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AWS Cloud Control v1.28.0 published on Monday, May 19, 2025 by Pulumi
pulumi/pulumi-aws-native

aws-native.comprehend.DocumentClassifier

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We recommend new projects start with resources from the AWS provider.

AWS Cloud Control v1.28.0 published on Monday, May 19, 2025 by Pulumi
pulumi/pulumi-aws-native

    Document Classifier enables training document classifier models.

    Create DocumentClassifier Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new DocumentClassifier(name: string, args: DocumentClassifierArgs, opts?: CustomResourceOptions);
    @overload
def DocumentClassifier(resource_name: str,
                       args: DocumentClassifierArgs,
                       opts: Optional[ResourceOptions] = None)

@overload
def DocumentClassifier(resource_name: str,
                       opts: Optional[ResourceOptions] = None,
                       data_access_role_arn: Optional[str] = None,
                       input_data_config: Optional[DocumentClassifierInputDataConfigArgs] = None,
                       language_code: Optional[DocumentClassifierLanguageCode] = None,
                       document_classifier_name: Optional[str] = None,
                       mode: Optional[DocumentClassifierMode] = None,
                       model_kms_key_id: Optional[str] = None,
                       model_policy: Optional[str] = None,
                       output_data_config: Optional[DocumentClassifierOutputDataConfigArgs] = None,
                       tags: Optional[Sequence[_root_inputs.TagArgs]] = None,
                       version_name: Optional[str] = None,
                       volume_kms_key_id: Optional[str] = None,
                       vpc_config: Optional[DocumentClassifierVpcConfigArgs] = None)
    func NewDocumentClassifier(ctx *Context, name string, args DocumentClassifierArgs, opts ...ResourceOption) (*DocumentClassifier, error)
    public DocumentClassifier(string name, DocumentClassifierArgs args, CustomResourceOptions? opts = null)
    public DocumentClassifier(String name, DocumentClassifierArgs args)
public DocumentClassifier(String name, DocumentClassifierArgs args, CustomResourceOptions options)

    type: aws-native:comprehend:DocumentClassifier
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args DocumentClassifierArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args DocumentClassifierArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args DocumentClassifierArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args DocumentClassifierArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args DocumentClassifierArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    DocumentClassifier Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The DocumentClassifier resource accepts the following input properties:

    DataAccessRoleArn string
    The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
    InputDataConfig Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierInputDataConfig
    Specifies the format and location of the input data for the job.
    LanguageCode Pulumi.AwsNative.Comprehend.DocumentClassifierLanguageCode
    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.
    DocumentClassifierName string
    The name of the document classifier.
    Mode Pulumi.AwsNative.Comprehend.DocumentClassifierMode
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    ModelKmsKeyId string
    ID for the AWS 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"
    ModelPolicy string

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    OutputDataConfig Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierOutputDataConfig
    Provides output results configuration parameters for custom classifier jobs.
    Tags List<Pulumi.AwsNative.Inputs.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.
    VersionName 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 AWS account / AWS Region .
    VolumeKmsKeyId string
    ID for the AWS 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"
    VpcConfig Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierVpcConfig
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .
    DataAccessRoleArn string
    The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
    InputDataConfig DocumentClassifierInputDataConfigArgs
    Specifies the format and location of the input data for the job.
    LanguageCode DocumentClassifierLanguageCode
    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.
    DocumentClassifierName string
    The name of the document classifier.
    Mode DocumentClassifierMode
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    ModelKmsKeyId string
    ID for the AWS 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"
    ModelPolicy string

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    OutputDataConfig DocumentClassifierOutputDataConfigArgs
    Provides output results configuration parameters for custom classifier jobs.
    Tags TagArgs
    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.
    VersionName 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 AWS account / AWS Region .
    VolumeKmsKeyId string
    ID for the AWS 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"
    VpcConfig DocumentClassifierVpcConfigArgs
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .
    dataAccessRoleArn String
    The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
    inputDataConfig DocumentClassifierInputDataConfig
    Specifies the format and location of the input data for the job.
    languageCode DocumentClassifierLanguageCode
    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.
    documentClassifierName String
    The name of the document classifier.
    mode DocumentClassifierMode
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    modelKmsKeyId String
    ID for the AWS 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"
    modelPolicy String

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    outputDataConfig DocumentClassifierOutputDataConfig
    Provides output results configuration parameters for custom classifier jobs.
    tags List<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.
    versionName 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 AWS account / AWS Region .
    volumeKmsKeyId String
    ID for the AWS 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"
    vpcConfig DocumentClassifierVpcConfig
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .
    dataAccessRoleArn string
    The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
    inputDataConfig DocumentClassifierInputDataConfig
    Specifies the format and location of the input data for the job.
    languageCode DocumentClassifierLanguageCode
    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.
    documentClassifierName string
    The name of the document classifier.
    mode DocumentClassifierMode
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    modelKmsKeyId string
    ID for the AWS 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"
    modelPolicy string

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    outputDataConfig DocumentClassifierOutputDataConfig
    Provides output results configuration parameters for custom classifier jobs.
    tags 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.
    versionName 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 AWS account / AWS Region .
    volumeKmsKeyId string
    ID for the AWS 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"
    vpcConfig DocumentClassifierVpcConfig
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .
    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 DocumentClassifierInputDataConfigArgs
    Specifies the format and location of the input data for the job.
    language_code DocumentClassifierLanguageCode
    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.
    document_classifier_name str
    The name of the document classifier.
    mode DocumentClassifierMode
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    model_kms_key_id str
    ID for the AWS 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 str

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    output_data_config DocumentClassifierOutputDataConfigArgs
    Provides output results configuration parameters for custom classifier jobs.
    tags Sequence[TagArgs]
    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.
    version_name 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 AWS account / AWS Region .
    volume_kms_key_id str
    ID for the AWS 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 DocumentClassifierVpcConfigArgs
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .
    dataAccessRoleArn String
    The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
    inputDataConfig Property Map
    Specifies the format and location of the input data for the job.
    languageCode "en" | "es" | "fr" | "it" | "de" | "pt"
    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.
    documentClassifierName String
    The name of the document classifier.
    mode "MULTI_CLASS" | "MULTI_LABEL"
    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).
    modelKmsKeyId String
    ID for the AWS 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"
    modelPolicy String

    The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another AWS 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"]}'

    outputDataConfig Property Map
    Provides output results configuration parameters for custom classifier jobs.
    tags List<Property Map>
    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.
    versionName 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 AWS account / AWS Region .
    volumeKmsKeyId String
    ID for the AWS 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"
    vpcConfig Property Map
    Configuration parameters for a private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC .

    Outputs

    All input properties are implicitly available as output properties. Additionally, the DocumentClassifier resource produces the following output properties:

    Arn string
    The Amazon Resource Name (ARN) of the document classifier.
    Id string
    The provider-assigned unique ID for this managed resource.
    Arn string
    The Amazon Resource Name (ARN) of the document classifier.
    Id string
    The provider-assigned unique ID for this managed resource.
    arn String
    The Amazon Resource Name (ARN) of the document classifier.
    id String
    The provider-assigned unique ID for this managed resource.
    arn string
    The Amazon Resource Name (ARN) of the document classifier.
    id string
    The provider-assigned unique ID for this managed resource.
    arn str
    The Amazon Resource Name (ARN) of the document classifier.
    id str
    The provider-assigned unique ID for this managed resource.
    arn String
    The Amazon Resource Name (ARN) of the document classifier.
    id String
    The provider-assigned unique ID for this managed resource.

    Supporting Types

    DocumentClassifierAugmentedManifestsListItem, DocumentClassifierAugmentedManifestsListItemArgs

    AttributeNames List<string>

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    S3Uri string
    The Amazon S3 location of the augmented manifest file.
    Split Pulumi.AwsNative.Comprehend.DocumentClassifierAugmentedManifestsListItemSplit

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    AttributeNames []string

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    S3Uri string
    The Amazon S3 location of the augmented manifest file.
    Split DocumentClassifierAugmentedManifestsListItemSplit

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    attributeNames List<String>

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    s3Uri String
    The Amazon S3 location of the augmented manifest file.
    split DocumentClassifierAugmentedManifestsListItemSplit

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    attributeNames string[]

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    s3Uri string
    The Amazon S3 location of the augmented manifest file.
    split DocumentClassifierAugmentedManifestsListItemSplit

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    attribute_names Sequence[str]

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    s3_uri str
    The Amazon S3 location of the augmented manifest file.
    split DocumentClassifierAugmentedManifestsListItemSplit

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    attributeNames List<String>

    The JSON attribute that contains the annotations for your training documents. The number of attribute names that you specify depends on whether your augmented manifest file is the output of a single labeling job or a chained labeling job.

    If your file is the output of a single labeling job, specify the LabelAttributeName key that was used when the job was created in Ground Truth.

    If your file is the output of a chained labeling job, specify the LabelAttributeName key for one or more jobs in the chain. Each LabelAttributeName key provides the annotations from an individual job.

    s3Uri String
    The Amazon S3 location of the augmented manifest file.
    split "TRAIN" | "TEST"

    The purpose of the data you've provided in the augmented manifest. You can either train or test this data. If you don't specify, the default is train.

    TRAIN - all of the documents in the manifest will be used for training. If no test documents are provided, Amazon Comprehend will automatically reserve a portion of the training documents for testing.

    TEST - all of the documents in the manifest will be used for testing.

    DocumentClassifierAugmentedManifestsListItemSplit, DocumentClassifierAugmentedManifestsListItemSplitArgs

    Train
    TRAIN
    Test
    TEST
    DocumentClassifierAugmentedManifestsListItemSplitTrain
    TRAIN
    DocumentClassifierAugmentedManifestsListItemSplitTest
    TEST
    Train
    TRAIN
    Test
    TEST
    Train
    TRAIN
    Test
    TEST
    TRAIN
    TRAIN
    TEST
    TEST
    "TRAIN"
    TRAIN
    "TEST"
    TEST

    DocumentClassifierDocumentReaderConfig, DocumentClassifierDocumentReaderConfigArgs

    DocumentReadAction Pulumi.AwsNative.Comprehend.DocumentClassifierDocumentReaderConfigDocumentReadAction
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    DocumentReadMode Pulumi.AwsNative.Comprehend.DocumentClassifierDocumentReaderConfigDocumentReadMode
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    FeatureTypes List<Pulumi.AwsNative.Comprehend.DocumentClassifierDocumentReaderConfigFeatureTypesItem>
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.
    DocumentReadAction DocumentClassifierDocumentReaderConfigDocumentReadAction
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    DocumentReadMode DocumentClassifierDocumentReaderConfigDocumentReadMode
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    FeatureTypes []DocumentClassifierDocumentReaderConfigFeatureTypesItem
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.
    documentReadAction DocumentClassifierDocumentReaderConfigDocumentReadAction
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    documentReadMode DocumentClassifierDocumentReaderConfigDocumentReadMode
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    featureTypes List<DocumentClassifierDocumentReaderConfigFeatureTypesItem>
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.
    documentReadAction DocumentClassifierDocumentReaderConfigDocumentReadAction
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    documentReadMode DocumentClassifierDocumentReaderConfigDocumentReadMode
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    featureTypes DocumentClassifierDocumentReaderConfigFeatureTypesItem[]
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.
    document_read_action DocumentClassifierDocumentReaderConfigDocumentReadAction
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    document_read_mode DocumentClassifierDocumentReaderConfigDocumentReadMode
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    feature_types Sequence[DocumentClassifierDocumentReaderConfigFeatureTypesItem]
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.
    documentReadAction "TEXTRACT_DETECT_DOCUMENT_TEXT" | "TEXTRACT_ANALYZE_DOCUMENT"
    This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:

    • TEXTRACT_DETECT_DOCUMENT_TEXT - The Amazon Comprehend service uses the DetectDocumentText API operation.
    • TEXTRACT_ANALYZE_DOCUMENT - The Amazon Comprehend service uses the AnalyzeDocument API operation.
    documentReadMode "SERVICE_DEFAULT" | "FORCE_DOCUMENT_READ_ACTION"
    Determines the text extraction actions for PDF files. Enter one of the following values:

    • SERVICE_DEFAULT - use the Amazon Comprehend service defaults for PDF files.
    • FORCE_DOCUMENT_READ_ACTION - Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
    featureTypes List<"TABLES" | "FORMS">
    Specifies the type of Amazon Textract features to apply. If you chose TEXTRACT_ANALYZE_DOCUMENT as the read action, you must specify one or both of the following values:

    • TABLES - Returns additional information about any tables that are detected in the input document.
    • FORMS - Returns additional information about any forms that are detected in the input document.

    DocumentClassifierDocumentReaderConfigDocumentReadAction, DocumentClassifierDocumentReaderConfigDocumentReadActionArgs

    TextractDetectDocumentText
    TEXTRACT_DETECT_DOCUMENT_TEXT
    TextractAnalyzeDocument
    TEXTRACT_ANALYZE_DOCUMENT
    DocumentClassifierDocumentReaderConfigDocumentReadActionTextractDetectDocumentText
    TEXTRACT_DETECT_DOCUMENT_TEXT
    DocumentClassifierDocumentReaderConfigDocumentReadActionTextractAnalyzeDocument
    TEXTRACT_ANALYZE_DOCUMENT
    TextractDetectDocumentText
    TEXTRACT_DETECT_DOCUMENT_TEXT
    TextractAnalyzeDocument
    TEXTRACT_ANALYZE_DOCUMENT
    TextractDetectDocumentText
    TEXTRACT_DETECT_DOCUMENT_TEXT
    TextractAnalyzeDocument
    TEXTRACT_ANALYZE_DOCUMENT
    TEXTRACT_DETECT_DOCUMENT_TEXT
    TEXTRACT_DETECT_DOCUMENT_TEXT
    TEXTRACT_ANALYZE_DOCUMENT
    TEXTRACT_ANALYZE_DOCUMENT
    "TEXTRACT_DETECT_DOCUMENT_TEXT"
    TEXTRACT_DETECT_DOCUMENT_TEXT
    "TEXTRACT_ANALYZE_DOCUMENT"
    TEXTRACT_ANALYZE_DOCUMENT

    DocumentClassifierDocumentReaderConfigDocumentReadMode, DocumentClassifierDocumentReaderConfigDocumentReadModeArgs

    ServiceDefault
    SERVICE_DEFAULT
    ForceDocumentReadAction
    FORCE_DOCUMENT_READ_ACTION
    DocumentClassifierDocumentReaderConfigDocumentReadModeServiceDefault
    SERVICE_DEFAULT
    DocumentClassifierDocumentReaderConfigDocumentReadModeForceDocumentReadAction
    FORCE_DOCUMENT_READ_ACTION
    ServiceDefault
    SERVICE_DEFAULT
    ForceDocumentReadAction
    FORCE_DOCUMENT_READ_ACTION
    ServiceDefault
    SERVICE_DEFAULT
    ForceDocumentReadAction
    FORCE_DOCUMENT_READ_ACTION
    SERVICE_DEFAULT
    SERVICE_DEFAULT
    FORCE_DOCUMENT_READ_ACTION
    FORCE_DOCUMENT_READ_ACTION
    "SERVICE_DEFAULT"
    SERVICE_DEFAULT
    "FORCE_DOCUMENT_READ_ACTION"
    FORCE_DOCUMENT_READ_ACTION

    DocumentClassifierDocumentReaderConfigFeatureTypesItem, DocumentClassifierDocumentReaderConfigFeatureTypesItemArgs

    Tables
    TABLES
    Forms
    FORMS
    DocumentClassifierDocumentReaderConfigFeatureTypesItemTables
    TABLES
    DocumentClassifierDocumentReaderConfigFeatureTypesItemForms
    FORMS
    Tables
    TABLES
    Forms
    FORMS
    Tables
    TABLES
    Forms
    FORMS
    TABLES
    TABLES
    FORMS
    FORMS
    "TABLES"
    TABLES
    "FORMS"
    FORMS

    DocumentClassifierDocuments, DocumentClassifierDocumentsArgs

    S3Uri string
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    TestS3Uri string
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.
    S3Uri string
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    TestS3Uri string
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.
    s3Uri String
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    testS3Uri String
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.
    s3Uri string
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    testS3Uri string
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.
    s3_uri str
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    test_s3_uri str
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.
    s3Uri String
    The S3 URI location of the training documents specified in the S3Uri CSV file.
    testS3Uri String
    The S3 URI location of the test documents included in the TestS3Uri CSV file. This field is not required if you do not specify a test CSV file.

    DocumentClassifierInputDataConfig, DocumentClassifierInputDataConfigArgs

    AugmentedManifests List<Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierAugmentedManifestsListItem>

    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 .

    DataFormat Pulumi.AwsNative.Comprehend.DocumentClassifierInputDataConfigDataFormat

    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.

    DocumentReaderConfig Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierDocumentReaderConfig
    DocumentType Pulumi.AwsNative.Comprehend.DocumentClassifierInputDataConfigDocumentType
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    Documents Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierDocuments
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    LabelDelimiter string
    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.
    S3Uri string

    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 .

    TestS3Uri string
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.
    AugmentedManifests []DocumentClassifierAugmentedManifestsListItem

    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 .

    DataFormat DocumentClassifierInputDataConfigDataFormat

    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.

    DocumentReaderConfig DocumentClassifierDocumentReaderConfig
    DocumentType DocumentClassifierInputDataConfigDocumentType
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    Documents DocumentClassifierDocuments
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    LabelDelimiter string
    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.
    S3Uri string

    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 .

    TestS3Uri string
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.
    augmentedManifests List<DocumentClassifierAugmentedManifestsListItem>

    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 .

    dataFormat DocumentClassifierInputDataConfigDataFormat

    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.

    documentReaderConfig DocumentClassifierDocumentReaderConfig
    documentType DocumentClassifierInputDataConfigDocumentType
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    documents DocumentClassifierDocuments
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    labelDelimiter String
    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.
    s3Uri String

    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 .

    testS3Uri String
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.
    augmentedManifests DocumentClassifierAugmentedManifestsListItem[]

    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 .

    dataFormat DocumentClassifierInputDataConfigDataFormat

    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.

    documentReaderConfig DocumentClassifierDocumentReaderConfig
    documentType DocumentClassifierInputDataConfigDocumentType
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    documents DocumentClassifierDocuments
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    labelDelimiter string
    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.
    s3Uri string

    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 .

    testS3Uri string
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.
    augmented_manifests Sequence[DocumentClassifierAugmentedManifestsListItem]

    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 .

    data_format DocumentClassifierInputDataConfigDataFormat

    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.

    document_reader_config DocumentClassifierDocumentReaderConfig
    document_type DocumentClassifierInputDataConfigDocumentType
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    documents DocumentClassifierDocuments
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    label_delimiter str
    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.
    s3_uri str

    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 .

    test_s3_uri str
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.
    augmentedManifests List<Property Map>

    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 .

    dataFormat "COMPREHEND_CSV" | "AUGMENTED_MANIFEST"

    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.

    documentReaderConfig Property Map
    documentType "PLAIN_TEXT_DOCUMENT" | "SEMI_STRUCTURED_DOCUMENT"
    The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.
    documents Property Map
    The S3 location of the training documents. This parameter is required in a request to create a native document model.
    labelDelimiter String
    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.
    s3Uri String

    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 .

    testS3Uri String
    This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same AWS Region as the API endpoint that you are calling.

    DocumentClassifierInputDataConfigDataFormat, DocumentClassifierInputDataConfigDataFormatArgs

    ComprehendCsv
    COMPREHEND_CSV
    AugmentedManifest
    AUGMENTED_MANIFEST
    DocumentClassifierInputDataConfigDataFormatComprehendCsv
    COMPREHEND_CSV
    DocumentClassifierInputDataConfigDataFormatAugmentedManifest
    AUGMENTED_MANIFEST
    ComprehendCsv
    COMPREHEND_CSV
    AugmentedManifest
    AUGMENTED_MANIFEST
    ComprehendCsv
    COMPREHEND_CSV
    AugmentedManifest
    AUGMENTED_MANIFEST
    COMPREHEND_CSV
    COMPREHEND_CSV
    AUGMENTED_MANIFEST
    AUGMENTED_MANIFEST
    "COMPREHEND_CSV"
    COMPREHEND_CSV
    "AUGMENTED_MANIFEST"
    AUGMENTED_MANIFEST

    DocumentClassifierInputDataConfigDocumentType, DocumentClassifierInputDataConfigDocumentTypeArgs

    PlainTextDocument
    PLAIN_TEXT_DOCUMENT
    SemiStructuredDocument
    SEMI_STRUCTURED_DOCUMENT
    DocumentClassifierInputDataConfigDocumentTypePlainTextDocument
    PLAIN_TEXT_DOCUMENT
    DocumentClassifierInputDataConfigDocumentTypeSemiStructuredDocument
    SEMI_STRUCTURED_DOCUMENT
    PlainTextDocument
    PLAIN_TEXT_DOCUMENT
    SemiStructuredDocument
    SEMI_STRUCTURED_DOCUMENT
    PlainTextDocument
    PLAIN_TEXT_DOCUMENT
    SemiStructuredDocument
    SEMI_STRUCTURED_DOCUMENT
    PLAIN_TEXT_DOCUMENT
    PLAIN_TEXT_DOCUMENT
    SEMI_STRUCTURED_DOCUMENT
    SEMI_STRUCTURED_DOCUMENT
    "PLAIN_TEXT_DOCUMENT"
    PLAIN_TEXT_DOCUMENT
    "SEMI_STRUCTURED_DOCUMENT"
    SEMI_STRUCTURED_DOCUMENT

    DocumentClassifierLanguageCode, DocumentClassifierLanguageCodeArgs

    En
    en
    Es
    es
    Fr
    fr
    It
    it
    De
    de
    Pt
    pt
    DocumentClassifierLanguageCodeEn
    en
    DocumentClassifierLanguageCodeEs
    es
    DocumentClassifierLanguageCodeFr
    fr
    DocumentClassifierLanguageCodeIt
    it
    DocumentClassifierLanguageCodeDe
    de
    DocumentClassifierLanguageCodePt
    pt
    En
    en
    Es
    es
    Fr
    fr
    It
    it
    De
    de
    Pt
    pt
    En
    en
    Es
    es
    Fr
    fr
    It
    it
    De
    de
    Pt
    pt
    EN
    en
    ES
    es
    FR
    fr
    IT
    it
    DE
    de
    PT
    pt
    "en"
    en
    "es"
    es
    "fr"
    fr
    "it"
    it
    "de"
    de
    "pt"
    pt

    DocumentClassifierMode, DocumentClassifierModeArgs

    MultiClass
    MULTI_CLASS
    MultiLabel
    MULTI_LABEL
    DocumentClassifierModeMultiClass
    MULTI_CLASS
    DocumentClassifierModeMultiLabel
    MULTI_LABEL
    MultiClass
    MULTI_CLASS
    MultiLabel
    MULTI_LABEL
    MultiClass
    MULTI_CLASS
    MultiLabel
    MULTI_LABEL
    MULTI_CLASS
    MULTI_CLASS
    MULTI_LABEL
    MULTI_LABEL
    "MULTI_CLASS"
    MULTI_CLASS
    "MULTI_LABEL"
    MULTI_LABEL

    DocumentClassifierOutputDataConfig, DocumentClassifierOutputDataConfigArgs

    KmsKeyId string
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    S3Uri string

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    KmsKeyId string
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    S3Uri string

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    kmsKeyId String
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    s3Uri String

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    kmsKeyId string
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    s3Uri string

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    kms_key_id str
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    s3_uri str

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    kmsKeyId String
    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one 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"
    • KMS Key Alias: "alias/ExampleAlias"
    • ARN of a KMS Key Alias: "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
    s3Uri String

    When you use the OutputDataConfig object while creating a custom classifier, you specify the Amazon S3 location where you want to write the confusion matrix and other output files. The URI must be in the same Region as the API endpoint that you are calling. The location is used as the prefix for the actual location of this output file.

    When the custom classifier job is finished, the service creates the output file in a directory specific to the job. The S3Uri field contains the location of the output file, called output.tar.gz . It is a compressed archive that contains the confusion matrix.

    DocumentClassifierVpcConfig, DocumentClassifierVpcConfigArgs

    SecurityGroupIds List<string>
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    Subnets List<string>
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .
    SecurityGroupIds []string
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    Subnets []string
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .
    securityGroupIds List<String>
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    subnets List<String>
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .
    securityGroupIds string[]
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    subnets string[]
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .
    security_group_ids Sequence[str]
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    subnets Sequence[str]
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .
    securityGroupIds List<String>
    The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by "sg-", for instance: "sg-03b388029b0a285ea". For more information, see Security Groups for your VPC .
    subnets List<String>
    The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s Region. This ID number is preceded by "subnet-", for instance: "subnet-04ccf456919e69055". For more information, see VPCs and Subnets .

    Tag, TagArgs

    Key string
    The key name of the tag
    Value string
    The value of the tag
    Key string
    The key name of the tag
    Value string
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag
    key string
    The key name of the tag
    value string
    The value of the tag
    key str
    The key name of the tag
    value str
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag

    Package Details

    Repository
    AWS Native pulumi/pulumi-aws-native
    License
    Apache-2.0
    aws-native logo

    We recommend new projects start with resources from the AWS provider.

    AWS Cloud Control v1.28.0 published on Monday, May 19, 2025 by Pulumi
    pulumi/pulumi-aws-native