#[non_exhaustive]pub struct ChannelBuilder { /* private fields */ }Expand description
A builder for Channel.
Implementations§
Source§impl ChannelBuilder
impl ChannelBuilder
Sourcepub fn channel_name(self, input: impl Into<String>) -> Self
pub fn channel_name(self, input: impl Into<String>) -> Self
The name of the channel.
This field is required.Sourcepub fn set_channel_name(self, input: Option<String>) -> Self
pub fn set_channel_name(self, input: Option<String>) -> Self
The name of the channel.
Sourcepub fn get_channel_name(&self) -> &Option<String>
pub fn get_channel_name(&self) -> &Option<String>
The name of the channel.
Sourcepub fn data_source(self, input: DataSource) -> Self
pub fn data_source(self, input: DataSource) -> Self
The location of the channel data.
This field is required.Sourcepub fn set_data_source(self, input: Option<DataSource>) -> Self
pub fn set_data_source(self, input: Option<DataSource>) -> Self
The location of the channel data.
Sourcepub fn get_data_source(&self) -> &Option<DataSource>
pub fn get_data_source(&self) -> &Option<DataSource>
The location of the channel data.
Sourcepub fn content_type(self, input: impl Into<String>) -> Self
pub fn content_type(self, input: impl Into<String>) -> Self
The MIME type of the data.
Sourcepub fn set_content_type(self, input: Option<String>) -> Self
pub fn set_content_type(self, input: Option<String>) -> Self
The MIME type of the data.
Sourcepub fn get_content_type(&self) -> &Option<String>
pub fn get_content_type(&self) -> &Option<String>
The MIME type of the data.
Sourcepub fn compression_type(self, input: CompressionType) -> Self
pub fn compression_type(self, input: CompressionType) -> Self
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
Sourcepub fn set_compression_type(self, input: Option<CompressionType>) -> Self
pub fn set_compression_type(self, input: Option<CompressionType>) -> Self
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
Sourcepub fn get_compression_type(&self) -> &Option<CompressionType>
pub fn get_compression_type(&self) -> &Option<CompressionType>
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
Sourcepub fn record_wrapper_type(self, input: RecordWrapper) -> Self
pub fn record_wrapper_type(self, input: RecordWrapper) -> Self
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
Sourcepub fn set_record_wrapper_type(self, input: Option<RecordWrapper>) -> Self
pub fn set_record_wrapper_type(self, input: Option<RecordWrapper>) -> Self
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
Sourcepub fn get_record_wrapper_type(&self) -> &Option<RecordWrapper>
pub fn get_record_wrapper_type(&self) -> &Option<RecordWrapper>
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
Sourcepub fn input_mode(self, input: TrainingInputMode) -> Self
pub fn input_mode(self, input: TrainingInputMode) -> Self
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
Sourcepub fn set_input_mode(self, input: Option<TrainingInputMode>) -> Self
pub fn set_input_mode(self, input: Option<TrainingInputMode>) -> Self
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
Sourcepub fn get_input_mode(&self) -> &Option<TrainingInputMode>
pub fn get_input_mode(&self) -> &Option<TrainingInputMode>
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
Sourcepub fn shuffle_config(self, input: ShuffleConfig) -> Self
pub fn shuffle_config(self, input: ShuffleConfig) -> Self
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
Sourcepub fn set_shuffle_config(self, input: Option<ShuffleConfig>) -> Self
pub fn set_shuffle_config(self, input: Option<ShuffleConfig>) -> Self
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
Sourcepub fn get_shuffle_config(&self) -> &Option<ShuffleConfig>
pub fn get_shuffle_config(&self) -> &Option<ShuffleConfig>
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
Trait Implementations§
Source§impl Clone for ChannelBuilder
impl Clone for ChannelBuilder
Source§fn clone(&self) -> ChannelBuilder
fn clone(&self) -> ChannelBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl Debug for ChannelBuilder
impl Debug for ChannelBuilder
Source§impl Default for ChannelBuilder
impl Default for ChannelBuilder
Source§fn default() -> ChannelBuilder
fn default() -> ChannelBuilder
Source§impl PartialEq for ChannelBuilder
impl PartialEq for ChannelBuilder
impl StructuralPartialEq for ChannelBuilder
Auto Trait Implementations§
impl Freeze for ChannelBuilder
impl RefUnwindSafe for ChannelBuilder
impl Send for ChannelBuilder
impl Sync for ChannelBuilder
impl Unpin for ChannelBuilder
impl UnwindSafe for ChannelBuilder
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