cloud Storage training data input.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

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.

Implementations

impl GcsTrainingInput

pub fn new() -> Self

pub fn set_corpus_data_path<T: Into<String>>(self, v: T) -> Self

Sets the value of corpus_data_path.

Example

let x = GcsTrainingInput::new().set_corpus_data_path("example");

pub fn set_query_data_path<T: Into<String>>(self, v: T) -> Self

Sets the value of query_data_path.

Example

let x = GcsTrainingInput::new().set_query_data_path("example");

pub fn set_train_data_path<T: Into<String>>(self, v: T) -> Self

Sets the value of train_data_path.

Example

let x = GcsTrainingInput::new().set_train_data_path("example");

pub fn set_test_data_path<T: Into<String>>(self, v: T) -> Self

Sets the value of test_data_path.

Example

let x = GcsTrainingInput::new().set_test_data_path("example");

Trait Implementations

impl Clone for GcsTrainingInput

fn clone(&self) -> GcsTrainingInput

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for GcsTrainingInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for GcsTrainingInput

fn default() -> GcsTrainingInput

Returns the “default value” for a type.

impl Message for GcsTrainingInput

fn typename() -> &'static str

The typename of this message.

impl PartialEq for GcsTrainingInput

fn eq(&self, other: &GcsTrainingInput) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for GcsTrainingInput