554 lines
33 KiB
C++
554 lines
33 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/sagemaker/SageMaker_EXPORTS.h>
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#include <aws/sagemaker/model/S3DataType.h>
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#include <aws/core/utils/memory/stl/AWSString.h>
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#include <aws/sagemaker/model/S3DataDistribution.h>
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#include <aws/core/utils/memory/stl/AWSVector.h>
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#include <utility>
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namespace Aws
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{
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namespace Utils
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{
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namespace Json
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{
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class JsonValue;
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class JsonView;
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} // namespace Json
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} // namespace Utils
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namespace SageMaker
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{
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namespace Model
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{
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/**
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* <p>Describes the S3 data source.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/S3DataSource">AWS
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* API Reference</a></p>
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*/
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class AWS_SAGEMAKER_API S3DataSource
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{
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public:
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S3DataSource();
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S3DataSource(Aws::Utils::Json::JsonView jsonValue);
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S3DataSource& operator=(Aws::Utils::Json::JsonView jsonValue);
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Aws::Utils::Json::JsonValue Jsonize() const;
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline const S3DataType& GetS3DataType() const{ return m_s3DataType; }
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline bool S3DataTypeHasBeenSet() const { return m_s3DataTypeHasBeenSet; }
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline void SetS3DataType(const S3DataType& value) { m_s3DataTypeHasBeenSet = true; m_s3DataType = value; }
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline void SetS3DataType(S3DataType&& value) { m_s3DataTypeHasBeenSet = true; m_s3DataType = std::move(value); }
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline S3DataSource& WithS3DataType(const S3DataType& value) { SetS3DataType(value); return *this;}
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/**
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* <p>If you choose <code>S3Prefix</code>, <code>S3Uri</code> identifies a key name
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* prefix. Amazon SageMaker uses all objects that match the specified key name
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* prefix for model training. </p> <p>If you choose <code>ManifestFile</code>,
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* <code>S3Uri</code> identifies an object that is a manifest file containing a
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* list of object keys that you want Amazon SageMaker to use for model training.
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* </p> <p>If you choose <code>AugmentedManifestFile</code>, S3Uri identifies an
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* object that is an augmented manifest file in JSON lines format. This file
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* contains the data you want to use for model training.
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* <code>AugmentedManifestFile</code> can only be used if the Channel's input mode
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* is <code>Pipe</code>.</p>
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*/
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inline S3DataSource& WithS3DataType(S3DataType&& value) { SetS3DataType(std::move(value)); return *this;}
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline const Aws::String& GetS3Uri() const{ return m_s3Uri; }
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline bool S3UriHasBeenSet() const { return m_s3UriHasBeenSet; }
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline void SetS3Uri(const Aws::String& value) { m_s3UriHasBeenSet = true; m_s3Uri = value; }
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline void SetS3Uri(Aws::String&& value) { m_s3UriHasBeenSet = true; m_s3Uri = std::move(value); }
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline void SetS3Uri(const char* value) { m_s3UriHasBeenSet = true; m_s3Uri.assign(value); }
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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|
* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
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* manifest format: </p> <p> <code>[ {"prefix":
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* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
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* "relative/path/to/custdata-1",</code> </p> <p> <code>
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* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
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* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
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* equivalent to the following <code>S3Uri</code> list:</p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
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* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
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* <p> <code>...</code> </p> <p>
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* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
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* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
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* the channel for this data source. The object that each <code>S3Uri</code> points
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* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
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* on your behalf. </p> </li> </ul>
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*/
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inline S3DataSource& WithS3Uri(const Aws::String& value) { SetS3Uri(value); return *this;}
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/**
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* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
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* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
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* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
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* </p> </li> <li> <p> A manifest might look like this:
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* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
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* object which is a JSON file consisting of an array of elements. The first
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* element is a prefix which is followed by one or more suffixes. SageMaker appends
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* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
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* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
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* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
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* from different S3 buckets.</p> <p> The following code example shows a valid
|
|
* manifest format: </p> <p> <code>[ {"prefix":
|
|
* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
|
|
* "relative/path/to/custdata-1",</code> </p> <p> <code>
|
|
* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
|
|
* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
|
|
* equivalent to the following <code>S3Uri</code> list:</p> <p>
|
|
* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
|
|
* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
|
|
* <p> <code>...</code> </p> <p>
|
|
* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
|
|
* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
|
|
* the channel for this data source. The object that each <code>S3Uri</code> points
|
|
* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
|
|
* on your behalf. </p> </li> </ul>
|
|
*/
|
|
inline S3DataSource& WithS3Uri(Aws::String&& value) { SetS3Uri(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>Depending on the value specified for the <code>S3DataType</code>, identifies
|
|
* either a key name prefix or a manifest. For example: </p> <ul> <li> <p> A key
|
|
* name prefix might look like this: <code>s3://bucketname/exampleprefix</code>
|
|
* </p> </li> <li> <p> A manifest might look like this:
|
|
* <code>s3://bucketname/example.manifest</code> </p> <p> A manifest is an S3
|
|
* object which is a JSON file consisting of an array of elements. The first
|
|
* element is a prefix which is followed by one or more suffixes. SageMaker appends
|
|
* the suffix elements to the prefix to get a full set of <code>S3Uri</code>. Note
|
|
* that the prefix must be a valid non-empty <code>S3Uri</code> that precludes
|
|
* users from specifying a manifest whose individual <code>S3Uri</code> is sourced
|
|
* from different S3 buckets.</p> <p> The following code example shows a valid
|
|
* manifest format: </p> <p> <code>[ {"prefix":
|
|
* "s3://customer_bucket/some/prefix/"},</code> </p> <p> <code>
|
|
* "relative/path/to/custdata-1",</code> </p> <p> <code>
|
|
* "relative/path/custdata-2",</code> </p> <p> <code> ...</code> </p> <p> <code>
|
|
* "relative/path/custdata-N"</code> </p> <p> <code>]</code> </p> <p> This JSON is
|
|
* equivalent to the following <code>S3Uri</code> list:</p> <p>
|
|
* <code>s3://customer_bucket/some/prefix/relative/path/to/custdata-1</code> </p>
|
|
* <p> <code>s3://customer_bucket/some/prefix/relative/path/custdata-2</code> </p>
|
|
* <p> <code>...</code> </p> <p>
|
|
* <code>s3://customer_bucket/some/prefix/relative/path/custdata-N</code> </p>
|
|
* <p>The complete set of <code>S3Uri</code> in this manifest is the input data for
|
|
* the channel for this data source. The object that each <code>S3Uri</code> points
|
|
* to must be readable by the IAM role that Amazon SageMaker uses to perform tasks
|
|
* on your behalf. </p> </li> </ul>
|
|
*/
|
|
inline S3DataSource& WithS3Uri(const char* value) { SetS3Uri(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline const S3DataDistribution& GetS3DataDistributionType() const{ return m_s3DataDistributionType; }
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline bool S3DataDistributionTypeHasBeenSet() const { return m_s3DataDistributionTypeHasBeenSet; }
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline void SetS3DataDistributionType(const S3DataDistribution& value) { m_s3DataDistributionTypeHasBeenSet = true; m_s3DataDistributionType = value; }
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline void SetS3DataDistributionType(S3DataDistribution&& value) { m_s3DataDistributionTypeHasBeenSet = true; m_s3DataDistributionType = std::move(value); }
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline S3DataSource& WithS3DataDistributionType(const S3DataDistribution& value) { SetS3DataDistributionType(value); return *this;}
|
|
|
|
/**
|
|
* <p>If you want Amazon SageMaker to replicate the entire dataset on each ML
|
|
* compute instance that is launched for model training, specify
|
|
* <code>FullyReplicated</code>. </p> <p>If you want Amazon SageMaker to replicate
|
|
* a subset of data on each ML compute instance that is launched for model
|
|
* training, specify <code>ShardedByS3Key</code>. If there are <i>n</i> ML compute
|
|
* instances launched for a training job, each instance gets approximately
|
|
* 1/<i>n</i> of the number of S3 objects. In this case, model training on each
|
|
* machine uses only the subset of training data. </p> <p>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. </p> <p>In distributed training, where you use multiple
|
|
* ML compute EC2 instances, you might choose <code>ShardedByS3Key</code>. If the
|
|
* algorithm requires copying training data to the ML storage volume (when
|
|
* <code>TrainingInputMode</code> is set to <code>File</code>), this copies
|
|
* 1/<i>n</i> of the number of objects. </p>
|
|
*/
|
|
inline S3DataSource& WithS3DataDistributionType(S3DataDistribution&& value) { SetS3DataDistributionType(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline const Aws::Vector<Aws::String>& GetAttributeNames() const{ return m_attributeNames; }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline bool AttributeNamesHasBeenSet() const { return m_attributeNamesHasBeenSet; }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline void SetAttributeNames(const Aws::Vector<Aws::String>& value) { m_attributeNamesHasBeenSet = true; m_attributeNames = value; }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline void SetAttributeNames(Aws::Vector<Aws::String>&& value) { m_attributeNamesHasBeenSet = true; m_attributeNames = std::move(value); }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline S3DataSource& WithAttributeNames(const Aws::Vector<Aws::String>& value) { SetAttributeNames(value); return *this;}
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline S3DataSource& WithAttributeNames(Aws::Vector<Aws::String>&& value) { SetAttributeNames(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline S3DataSource& AddAttributeNames(const Aws::String& value) { m_attributeNamesHasBeenSet = true; m_attributeNames.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline S3DataSource& AddAttributeNames(Aws::String&& value) { m_attributeNamesHasBeenSet = true; m_attributeNames.push_back(std::move(value)); return *this; }
|
|
|
|
/**
|
|
* <p>A list of one or more attribute names to use that are found in a specified
|
|
* augmented manifest file.</p>
|
|
*/
|
|
inline S3DataSource& AddAttributeNames(const char* value) { m_attributeNamesHasBeenSet = true; m_attributeNames.push_back(value); return *this; }
|
|
|
|
private:
|
|
|
|
S3DataType m_s3DataType;
|
|
bool m_s3DataTypeHasBeenSet;
|
|
|
|
Aws::String m_s3Uri;
|
|
bool m_s3UriHasBeenSet;
|
|
|
|
S3DataDistribution m_s3DataDistributionType;
|
|
bool m_s3DataDistributionTypeHasBeenSet;
|
|
|
|
Aws::Vector<Aws::String> m_attributeNames;
|
|
bool m_attributeNamesHasBeenSet;
|
|
};
|
|
|
|
} // namespace Model
|
|
} // namespace SageMaker
|
|
} // namespace Aws
|