CfnEntityRecognizerProps

class aws_cdk.aws_comprehend.CfnEntityRecognizerProps(*, data_access_role_arn, input_data_config, language_code, recognizer_name, model_kms_key_id=None, model_policy=None, tags=None, version_name=None, volume_kms_key_id=None, vpc_config=None)

Bases: object

Properties for defining a CfnEntityRecognizer.

Parameters:

data_access_role_arn (str) – The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
input_data_config (Union[IResolvable, EntityRecognizerInputDataConfigProperty, Dict[str, Any]]) – Specifies the format and location of the input data for an entity recognizer.
language_code (str) – The language of the input documents. All documents must be in the same language.
recognizer_name (str) – The name given to the entity recognizer.
model_kms_key_id (Optional[str]) – ID for the AWS KMS key that Amazon Comprehend uses to encrypt trained custom models.
model_policy (Optional[str]) – The JSON resource-based policy to attach to your custom entity recognizer model.
tags (Optional[Sequence[Union[CfnTag, Dict[str, Any]]]]) – Tags to associate with the entity recognizer.
version_name (Optional[str]) – The version name given to the entity recognizer.
volume_kms_key_id (Optional[str]) – ID for the AWS KMS key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s).
vpc_config (Union[IResolvable, VpcConfigProperty, Dict[str, Any], None]) – Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for the job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-comprehend-entityrecognizer.html

ExampleMetadata:

fixture=_generated

Example:

from aws_cdk import CfnTag
# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_comprehend as comprehend

cfn_entity_recognizer_props = comprehend.CfnEntityRecognizerProps(
    data_access_role_arn="dataAccessRoleArn",
    input_data_config=comprehend.CfnEntityRecognizer.EntityRecognizerInputDataConfigProperty(
        entity_types=[comprehend.CfnEntityRecognizer.EntityTypesListItemProperty(
            type="type"
        )],

        # the properties below are optional
        annotations=comprehend.CfnEntityRecognizer.EntityRecognizerAnnotationsProperty(
            s3_uri="s3Uri",

            # the properties below are optional
            test_s3_uri="testS3Uri"
        ),
        augmented_manifests=[comprehend.CfnEntityRecognizer.AugmentedManifestsListItemProperty(
            attribute_names=["attributeNames"],
            s3_uri="s3Uri",

            # the properties below are optional
            annotation_data_s3_uri="annotationDataS3Uri",
            document_type="documentType",
            source_documents_s3_uri="sourceDocumentsS3Uri",
            split="split"
        )],
        data_format="dataFormat",
        documents=comprehend.CfnEntityRecognizer.EntityRecognizerDocumentsProperty(
            s3_uri="s3Uri",

            # the properties below are optional
            input_format="inputFormat",
            test_s3_uri="testS3Uri"
        ),
        entity_list=comprehend.CfnEntityRecognizer.EntityRecognizerEntityListProperty(
            s3_uri="s3Uri"
        )
    ),
    language_code="languageCode",
    recognizer_name="recognizerName",

    # the properties below are optional
    model_kms_key_id="modelKmsKeyId",
    model_policy="modelPolicy",
    tags=[CfnTag(
        key="key",
        value="value"
    )],
    version_name="versionName",
    volume_kms_key_id="volumeKmsKeyId",
    vpc_config=comprehend.CfnEntityRecognizer.VpcConfigProperty(
        security_group_ids=["securityGroupIds"],
        subnets=["subnets"]
    )
)