Struct aws_sdk_comprehend::model::document_classifier_input_data_config::Builder

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

A builder for DocumentClassifierInputDataConfig

Implementations

impl Builder

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

The format of your training data:

• COMPREHEND_CSV: A two-column CSV file, where labels are provided in the first column, and documents are provided in the second. If you use this value, you must provide the S3Uri parameter in your request.

• 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 associated labels.

  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.

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

The format of your training data:

• COMPREHEND_CSV: A two-column CSV file, where labels are provided in the first column, and documents are provided in the second. If you use this value, you must provide the S3Uri parameter in your request.

• 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 associated labels.

  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.

pub fn s3_uri(self, input: impl Into<String>) -> Self

The Amazon S3 URI for the input data. The S3 bucket must be in the same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files.

For example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.

This parameter is required if you set DataFormat to COMPREHEND_CSV.

pub fn set_s3_uri(self, input: Option<String>) -> Self

The Amazon S3 URI for the input data. The S3 bucket must be in the same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files.

For example, if you use the URI S3://bucketName/prefix, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.

This parameter is required if you set DataFormat to COMPREHEND_CSV.

pub fn test_s3_uri(self, input: impl Into<String>) -> Self

The Amazon S3 URI for the input data. The Amazon S3 bucket must be in the same AWS Region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files.

pub fn set_test_s3_uri(self, input: Option<String>) -> Self

The Amazon S3 URI for the input data. The Amazon S3 bucket must be in the same AWS Region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files.

pub fn label_delimiter(self, input: impl Into<String>) -> Self

Indicates the delimiter used to separate each label for training a multi-label classifier. The default delimiter between labels is a pipe (|). You can use a different character as a delimiter (if it's an allowed character) by specifying it under Delimiter for labels. If the training documents use a delimiter other than the default or the delimiter you specify, the labels on that line will be combined to make a single unique label, such as LABELLABELLABEL.

pub fn set_label_delimiter(self, input: Option<String>) -> Self

Indicates the delimiter used to separate each label for training a multi-label classifier. The default delimiter between labels is a pipe (|). You can use a different character as a delimiter (if it's an allowed character) by specifying it under Delimiter for labels. If the training documents use a delimiter other than the default or the delimiter you specify, the labels on that line will be combined to make a single unique label, such as LABELLABELLABEL.

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.

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.

pub fn build(self) -> DocumentClassifierInputDataConfig

Consumes the builder and constructs a DocumentClassifierInputDataConfig

Trait Implementations

impl Clone for Builder

fn clone(&self) -> Builder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Builder

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

Formats the value using the given formatter.

impl Default for Builder

fn default() -> Builder

Returns the “default value” for a type.

impl PartialEq<Builder> for Builder

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

This method tests for self and other values to be equal, and is used by ==.

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

This method tests for !=.

impl StructuralPartialEq for Builder