/AWS1/CL_SGMAUTOMLS3DATASOURCE

Describes the Amazon S3 data source.

CONSTRUCTOR

IMPORTING

Required arguments:

iv_s3datatype TYPE /AWS1/SGMAUTOMLS3DATATYPE /AWS1/SGMAUTOMLS3DATATYPE

The data type.

• If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker AI uses all objects that match the specified key name prefix for model training.

  The S3Prefix should have the following format:

  s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE

• If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.

  A ManifestFile should have the format shown below:

  [ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},

  "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",

  "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",

  ... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]

• If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).

  Here is a minimal, single-record example of an AugmentedManifestFile:

  {"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",

  "label-metadata": {"class-name": "cat" }

  For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.

iv_s3uri TYPE /AWS1/SGMS3URI /AWS1/SGMS3URI

The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.

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Queryable Attributes

S3DataType

The data type.

• If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker AI uses all objects that match the specified key name prefix for model training.

  The S3Prefix should have the following format:

  s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE

• If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.

  A ManifestFile should have the format shown below:

  [ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},

  "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",

  "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",

  ... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]

• If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).

  Here is a minimal, single-record example of an AugmentedManifestFile:

  {"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",

  "label-metadata": {"class-name": "cat" }

  For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.

Accessible with the following methods

Method	Description
GET_S3DATATYPE()	Getter for S3DATATYPE, with configurable default
ASK_S3DATATYPE()	Getter for S3DATATYPE w/ exceptions if field has no value
HAS_S3DATATYPE()	Determine if S3DATATYPE has a value

S3Uri

The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.

Accessible with the following methods

Method	Description
GET_S3URI()	Getter for S3URI, with configurable default
ASK_S3URI()	Getter for S3URI w/ exceptions if field has no value
HAS_S3URI()	Determine if S3URI has a value