Struct rusoto_sagemaker::TrainingJobDefinition

pub struct TrainingJobDefinition {
    pub hyper_parameters: Option<HashMap<String, String>>,
    pub input_data_config: Vec<Channel>,
    pub output_data_config: OutputDataConfig,
    pub resource_config: ResourceConfig,
    pub stopping_condition: StoppingCondition,
    pub training_input_mode: String,
}

Defines the input needed to run a training job using the algorithm.

Fields

hyper_parameters: Option<HashMap<String, String>>

The hyperparameters used for the training job.

input_data_config: Vec<Channel>

An array of Channel objects, each of which specifies an input source.

output_data_config: OutputDataConfig

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

resource_config: ResourceConfig

The resources, including the ML compute instances and ML storage volumes, to use for model training.

stopping_condition: StoppingCondition

Sets a duration for training. Use this parameter to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts.

training_input_mode: String

The input mode used by the algorithm for the training job. For the input modes that Amazon SageMaker algorithms support, see Algorithms.

If an algorithm supports the File input mode, Amazon SageMaker downloads the training data from S3 to the provisioned ML storage Volume, and mounts the directory to docker volume for training container. If an algorithm supports the Pipe input mode, Amazon SageMaker streams data directly from S3 to the container.

Trait Implementations

impl PartialEq<TrainingJobDefinition> for TrainingJobDefinition

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

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

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

This method tests for !=.

impl Default for TrainingJobDefinition

fn default() -> TrainingJobDefinition

Returns the "default value" for a type.

impl Clone for TrainingJobDefinition

fn clone(&self) -> TrainingJobDefinition

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for TrainingJobDefinition

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

Formats the value using the given formatter.

impl Serialize for TrainingJobDefinition

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 TrainingJobDefinition

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

Deserialize this value from the given Serde deserializer.