aws_sdk_cleanroomsml::operation::get_trained_model_inference_job::builders

Struct GetTrainedModelInferenceJobOutputBuilder

#[non_exhaustive]
pub struct GetTrainedModelInferenceJobOutputBuilder { /* private fields */ }

Expand description

A builder for GetTrainedModelInferenceJobOutput.

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impl GetTrainedModelInferenceJobOutputBuilder

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

The time at which the trained model inference job 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 inference job was created.

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

The time at which the trained model inference job was created.

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

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

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

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

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

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

This field is required.

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

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

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

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

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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 for the trained model inference job.

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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 for the trained model inference job.

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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 for the trained model inference job.

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

The name of the trained model inference job.

This field is required.

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

The name of the trained model inference job.

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

The name of the trained model inference job.

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

The status of the trained model inference job.

This field is required.

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pub fn set_status(self, input: Option<TrainedModelInferenceJobStatus>) -> Self

The status of the trained model inference job.

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

The status of the trained model inference job.

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

The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.

This field is required.

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

The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.

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

The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.

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

The version identifier of the trained model used for this inference job. This identifies the specific version of the trained model that was used to generate the inference results.

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

The version identifier of the trained model used for this inference job. This identifies the specific version of the trained model that was used to generate the inference results.

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

The version identifier of the trained model used for this inference job. This identifies the specific version of the trained model that was used to generate the inference results.

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

The resource configuration information for the trained model inference job.

This field is required.

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

The resource configuration information for the trained model inference job.

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

The resource configuration information for the trained model inference job.

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pub fn output_configuration(self, input: InferenceOutputConfiguration) -> Self

The output configuration information for the trained model inference job.

This field is required.

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pub fn set_output_configuration( self, input: Option<InferenceOutputConfiguration>, ) -> Self

The output configuration information for the trained model inference job.

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pub fn get_output_configuration(&self) -> &Option<InferenceOutputConfiguration>

The output configuration information for the trained model inference job.

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

The membership ID of the membership that contains the trained model inference job.

This field is required.

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

The membership ID of the membership that contains the trained model inference job.

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

The membership ID of the membership that contains the trained model inference job.

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pub fn data_source(self, input: ModelInferenceDataSource) -> Self

The data source that was used for the trained model inference job.

This field is required.

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pub fn set_data_source(self, input: Option<ModelInferenceDataSource>) -> Self

The data source that was used for the trained model inference job.

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pub fn get_data_source(&self) -> &Option<ModelInferenceDataSource>

The data source that was used for the trained model inference job.

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pub fn container_execution_parameters( self, input: InferenceContainerExecutionParameters, ) -> Self

The execution parameters for the model inference job container.

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pub fn set_container_execution_parameters( self, input: Option<InferenceContainerExecutionParameters>, ) -> Self

The execution parameters for the model inference job container.

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pub fn get_container_execution_parameters( &self, ) -> &Option<InferenceContainerExecutionParameters>

The execution parameters for the model inference job container.

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

The description of the trained model inference job.

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

The description of the trained model inference job.

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

The description of the trained model inference job.

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

Information about the training container image.

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

Information about the training container image.

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

Information about the training container image.

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pub fn environment(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to environment.

To override the contents of this collection use set_environment.

The environment variables to set in the Docker container.

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

The environment variables to set in the Docker container.

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pub fn get_environment(&self) -> &Option<HashMap<String, String>>

The environment variables to set in the Docker container.

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

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

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

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

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

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

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

The metrics status for the trained model inference job.

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

The metrics status for the trained model inference job.

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

The metrics status for the trained model inference job.

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

Details about the metrics status for the trained model inference job.

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

Details about the metrics status for the trained model inference job.

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

Details about the metrics status for the trained model inference job.

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

The logs status for the trained model inference job.

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

The logs status for the trained model inference job.

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

The logs status for the trained model inference job.

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

Details about the logs status for the trained model inference job.

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

Details about the logs status for the trained model inference job.

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

Details about the logs status for the trained model inference job.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to tags.

To override the contents of this collection use set_tags.

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

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

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

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

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

Trait Implementations§

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impl Clone for GetTrainedModelInferenceJobOutputBuilder

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fn clone(&self) -> GetTrainedModelInferenceJobOutputBuilder

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 GetTrainedModelInferenceJobOutputBuilder

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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 GetTrainedModelInferenceJobOutputBuilder

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fn default() -> GetTrainedModelInferenceJobOutputBuilder

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

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impl PartialEq for GetTrainedModelInferenceJobOutputBuilder

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fn eq(&self, other: &GetTrainedModelInferenceJobOutputBuilder) -> 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 GetTrainedModelInferenceJobOutputBuilder

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impl UnwindSafe for GetTrainedModelInferenceJobOutputBuilder

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GetTrainedModelInferenceJobOutputBuilder

Struct GetTrainedModelInferenceJobOutputBuilder Copy item path

Implementations§

impl GetTrainedModelInferenceJobOutputBuilder

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

pub fn set_create_time(self, input: Option<DateTime>) -> Self

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

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

pub fn set_update_time(self, input: Option<DateTime>) -> Self

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

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

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

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

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

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

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

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

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

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

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

pub fn set_status(self, input: Option<TrainedModelInferenceJobStatus>) -> Self

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

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

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

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

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

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

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

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

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

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

pub fn output_configuration(self, input: InferenceOutputConfiguration) -> Self

pub fn set_output_configuration( self, input: Option<InferenceOutputConfiguration>, ) -> Self

pub fn get_output_configuration(&self) -> &Option<InferenceOutputConfiguration>

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

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

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

pub fn data_source(self, input: ModelInferenceDataSource) -> Self

pub fn set_data_source(self, input: Option<ModelInferenceDataSource>) -> Self

pub fn get_data_source(&self) -> &Option<ModelInferenceDataSource>

pub fn container_execution_parameters( self, input: InferenceContainerExecutionParameters, ) -> Self

pub fn set_container_execution_parameters( self, input: Option<InferenceContainerExecutionParameters>, ) -> Self

pub fn get_container_execution_parameters( &self, ) -> &Option<InferenceContainerExecutionParameters>

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

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

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

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

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

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

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

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

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

pub fn environment(self, k: impl Into<String>, v: impl Into<String>) -> Self

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

pub fn get_environment(&self) -> &Option<HashMap<String, String>>

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

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

pub fn get_tags(&self) -> &Option<HashMap<String, String>>

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

Trait Implementations§

impl Clone for GetTrainedModelInferenceJobOutputBuilder

fn clone(&self) -> GetTrainedModelInferenceJobOutputBuilder

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

impl Debug for GetTrainedModelInferenceJobOutputBuilder

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

Struct GetTrainedModelInferenceJobOutputBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,