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Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
Namespace: Amazon.SageMaker.Model
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public class S3DataSource
The S3DataSource type exposes the following members
Name | Description | |
---|---|---|
S3DataSource() |
Name | Type | Description | |
---|---|---|---|
AttributeNames | System.Collections.Generic.List<System.String> |
Gets and sets the property AttributeNames. A list of one or more attribute names to use that are found in a specified augmented manifest file. |
|
InstanceGroupNames | System.Collections.Generic.List<System.String> |
Gets and sets the property InstanceGroupNames. A list of names of instance groups that get data from the S3 data source. |
|
S3DataDistributionType | Amazon.SageMaker.S3DataDistribution |
Gets and sets the property S3DataDistributionType.
If you want SageMaker to replicate the entire dataset on each ML compute instance
that is launched for model training, specify
If you want SageMaker to replicate a subset of data on each ML compute instance that
is launched for model training, specify Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might
choose |
|
S3DataType | Amazon.SageMaker.S3DataType |
Gets and sets the property S3DataType.
If you choose
If you choose
If you choose |
|
S3Uri | System.String |
Gets and sets the property S3Uri.
Depending on the value specified for the
Your input bucket must be located in same Amazon Web Services region as your training job. |
.NET Core App:
Supported in: 3.1
.NET Standard:
Supported in: 2.0
.NET Framework:
Supported in: 4.5, 4.0, 3.5