Struct EntityRecognizerInputDataConfigBuilder

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#[non_exhaustive]
pub struct EntityRecognizerInputDataConfigBuilder { /* private fields */ }

Expand description

A builder for EntityRecognizerInputDataConfig.

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impl EntityRecognizerInputDataConfigBuilder

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pub fn data_format(self, input: EntityRecognizerDataFormat) -> Self

The format of your training data:

COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.

If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.

If you use this value, you must provide the AugmentedManifests parameter in your request.

If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.

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pub fn set_data_format(self, input: Option<EntityRecognizerDataFormat>) -> Self

The format of your training data:

COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.

If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.

If you use this value, you must provide the AugmentedManifests parameter in your request.

If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.

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pub fn get_data_format(&self) -> &Option<EntityRecognizerDataFormat>

The format of your training data:

COMPREHEND_CSV: A CSV file that supplements your training documents. The CSV file contains information about the custom entities that your trained model will detect. The required format of the file depends on whether you are providing annotations or an entity list.

If you use this value, you must provide your CSV file by using either the Annotations or EntityList parameters. You must provide your training documents by using the Documents parameter.
AUGMENTED_MANIFEST: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its labels. Each label annotates a named entity in the training document.

If you use this value, you must provide the AugmentedManifests parameter in your request.

If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV as the default.

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pub fn entity_types(self, input: EntityTypesListItem) -> Self

Appends an item to entity_types.

To override the contents of this collection use set_entity_types.

The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.

A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).

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pub fn set_entity_types(self, input: Option<Vec<EntityTypesListItem>>) -> Self

The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.

A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).

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pub fn get_entity_types(&self) -> &Option<Vec<EntityTypesListItem>>

The entity types in the labeled training data that Amazon Comprehend uses to train the custom entity recognizer. Any entity types that you don't specify are ignored.

A maximum of 25 entity types can be used at one time to train an entity recognizer. Entity types must not contain the following invalid characters: \n (line break), \\n (escaped line break), \r (carriage return), \\r (escaped carriage return), \t (tab), \\t (escaped tab), space, and , (comma).

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pub fn documents(self, input: EntityRecognizerDocuments) -> Self

The S3 location of the folder that contains the training documents for your custom entity recognizer.

This parameter is required if you set DataFormat to COMPREHEND_CSV.

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pub fn set_documents(self, input: Option<EntityRecognizerDocuments>) -> Self

The S3 location of the folder that contains the training documents for your custom entity recognizer.

This parameter is required if you set DataFormat to COMPREHEND_CSV.

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pub fn get_documents(&self) -> &Option<EntityRecognizerDocuments>

The S3 location of the folder that contains the training documents for your custom entity recognizer.

This parameter is required if you set DataFormat to COMPREHEND_CSV.

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pub fn annotations(self, input: EntityRecognizerAnnotations) -> Self

The S3 location of the CSV file that annotates your training documents.

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pub fn set_annotations(self, input: Option<EntityRecognizerAnnotations>) -> Self

The S3 location of the CSV file that annotates your training documents.

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pub fn get_annotations(&self) -> &Option<EntityRecognizerAnnotations>

The S3 location of the CSV file that annotates your training documents.

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pub fn entity_list(self, input: EntityRecognizerEntityList) -> Self

The S3 location of the CSV file that has the entity list for your custom entity recognizer.

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pub fn set_entity_list(self, input: Option<EntityRecognizerEntityList>) -> Self

The S3 location of the CSV file that has the entity list for your custom entity recognizer.

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pub fn get_entity_list(&self) -> &Option<EntityRecognizerEntityList>

The S3 location of the CSV file that has the entity list for your custom entity recognizer.

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pub fn augmented_manifests(self, input: AugmentedManifestsListItem) -> Self

Appends an item to augmented_manifests.

To override the contents of this collection use set_augmented_manifests.

A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.

This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.

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pub fn set_augmented_manifests( self, input: Option<Vec<AugmentedManifestsListItem>>, ) -> Self

A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.

This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.

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pub fn get_augmented_manifests( &self, ) -> &Option<Vec<AugmentedManifestsListItem>>

A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.

This parameter is required if you set DataFormat to AUGMENTED_MANIFEST.

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pub fn build(self) -> Result<EntityRecognizerInputDataConfig, BuildError>

Consumes the builder and constructs a EntityRecognizerInputDataConfig. This method will fail if any of the following fields are not set:

entity_types

Trait Implementations§

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impl Clone for EntityRecognizerInputDataConfigBuilder

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fn clone(&self) -> EntityRecognizerInputDataConfigBuilder

Returns a copy of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for EntityRecognizerInputDataConfigBuilder

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

Formats the value using the given formatter. Read more

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impl Default for EntityRecognizerInputDataConfigBuilder

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fn default() -> EntityRecognizerInputDataConfigBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for EntityRecognizerInputDataConfigBuilder

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

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

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

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

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impl StructuralPartialEq for EntityRecognizerInputDataConfigBuilder

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impl UnwindSafe for EntityRecognizerInputDataConfigBuilder

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Struct EntityRecognizerInputDataConfigBuilderCopy item path

Implementations§

impl EntityRecognizerInputDataConfigBuilder

pub fn data_format(self, input: EntityRecognizerDataFormat) -> Self

pub fn set_data_format(self, input: Option<EntityRecognizerDataFormat>) -> Self

pub fn get_data_format(&self) -> &Option<EntityRecognizerDataFormat>

pub fn entity_types(self, input: EntityTypesListItem) -> Self

pub fn set_entity_types(self, input: Option<Vec<EntityTypesListItem>>) -> Self

pub fn get_entity_types(&self) -> &Option<Vec<EntityTypesListItem>>

pub fn documents(self, input: EntityRecognizerDocuments) -> Self

pub fn set_documents(self, input: Option<EntityRecognizerDocuments>) -> Self

pub fn get_documents(&self) -> &Option<EntityRecognizerDocuments>

pub fn annotations(self, input: EntityRecognizerAnnotations) -> Self

pub fn set_annotations(self, input: Option<EntityRecognizerAnnotations>) -> Self

pub fn get_annotations(&self) -> &Option<EntityRecognizerAnnotations>

pub fn entity_list(self, input: EntityRecognizerEntityList) -> Self

pub fn set_entity_list(self, input: Option<EntityRecognizerEntityList>) -> Self

pub fn get_entity_list(&self) -> &Option<EntityRecognizerEntityList>

pub fn augmented_manifests(self, input: AugmentedManifestsListItem) -> Self

pub fn set_augmented_manifests( self, input: Option<Vec<AugmentedManifestsListItem>>, ) -> Self

pub fn get_augmented_manifests( &self, ) -> &Option<Vec<AugmentedManifestsListItem>>

pub fn build(self) -> Result<EntityRecognizerInputDataConfig, BuildError>

Trait Implementations§

impl Clone for EntityRecognizerInputDataConfigBuilder

fn clone(&self) -> EntityRecognizerInputDataConfigBuilder

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

impl Debug for EntityRecognizerInputDataConfigBuilder

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

impl Default for EntityRecognizerInputDataConfigBuilder

fn default() -> EntityRecognizerInputDataConfigBuilder

impl PartialEq for EntityRecognizerInputDataConfigBuilder

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

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

impl StructuralPartialEq for EntityRecognizerInputDataConfigBuilder

Auto Trait Implementations§

impl Freeze for EntityRecognizerInputDataConfigBuilder

impl RefUnwindSafe for EntityRecognizerInputDataConfigBuilder

impl Send for EntityRecognizerInputDataConfigBuilder

impl Sync for EntityRecognizerInputDataConfigBuilder

impl Unpin for EntityRecognizerInputDataConfigBuilder

impl UnwindSafe for EntityRecognizerInputDataConfigBuilder

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impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unsharedwhere Shared: FromUnshared<Unshared>,

fn into_shared(self) -> Shared

impl<T> Paint for Twhere T: ?Sized,

fn fg(&self, value: Color) -> Painted<&T>

§Example

fn primary(&self) -> Painted<&T>

§Example

fn fixed(&self, color: u8) -> Painted<&T>

§Example

fn rgb(&self, r: u8, g: u8, b: u8) -> Painted<&T>

§Example

fn black(&self) -> Painted<&T>

§Example

fn red(&self) -> Painted<&T>

§Example

fn green(&self) -> Painted<&T>

§Example

fn yellow(&self) -> Painted<&T>

§Example

fn blue(&self) -> Painted<&T>

Struct EntityRecognizerInputDataConfigBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,