GetCollaborationTrainedModelOutputBuilder

aws_sdk_cleanroomsml::operation::get_collaboration_trained_model::builders

Struct GetCollaborationTrainedModelOutputBuilder 

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#[non_exhaustive]
pub struct GetCollaborationTrainedModelOutputBuilder { /* private fields */ }
Expand description

A builder for GetCollaborationTrainedModelOutput.

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impl GetCollaborationTrainedModelOutputBuilder

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pub fn membership_identifier(self, input: impl Into<String>) -> Self

The membership ID of the member that created the trained model.

This field is required.
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pub fn set_membership_identifier(self, input: Option<String>) -> Self

The membership ID of the member that created the trained model.

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pub fn get_membership_identifier(&self) -> &Option<String>

The membership ID of the member that created the trained model.

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pub fn collaboration_identifier(self, input: impl Into<String>) -> Self

The collaboration ID of the collaboration that contains the trained model.

This field is required.
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pub fn set_collaboration_identifier(self, input: Option<String>) -> Self

The collaboration ID of the collaboration that contains the trained model.

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pub fn get_collaboration_identifier(&self) -> &Option<String>

The collaboration ID of the collaboration that contains the trained model.

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pub fn trained_model_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the trained model.

This field is required.
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pub fn set_trained_model_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the trained model.

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pub fn get_trained_model_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of the trained model.

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pub fn version_identifier(self, input: impl Into<String>) -> Self

The version identifier of the trained model. This unique identifier distinguishes this version from other versions of the same trained model.

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pub fn set_version_identifier(self, input: Option<String>) -> Self

The version identifier of the trained model. This unique identifier distinguishes this version from other versions of the same trained model.

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pub fn get_version_identifier(&self) -> &Option<String>

The version identifier of the trained model. This unique identifier distinguishes this version from other versions of the same trained model.

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pub fn incremental_training_data_channels( self, input: IncrementalTrainingDataChannelOutput, ) -> Self

Appends an item to incremental_training_data_channels.

To override the contents of this collection use set_incremental_training_data_channels.

Information about the incremental training data channels used to create this version of the trained model. This includes details about the base model that was used for incremental training and the channel configuration.

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pub fn set_incremental_training_data_channels( self, input: Option<Vec<IncrementalTrainingDataChannelOutput>>, ) -> Self

Information about the incremental training data channels used to create this version of the trained model. This includes details about the base model that was used for incremental training and the channel configuration.

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pub fn get_incremental_training_data_channels( &self, ) -> &Option<Vec<IncrementalTrainingDataChannelOutput>>

Information about the incremental training data channels used to create this version of the trained model. This includes details about the base model that was used for incremental training and the channel configuration.

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pub fn name(self, input: impl Into<String>) -> Self

The name of the trained model.

This field is required.
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pub fn set_name(self, input: Option<String>) -> Self

The name of the trained model.

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pub fn get_name(&self) -> &Option<String>

The name of the trained model.

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pub fn description(self, input: impl Into<String>) -> Self

The description of the trained model.

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pub fn set_description(self, input: Option<String>) -> Self

The description of the trained model.

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pub fn get_description(&self) -> &Option<String>

The description of the trained model.

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pub fn status(self, input: TrainedModelStatus) -> Self

The status of the trained model.

This field is required.
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pub fn set_status(self, input: Option<TrainedModelStatus>) -> Self

The status of the trained model.

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pub fn get_status(&self) -> &Option<TrainedModelStatus>

The status of the trained model.

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pub fn status_details(self, input: StatusDetails) -> Self

Details about the status of a resource.

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pub fn set_status_details(self, input: Option<StatusDetails>) -> Self

Details about the status of a resource.

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pub fn get_status_details(&self) -> &Option<StatusDetails>

Details about the status of a resource.

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pub fn configured_model_algorithm_association_arn( self, input: impl Into<String>, ) -> Self

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

This field is required.
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pub fn set_configured_model_algorithm_association_arn( self, input: Option<String>, ) -> Self

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

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pub fn get_configured_model_algorithm_association_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

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pub fn resource_config(self, input: ResourceConfig) -> Self

The EC2 resource configuration that was used to train this model.

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pub fn set_resource_config(self, input: Option<ResourceConfig>) -> Self

The EC2 resource configuration that was used to train this model.

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pub fn get_resource_config(&self) -> &Option<ResourceConfig>

The EC2 resource configuration that was used to train this model.

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pub fn training_input_mode(self, input: TrainingInputMode) -> Self

The input mode that was used for accessing the training data when this trained model was created. This indicates how the training data was made available to the training algorithm.

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pub fn set_training_input_mode(self, input: Option<TrainingInputMode>) -> Self

The input mode that was used for accessing the training data when this trained model was created. This indicates how the training data was made available to the training algorithm.

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pub fn get_training_input_mode(&self) -> &Option<TrainingInputMode>

The input mode that was used for accessing the training data when this trained model was created. This indicates how the training data was made available to the training algorithm.

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pub fn stopping_condition(self, input: StoppingCondition) -> Self

The stopping condition that determined when model training ended.

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pub fn set_stopping_condition(self, input: Option<StoppingCondition>) -> Self

The stopping condition that determined when model training ended.

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pub fn get_stopping_condition(&self) -> &Option<StoppingCondition>

The stopping condition that determined when model training ended.

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pub fn metrics_status(self, input: MetricsStatus) -> Self

The status of the model metrics.

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pub fn set_metrics_status(self, input: Option<MetricsStatus>) -> Self

The status of the model metrics.

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pub fn get_metrics_status(&self) -> &Option<MetricsStatus>

The status of the model metrics.

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pub fn metrics_status_details(self, input: impl Into<String>) -> Self

Details about the status information for the model metrics.

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pub fn set_metrics_status_details(self, input: Option<String>) -> Self

Details about the status information for the model metrics.

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pub fn get_metrics_status_details(&self) -> &Option<String>

Details about the status information for the model metrics.

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pub fn logs_status(self, input: LogsStatus) -> Self

Status information for the logs.

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pub fn set_logs_status(self, input: Option<LogsStatus>) -> Self

Status information for the logs.

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pub fn get_logs_status(&self) -> &Option<LogsStatus>

Status information for the logs.

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pub fn logs_status_details(self, input: impl Into<String>) -> Self

Details about the status information for the logs.

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pub fn set_logs_status_details(self, input: Option<String>) -> Self

Details about the status information for the logs.

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pub fn get_logs_status_details(&self) -> &Option<String>

Details about the status information for the logs.

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pub fn training_container_image_digest(self, input: impl Into<String>) -> Self

Information about the training container image.

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pub fn set_training_container_image_digest(self, input: Option<String>) -> Self

Information about the training container image.

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pub fn get_training_container_image_digest(&self) -> &Option<String>

Information about the training container image.

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pub fn create_time(self, input: DateTime) -> Self

The time at which the trained model was created.

This field is required.
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pub fn set_create_time(self, input: Option<DateTime>) -> Self

The time at which the trained model was created.

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pub fn get_create_time(&self) -> &Option<DateTime>

The time at which the trained model was created.

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pub fn update_time(self, input: DateTime) -> Self

The most recent time at which the trained model was updated.

This field is required.
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pub fn set_update_time(self, input: Option<DateTime>) -> Self

The most recent time at which the trained model was updated.

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pub fn get_update_time(&self) -> &Option<DateTime>

The most recent time at which the trained model was updated.

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pub fn creator_account_id(self, input: impl Into<String>) -> Self

The account ID of the member that created the trained model.

This field is required.
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pub fn set_creator_account_id(self, input: Option<String>) -> Self

The account ID of the member that created the trained model.

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pub fn get_creator_account_id(&self) -> &Option<String>

The account ID of the member that created the trained model.

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pub fn build(self) -> Result<GetCollaborationTrainedModelOutput, BuildError>

Consumes the builder and constructs a GetCollaborationTrainedModelOutput. This method will fail if any of the following fields are not set:

Trait Implementations§

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impl Clone for GetCollaborationTrainedModelOutputBuilder

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fn clone(&self) -> GetCollaborationTrainedModelOutputBuilder

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for GetCollaborationTrainedModelOutputBuilder

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

Formats the value using the given formatter. Read more
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impl Default for GetCollaborationTrainedModelOutputBuilder

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fn default() -> GetCollaborationTrainedModelOutputBuilder

Returns the “default value” for a type. Read more
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impl PartialEq for GetCollaborationTrainedModelOutputBuilder

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

Tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl StructuralPartialEq for GetCollaborationTrainedModelOutputBuilder

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