Struct rusoto_sagemaker::TrainingSpecification

pub struct TrainingSpecification {
    pub metric_definitions: Option<Vec<MetricDefinition>>,
    pub supported_hyper_parameters: Option<Vec<HyperParameterSpecification>>,
    pub supported_training_instance_types: Vec<String>,
    pub supported_tuning_job_objective_metrics: Option<Vec<HyperParameterTuningJobObjective>>,
    pub supports_distributed_training: Option<bool>,
    pub training_channels: Vec<ChannelSpecification>,
    pub training_image: String,
    pub training_image_digest: Option<String>,
}

Defines how the algorithm is used for a training job.

Fields

metric_definitions: Option<Vec<MetricDefinition>>

A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

supported_hyper_parameters: Option<Vec<HyperParameterSpecification>>

A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

supported_training_instance_types: Vec<String>

A list of the instance types that this algorithm can use for training.

supported_tuning_job_objective_metrics: Option<Vec<HyperParameterTuningJobObjective>>

A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

supports_distributed_training: Option<bool>

Indicates whether the algorithm supports distributed training. If set to false, buyers can’t request more than one instance during training.

training_channels: Vec<ChannelSpecification>

A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

training_image: String

The Amazon ECR registry path of the Docker image that contains the training algorithm.

training_image_digest: Option<String>

An MD5 hash of the training algorithm that identifies the Docker image used for training.

Trait Implementations

impl PartialEq<TrainingSpecification> for TrainingSpecification

fn eq(&self, other: &TrainingSpecification) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &TrainingSpecification) -> bool

This method tests for !=.

impl Default for TrainingSpecification

fn default() -> TrainingSpecification

Returns the "default value" for a type.

impl Clone for TrainingSpecification

fn clone(&self) -> TrainingSpecification

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TrainingSpecification

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Serialize for TrainingSpecification

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl<'de> Deserialize<'de> for TrainingSpecification

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.