Interface CfnModelPackage.TransformInputProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnModelPackage.TransformInputProperty.Jsii$Proxy
- Enclosing class:
CfnModelPackage
Example:
// The code below shows an example of how to instantiate this type. // The values are placeholders you should change. import software.amazon.awscdk.services.sagemaker.*; TransformInputProperty transformInputProperty = TransformInputProperty.builder() .dataSource(DataSourceProperty.builder() .s3DataSource(S3DataSourceProperty.builder() .s3DataType("s3DataType") .s3Uri("s3Uri") .build()) .build()) // the properties below are optional .compressionType("compressionType") .contentType("contentType") .splitType("splitType") .build();
- See Also:
-
Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic final class
A builder forCfnModelPackage.TransformInputProperty
static final class
An implementation forCfnModelPackage.TransformInputProperty
-
Method Summary
Modifier and TypeMethodDescriptionbuilder()
default String
If your transform data is compressed, specify the compression type.default String
The multipurpose internet mail extension (MIME) type of the data.Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.default String
The method to use to split the transform job's data files into smaller batches.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
-
Method Details
-
getDataSource
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.- See Also:
-
getCompressionType
If your transform data is compressed, specify the compression type.Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is
None
.- See Also:
-
getContentType
The multipurpose internet mail extension (MIME) type of the data.Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
- See Also:
-
getSplitType
The method to use to split the transform job's data files into smaller batches.Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for
SplitType
isNone
, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter toLine
to split records on a newline character boundary.SplitType
also supports a number of record-oriented binary data formats. Currently, the supported record formats are:- RecordIO
- TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the
BatchStrategy
andMaxPayloadInMB
parameters. When the value ofBatchStrategy
isMultiRecord
, Amazon SageMaker sends the maximum number of records in each request, up to theMaxPayloadInMB
limit. If the value ofBatchStrategy
isSingleRecord
, Amazon SageMaker sends individual records in each request.Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of
BatchStrategy
is set toSingleRecord
. Padding is not removed if the value ofBatchStrategy
is set toMultiRecord
.For more information about
RecordIO
, see Create a Dataset Using RecordIO in the MXNet documentation. For more information aboutTFRecord
, see Consuming TFRecord data in the TensorFlow documentation.- See Also:
-
builder
-