Struct aws_sdk_comprehend::operation::create_document_classifier::CreateDocumentClassifierInput

#[non_exhaustive]
pub struct CreateDocumentClassifierInput {

    pub document_classifier_name: Option<String>,
    pub version_name: Option<String>,
    pub data_access_role_arn: Option<String>,
    pub tags: Option<Vec<Tag>>,
    pub input_data_config: Option<DocumentClassifierInputDataConfig>,
    pub output_data_config: Option<DocumentClassifierOutputDataConfig>,
    pub client_request_token: Option<String>,
    pub language_code: Option<LanguageCode>,
    pub volume_kms_key_id: Option<String>,
    pub vpc_config: Option<VpcConfig>,
    pub mode: Option<DocumentClassifierMode>,
    pub model_kms_key_id: Option<String>,
    pub model_policy: Option<String>,
}

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.

document_classifier_name: Option<String>

The name of the document classifier.

version_name: Option<String>

The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the Amazon Web Services account/Amazon Web Services Region.

data_access_role_arn: Option<String>

The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.

tags: Option<Vec<Tag>>

Tags to associate with the document classifier. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.

input_data_config: Option<DocumentClassifierInputDataConfig>

Specifies the format and location of the input data for the job.

output_data_config: Option<DocumentClassifierOutputDataConfig>

Specifies the location for the output files from a custom classifier job. This parameter is required for a request that creates a native document model.

client_request_token: Option<String>

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

language_code: Option<LanguageCode>

The language of the input documents. You can specify any of the languages supported by Amazon Comprehend. All documents must be in the same language.

volume_kms_key_id: Option<String>

ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

vpc_config: Option<VpcConfig>

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC.

mode: Option<DocumentClassifierMode>

Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class mode, which identifies one and only one class for each document, or multi-label mode, which identifies one or more labels for each document. In multi-label mode, multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).

model_kms_key_id: Option<String>

ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

model_policy: Option<String>

The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another Amazon Web Services account to import your custom model.

Provide your policy as a JSON body that you enter as a UTF-8 encoded string without line breaks. To provide valid JSON, enclose the attribute names and values in double quotes. If the JSON body is also enclosed in double quotes, then you must escape the double quotes that are inside the policy:

"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"

To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:

'{"attribute": "value", "attribute": ["value"]}'

Implementations

impl CreateDocumentClassifierInput

pub fn document_classifier_name(&self) -> Option<&str>

The name of the document classifier.

pub fn version_name(&self) -> Option<&str>

The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the Amazon Web Services account/Amazon Web Services Region.

pub fn data_access_role_arn(&self) -> Option<&str>

The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.

pub fn tags(&self) -> &[Tag]

Tags to associate with the document classifier. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .tags.is_none().

pub fn input_data_config(&self) -> Option<&DocumentClassifierInputDataConfig>

Specifies the format and location of the input data for the job.

pub fn output_data_config(&self) -> Option<&DocumentClassifierOutputDataConfig>

Specifies the location for the output files from a custom classifier job. This parameter is required for a request that creates a native document model.

pub fn client_request_token(&self) -> Option<&str>

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

pub fn language_code(&self) -> Option<&LanguageCode>

The language of the input documents. You can specify any of the languages supported by Amazon Comprehend. All documents must be in the same language.

pub fn volume_kms_key_id(&self) -> Option<&str>

ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

pub fn vpc_config(&self) -> Option<&VpcConfig>

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC.

pub fn mode(&self) -> Option<&DocumentClassifierMode>

Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class mode, which identifies one and only one class for each document, or multi-label mode, which identifies one or more labels for each document. In multi-label mode, multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).

pub fn model_kms_key_id(&self) -> Option<&str>

ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

pub fn model_policy(&self) -> Option<&str>

The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another Amazon Web Services account to import your custom model.

Provide your policy as a JSON body that you enter as a UTF-8 encoded string without line breaks. To provide valid JSON, enclose the attribute names and values in double quotes. If the JSON body is also enclosed in double quotes, then you must escape the double quotes that are inside the policy:

"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"

To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:

'{"attribute": "value", "attribute": ["value"]}'

impl CreateDocumentClassifierInput

pub fn builder() -> CreateDocumentClassifierInputBuilder

Creates a new builder-style object to manufacture CreateDocumentClassifierInput.

Trait Implementations

impl Clone for CreateDocumentClassifierInput

fn clone(&self) -> CreateDocumentClassifierInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for CreateDocumentClassifierInput

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

Formats the value using the given formatter.

impl PartialEq for CreateDocumentClassifierInput

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

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

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

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

impl StructuralPartialEq for CreateDocumentClassifierInput