/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include Configuration for downloading input data from Amazon S3 into the processing
* container.See Also:
AWS
* API Reference
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline const Aws::String& GetS3Uri() const{ return m_s3Uri; } /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline bool S3UriHasBeenSet() const { return m_s3UriHasBeenSet; } /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline void SetS3Uri(const Aws::String& value) { m_s3UriHasBeenSet = true; m_s3Uri = value; } /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline void SetS3Uri(Aws::String&& value) { m_s3UriHasBeenSet = true; m_s3Uri = std::move(value); } /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline void SetS3Uri(const char* value) { m_s3UriHasBeenSet = true; m_s3Uri.assign(value); } /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline ProcessingS3Input& WithS3Uri(const Aws::String& value) { SetS3Uri(value); return *this;} /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline ProcessingS3Input& WithS3Uri(Aws::String&& value) { SetS3Uri(std::move(value)); return *this;} /** *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to * run a processing job.
*/ inline ProcessingS3Input& WithS3Uri(const char* value) { SetS3Uri(value); return *this;} /** *The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
The local path in your container where you want Amazon SageMaker to write
* input data to. LocalPath is an absolute path to the input data and
* must begin with /opt/ml/processing/. LocalPath is a
* required parameter when AppManaged is False
* (default).
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether you use an S3Prefix or a ManifestFile for
* the data type. If you choose S3Prefix, S3Uri
* identifies a key name prefix. Amazon SageMaker uses all objects with the
* specified key name prefix for the processing job. If you choose
* ManifestFile, S3Uri identifies an object that is a
* manifest file containing a list of object keys that you want Amazon SageMaker to
* use for the processing job.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File
* mode, Amazon SageMaker copies the data from the input source onto the local ML
* storage volume before starting your processing container. This is the most
* commonly used input mode. In Pipe mode, Amazon SageMaker streams
* input data from the source directly to your processing container into named
* pipes without using the ML storage volume.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances
* with FullyReplicated, or whether the data from Amazon S3 is shared
* by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
* processing container. Gzip can only be used when Pipe
* mode is specified as the S3InputMode. In Pipe mode,
* Amazon SageMaker streams input data from the source directly to your container
* without using the EBS volume.