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AWS Cloud Control v1.27.0 published on Monday, Apr 14, 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 v1.27.0 published on Monday, Apr 14, 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 This property is required. string
The unique name of the resource.
args This property is required. DocumentClassifierArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. 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 This property is required. string
The unique name of the resource.
args This property is required. DocumentClassifierArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. DocumentClassifierArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. 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 This property is required. string
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
InputDataConfig This property is required. Pulumi.AwsNative.Comprehend.Inputs.DocumentClassifierInputDataConfig
Specifies the format and location of the input data for the job.
LanguageCode This property is required. 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 This property is required. string
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
InputDataConfig This property is required. DocumentClassifierInputDataConfigArgs
Specifies the format and location of the input data for the job.
LanguageCode This property is required. 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 This property is required. String
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
inputDataConfig This property is required. DocumentClassifierInputDataConfig
Specifies the format and location of the input data for the job.
languageCode This property is required. 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 This property is required. string
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
inputDataConfig This property is required. DocumentClassifierInputDataConfig
Specifies the format and location of the input data for the job.
languageCode This property is required. 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 This property is required. str
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
input_data_config This property is required. DocumentClassifierInputDataConfigArgs
Specifies the format and location of the input data for the job.
language_code This property is required. 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 This property is required. String
The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.
inputDataConfig This property is required. Property Map
Specifies the format and location of the input data for the job.
languageCode This property is required. "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 This property is required. 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 This property is required. 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 This property is required. []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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. "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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. []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 This property is required. []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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. string
The key name of the tag
Value This property is required. string
The value of the tag
Key This property is required. string
The key name of the tag
Value This property is required. string
The value of the tag
key This property is required. String
The key name of the tag
value This property is required. String
The value of the tag
key This property is required. string
The key name of the tag
value This property is required. string
The value of the tag
key This property is required. str
The key name of the tag
value This property is required. str
The value of the tag
key This property is required. String
The key name of the tag
value This property is required. String
The value of the tag

Package Details

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

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

AWS Cloud Control v1.27.0 published on Monday, Apr 14, 2025 by Pulumi
pulumi/pulumi-aws-native