CfnEntityRecognizerPropsMixin
- class aws_cdk.cfn_property_mixins.aws_comprehend.CfnEntityRecognizerPropsMixin(props, *, strategy=None)
Bases:
MixinAn Amazon Comprehend custom entity recognizer: a trained model that identifies custom entity types in text, created via an asynchronous training job.
- See:
- CloudformationResource:
AWS::Comprehend::EntityRecognizer
- Mixin:
true
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend import aws_cdk as cdk # merge_strategy: cdk.IMergeStrategy cfn_entity_recognizer_props_mixin = comprehend.CfnEntityRecognizerPropsMixin(comprehend.CfnEntityRecognizerMixinProps( data_access_role_arn="dataAccessRoleArn", input_data_config=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerInputDataConfigProperty( annotations=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerAnnotationsProperty( s3_uri="s3Uri", test_s3_uri="testS3Uri" ), augmented_manifests=[comprehend.CfnEntityRecognizerPropsMixin.AugmentedManifestsListItemProperty( annotation_data_s3_uri="annotationDataS3Uri", attribute_names=["attributeNames"], document_type="documentType", s3_uri="s3Uri", source_documents_s3_uri="sourceDocumentsS3Uri", split="split" )], data_format="dataFormat", documents=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerDocumentsProperty( input_format="inputFormat", s3_uri="s3Uri", test_s3_uri="testS3Uri" ), entity_list=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerEntityListProperty( s3_uri="s3Uri" ), entity_types=[comprehend.CfnEntityRecognizerPropsMixin.EntityTypesListItemProperty( type="type" )] ), language_code="languageCode", model_kms_key_id="modelKmsKeyId", model_policy="modelPolicy", recognizer_name="recognizerName", tags=[cdk.CfnTag( key="key", value="value" )], version_name="versionName", volume_kms_key_id="volumeKmsKeyId", vpc_config=comprehend.CfnEntityRecognizerPropsMixin.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] ) ), strategy=merge_strategy )
Create a mixin to apply properties to
AWS::Comprehend::EntityRecognizer.- Parameters:
props (
Union[CfnEntityRecognizerMixinProps,Dict[str,Any]]) – L1 properties to apply.strategy (
Optional[IMergeStrategy]) – Strategy for merging nested properties. Default: - PropertyMergeStrategy.combine()
Methods
- apply_to(construct)
Apply the mixin properties to the construct.
- Parameters:
construct (
IConstruct)- Return type:
None
- supports(construct)
Check if this mixin supports the given construct.
- Parameters:
construct (
IConstruct)- Return type:
bool
Attributes
- CFN_PROPERTY_KEYS = ['dataAccessRoleArn', 'inputDataConfig', 'languageCode', 'modelKmsKeyId', 'modelPolicy', 'recognizerName', 'tags', 'versionName', 'volumeKmsKeyId', 'vpcConfig']
Static Methods
- classmethod is_mixin(x)
Checks if
xis a Mixin.- Parameters:
x (
Any) – Any object.- Return type:
bool- Returns:
true if
xis an object created from a class which extendsMixin.
AugmentedManifestsListItemProperty
- class CfnEntityRecognizerPropsMixin.AugmentedManifestsListItemProperty(*, annotation_data_s3_uri=None, attribute_names=None, document_type=None, s3_uri=None, source_documents_s3_uri=None, split=None)
Bases:
objectAn augmented manifest file that provides training data for your custom model.
- Parameters:
annotation_data_s3_uri (
Optional[str]) – The S3 prefix to the annotation files that are referred in the augmented manifest file.attribute_names (
Optional[Sequence[str]]) – The JSON attribute that contains the annotations for your training documents.document_type (
Optional[str]) – The type of augmented manifest.s3_uri (
Optional[str]) – The Amazon S3 location of the augmented manifest file.source_documents_s3_uri (
Optional[str]) – The S3 prefix to the source files (PDFs) that are referred to in the augmented manifest file.split (
Optional[str]) – The purpose of the data you’ve provided in the augmented manifest.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend augmented_manifests_list_item_property = comprehend.CfnEntityRecognizerPropsMixin.AugmentedManifestsListItemProperty( annotation_data_s3_uri="annotationDataS3Uri", attribute_names=["attributeNames"], document_type="documentType", s3_uri="s3Uri", source_documents_s3_uri="sourceDocumentsS3Uri", split="split" )
Attributes
- annotation_data_s3_uri
The S3 prefix to the annotation files that are referred in the augmented manifest file.
- attribute_names
The JSON attribute that contains the annotations for your training documents.
- document_type
The type of augmented manifest.
- s3_uri
The Amazon S3 location of the augmented manifest file.
- source_documents_s3_uri
The S3 prefix to the source files (PDFs) that are referred to in the augmented manifest file.
- split
The purpose of the data you’ve provided in the augmented manifest.
EntityRecognizerAnnotationsProperty
- class CfnEntityRecognizerPropsMixin.EntityRecognizerAnnotationsProperty(*, s3_uri=None, test_s3_uri=None)
Bases:
objectDescribes the annotations associated with an entity recognizer.
- Parameters:
s3_uri (
Optional[str]) – Specifies the Amazon S3 location where the annotations are located.test_s3_uri (
Optional[str]) – Specifies the Amazon S3 location where the test annotations are located.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend entity_recognizer_annotations_property = comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerAnnotationsProperty( s3_uri="s3Uri", test_s3_uri="testS3Uri" )
Attributes
- s3_uri
Specifies the Amazon S3 location where the annotations are located.
- test_s3_uri
Specifies the Amazon S3 location where the test annotations are located.
EntityRecognizerDocumentsProperty
- class CfnEntityRecognizerPropsMixin.EntityRecognizerDocumentsProperty(*, input_format=None, s3_uri=None, test_s3_uri=None)
Bases:
objectDescribes the training documents submitted with an entity recognizer.
- Parameters:
input_format (
Optional[str]) – Specifies how the text in an input file should be processed.s3_uri (
Optional[str]) – Specifies the Amazon S3 location where the training documents are located.test_s3_uri (
Optional[str]) – Specifies the Amazon S3 location where the test documents are located.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend entity_recognizer_documents_property = comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerDocumentsProperty( input_format="inputFormat", s3_uri="s3Uri", test_s3_uri="testS3Uri" )
Attributes
- input_format
Specifies how the text in an input file should be processed.
- s3_uri
Specifies the Amazon S3 location where the training documents are located.
- test_s3_uri
Specifies the Amazon S3 location where the test documents are located.
EntityRecognizerEntityListProperty
- class CfnEntityRecognizerPropsMixin.EntityRecognizerEntityListProperty(*, s3_uri=None)
Bases:
objectDescribes the entity list submitted with an entity recognizer.
- Parameters:
s3_uri (
Optional[str]) – Specifies the Amazon S3 location where the entity list is located.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend entity_recognizer_entity_list_property = comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerEntityListProperty( s3_uri="s3Uri" )
Attributes
- s3_uri
Specifies the Amazon S3 location where the entity list is located.
EntityRecognizerInputDataConfigProperty
- class CfnEntityRecognizerPropsMixin.EntityRecognizerInputDataConfigProperty(*, annotations=None, augmented_manifests=None, data_format=None, documents=None, entity_list=None, entity_types=None)
Bases:
objectSpecifies the format and location of the input data for an entity recognizer.
- Parameters:
annotations (
Union[IResolvable,EntityRecognizerAnnotationsProperty,Dict[str,Any],None]) – Describes the annotations associated with an entity recognizer.augmented_manifests (
Union[IResolvable,Sequence[Union[IResolvable,AugmentedManifestsListItemProperty,Dict[str,Any]]],None]) – A list of augmented manifest files that provide training data for a custom model.data_format (
Optional[str]) – The format of your training data.documents (
Union[IResolvable,EntityRecognizerDocumentsProperty,Dict[str,Any],None]) – Describes the training documents submitted with an entity recognizer.entity_list (
Union[IResolvable,EntityRecognizerEntityListProperty,Dict[str,Any],None]) – Describes the entity list submitted with an entity recognizer.entity_types (
Union[IResolvable,Sequence[Union[IResolvable,EntityTypesListItemProperty,Dict[str,Any]]],None]) – The entity types in the labeled training data.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend entity_recognizer_input_data_config_property = comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerInputDataConfigProperty( annotations=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerAnnotationsProperty( s3_uri="s3Uri", test_s3_uri="testS3Uri" ), augmented_manifests=[comprehend.CfnEntityRecognizerPropsMixin.AugmentedManifestsListItemProperty( annotation_data_s3_uri="annotationDataS3Uri", attribute_names=["attributeNames"], document_type="documentType", s3_uri="s3Uri", source_documents_s3_uri="sourceDocumentsS3Uri", split="split" )], data_format="dataFormat", documents=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerDocumentsProperty( input_format="inputFormat", s3_uri="s3Uri", test_s3_uri="testS3Uri" ), entity_list=comprehend.CfnEntityRecognizerPropsMixin.EntityRecognizerEntityListProperty( s3_uri="s3Uri" ), entity_types=[comprehend.CfnEntityRecognizerPropsMixin.EntityTypesListItemProperty( type="type" )] )
Attributes
- annotations
Describes the annotations associated with an entity recognizer.
- augmented_manifests
A list of augmented manifest files that provide training data for a custom model.
- data_format
The format of your training data.
- documents
Describes the training documents submitted with an entity recognizer.
- entity_list
Describes the entity list submitted with an entity recognizer.
- entity_types
The entity types in the labeled training data.
EntityTypesListItemProperty
- class CfnEntityRecognizerPropsMixin.EntityTypesListItemProperty(*, type=None)
Bases:
objectAn entity type within a labeled training dataset that Amazon Comprehend uses to train a custom entity recognizer.
- Parameters:
type (
Optional[str]) – An entity type within a labeled training dataset.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend entity_types_list_item_property = comprehend.CfnEntityRecognizerPropsMixin.EntityTypesListItemProperty( type="type" )
Attributes
- type
An entity type within a labeled training dataset.
VpcConfigProperty
- class CfnEntityRecognizerPropsMixin.VpcConfigProperty(*, security_group_ids=None, subnets=None)
Bases:
objectConfiguration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for the job.
- Parameters:
security_group_ids (
Optional[Sequence[str]]) – The ID number for a security group on an instance of your private VPC.subnets (
Optional[Sequence[str]]) – The ID for each subnet being used in your private VPC.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.cfn_property_mixins import aws_comprehend as comprehend vpc_config_property = comprehend.CfnEntityRecognizerPropsMixin.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] )
Attributes
- security_group_ids
The ID number for a security group on an instance of your private VPC.
- subnets
The ID for each subnet being used in your private VPC.