Struct InputDataConfig

#[non_exhaustive]
pub struct InputDataConfig {
    pub dataset_id: String,
    pub annotations_filter: String,
    pub annotation_schema_uri: String,
    pub saved_query_id: String,
    pub persist_ml_use_assignment: bool,
    pub split: Option<Split>,
    pub destination: Option<Destination>,
    /* private fields */
}

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

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.

dataset_id: String

Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline’s [training_task_definition] [google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]. For tabular Datasets, all their data is exported to training, to pick and choose from.

annotations_filter: String

Applicable only to Datasets that have DataItems and Annotations.

A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.

annotation_schema_uri: String

Applicable only to custom training with Datasets that have DataItems and Annotations.

Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id.

Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on.

When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

saved_query_id: String

Only applicable to Datasets that have SavedQueries.

The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training.

Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter.

Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

persist_ml_use_assignment: bool

Whether to persist the ML use assignment to data item system labels.

split: Option<Split>

The instructions how the input data should be split between the training, validation and test sets. If no split type is provided, the fraction_split is used by default.

destination: Option<Destination>

Only applicable to Custom and Hyperparameter Tuning TrainingPipelines.

The destination of the training data to be written to.

Supported destination file formats:

• For non-tabular data: “jsonl”.
• For tabular data: “csv” and “bigquery”.

The following Vertex AI environment variables are passed to containers or python modules of the training task when this field is set:

• AIP_DATA_FORMAT : Exported data format.
• AIP_TRAINING_DATA_URI : Sharded exported training data uris.
• AIP_VALIDATION_DATA_URI : Sharded exported validation data uris.
• AIP_TEST_DATA_URI : Sharded exported test data uris.

Implementations

impl InputDataConfig

pub fn new() -> Self

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

Sets the value of dataset_id.

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

Sets the value of annotations_filter.

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

Sets the value of annotation_schema_uri.

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

Sets the value of saved_query_id.

pub fn set_persist_ml_use_assignment<T: Into<bool>>(self, v: T) -> Self

Sets the value of persist_ml_use_assignment.

pub fn set_split<T: Into<Option<Split>>>(self, v: T) -> Self

Sets the value of split.

Note that all the setters affecting split are mutually exclusive.

pub fn fraction_split(&self) -> Option<&Box<FractionSplit>>

The value of split if it holds a FractionSplit, None if the field is not set or holds a different branch.

pub fn set_fraction_split<T: Into<Box<FractionSplit>>>(self, v: T) -> Self

Sets the value of split to hold a FractionSplit.

Note that all the setters affecting split are mutually exclusive.

pub fn filter_split(&self) -> Option<&Box<FilterSplit>>

The value of split if it holds a FilterSplit, None if the field is not set or holds a different branch.

pub fn set_filter_split<T: Into<Box<FilterSplit>>>(self, v: T) -> Self

Sets the value of split to hold a FilterSplit.

Note that all the setters affecting split are mutually exclusive.

pub fn predefined_split(&self) -> Option<&Box<PredefinedSplit>>

The value of split if it holds a PredefinedSplit, None if the field is not set or holds a different branch.

pub fn set_predefined_split<T: Into<Box<PredefinedSplit>>>(self, v: T) -> Self

Sets the value of split to hold a PredefinedSplit.

Note that all the setters affecting split are mutually exclusive.

pub fn timestamp_split(&self) -> Option<&Box<TimestampSplit>>

The value of split if it holds a TimestampSplit, None if the field is not set or holds a different branch.

pub fn set_timestamp_split<T: Into<Box<TimestampSplit>>>(self, v: T) -> Self

Sets the value of split to hold a TimestampSplit.

Note that all the setters affecting split are mutually exclusive.

pub fn stratified_split(&self) -> Option<&Box<StratifiedSplit>>

The value of split if it holds a StratifiedSplit, None if the field is not set or holds a different branch.

pub fn set_stratified_split<T: Into<Box<StratifiedSplit>>>(self, v: T) -> Self

Sets the value of split to hold a StratifiedSplit.

Note that all the setters affecting split are mutually exclusive.

pub fn set_destination<T: Into<Option<Destination>>>(self, v: T) -> Self

Sets the value of destination.

Note that all the setters affecting destination are mutually exclusive.

pub fn gcs_destination(&self) -> Option<&Box<GcsDestination>>

The value of destination if it holds a GcsDestination, None if the field is not set or holds a different branch.

pub fn set_gcs_destination<T: Into<Box<GcsDestination>>>(self, v: T) -> Self

Sets the value of destination to hold a GcsDestination.

Note that all the setters affecting destination are mutually exclusive.

pub fn bigquery_destination(&self) -> Option<&Box<BigQueryDestination>>

The value of destination if it holds a BigqueryDestination, None if the field is not set or holds a different branch.

pub fn set_bigquery_destination<T: Into<Box<BigQueryDestination>>>( self, v: T, ) -> Self

Sets the value of destination to hold a BigqueryDestination.

Note that all the setters affecting destination are mutually exclusive.

Trait Implementations

impl Clone for InputDataConfig

fn clone(&self) -> InputDataConfig

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for InputDataConfig

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

Formats the value using the given formatter.

impl Default for InputDataConfig

fn default() -> InputDataConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for InputDataConfig

where InputDataConfig: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Message for InputDataConfig

fn typename() -> &'static str

The typename of this message.

impl PartialEq for InputDataConfig

fn eq(&self, other: &InputDataConfig) -> 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 Serialize for InputDataConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for InputDataConfig