aws-sdk-sagemaker 1.196.0

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_ai_benchmark_job::_create_ai_benchmark_job_input::CreateAiBenchmarkJobInputBuilder;

pub use crate::operation::create_ai_benchmark_job::_create_ai_benchmark_job_output::CreateAiBenchmarkJobOutputBuilder;

impl crate::operation::create_ai_benchmark_job::builders::CreateAiBenchmarkJobInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::create_ai_benchmark_job::CreateAiBenchmarkJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_ai_benchmark_job();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateAIBenchmarkJob`.
///
/// <p>Creates a benchmark job that runs performance benchmarks against inference infrastructure using a predefined AI workload configuration. The benchmark job measures metrics such as latency, throughput, and cost for your generative AI inference endpoints.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateAIBenchmarkJobFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_ai_benchmark_job::builders::CreateAiBenchmarkJobInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_ai_benchmark_job::CreateAiBenchmarkJobOutput,
        crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJobError,
    > for CreateAIBenchmarkJobFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_ai_benchmark_job::CreateAiBenchmarkJobOutput,
            crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJobError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateAIBenchmarkJobFluentBuilder {
    /// Creates a new `CreateAIBenchmarkJobFluentBuilder`.
    pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: ::std::default::Default::default(),
            config_override: ::std::option::Option::None,
        }
    }
    /// Access the CreateAIBenchmarkJob as a reference.
    pub fn as_input(&self) -> &crate::operation::create_ai_benchmark_job::builders::CreateAiBenchmarkJobInputBuilder {
        &self.inner
    }
    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> ::std::result::Result<
        crate::operation::create_ai_benchmark_job::CreateAiBenchmarkJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let input = self
            .inner
            .build()
            .map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
        let runtime_plugins = crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJob::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJob::orchestrate(&runtime_plugins, input).await
    }

    /// Consumes this builder, creating a customizable operation that can be modified before being sent.
    pub fn customize(
        self,
    ) -> crate::client::customize::CustomizableOperation<
        crate::operation::create_ai_benchmark_job::CreateAiBenchmarkJobOutput,
        crate::operation::create_ai_benchmark_job::CreateAIBenchmarkJobError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
        self.set_config_override(::std::option::Option::Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The name of the AI benchmark job. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.</p>
    pub fn ai_benchmark_job_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.ai_benchmark_job_name(input.into());
        self
    }
    /// <p>The name of the AI benchmark job. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.</p>
    pub fn set_ai_benchmark_job_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_ai_benchmark_job_name(input);
        self
    }
    /// <p>The name of the AI benchmark job. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.</p>
    pub fn get_ai_benchmark_job_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_ai_benchmark_job_name()
    }
    /// <p>The target endpoint to benchmark. Specify a SageMaker endpoint by providing its name or Amazon Resource Name (ARN).</p>
    pub fn benchmark_target(mut self, input: crate::types::AiBenchmarkTarget) -> Self {
        self.inner = self.inner.benchmark_target(input);
        self
    }
    /// <p>The target endpoint to benchmark. Specify a SageMaker endpoint by providing its name or Amazon Resource Name (ARN).</p>
    pub fn set_benchmark_target(mut self, input: ::std::option::Option<crate::types::AiBenchmarkTarget>) -> Self {
        self.inner = self.inner.set_benchmark_target(input);
        self
    }
    /// <p>The target endpoint to benchmark. Specify a SageMaker endpoint by providing its name or Amazon Resource Name (ARN).</p>
    pub fn get_benchmark_target(&self) -> &::std::option::Option<crate::types::AiBenchmarkTarget> {
        self.inner.get_benchmark_target()
    }
    /// <p>The output configuration for the benchmark job, including the Amazon S3 location where benchmark results are stored.</p>
    pub fn output_config(mut self, input: crate::types::AiBenchmarkOutputConfig) -> Self {
        self.inner = self.inner.output_config(input);
        self
    }
    /// <p>The output configuration for the benchmark job, including the Amazon S3 location where benchmark results are stored.</p>
    pub fn set_output_config(mut self, input: ::std::option::Option<crate::types::AiBenchmarkOutputConfig>) -> Self {
        self.inner = self.inner.set_output_config(input);
        self
    }
    /// <p>The output configuration for the benchmark job, including the Amazon S3 location where benchmark results are stored.</p>
    pub fn get_output_config(&self) -> &::std::option::Option<crate::types::AiBenchmarkOutputConfig> {
        self.inner.get_output_config()
    }
    /// <p>The name or Amazon Resource Name (ARN) of the AI workload configuration to use for this benchmark job.</p>
    pub fn ai_workload_config_identifier(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.ai_workload_config_identifier(input.into());
        self
    }
    /// <p>The name or Amazon Resource Name (ARN) of the AI workload configuration to use for this benchmark job.</p>
    pub fn set_ai_workload_config_identifier(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_ai_workload_config_identifier(input);
        self
    }
    /// <p>The name or Amazon Resource Name (ARN) of the AI workload configuration to use for this benchmark job.</p>
    pub fn get_ai_workload_config_identifier(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_ai_workload_config_identifier()
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.</p>
    pub fn role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.role_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.</p>
    pub fn set_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_role_arn(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.</p>
    pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_role_arn()
    }
    /// <p>The network configuration for the benchmark job, including VPC settings.</p>
    pub fn network_config(mut self, input: crate::types::AiBenchmarkNetworkConfig) -> Self {
        self.inner = self.inner.network_config(input);
        self
    }
    /// <p>The network configuration for the benchmark job, including VPC settings.</p>
    pub fn set_network_config(mut self, input: ::std::option::Option<crate::types::AiBenchmarkNetworkConfig>) -> Self {
        self.inner = self.inner.set_network_config(input);
        self
    }
    /// <p>The network configuration for the benchmark job, including VPC settings.</p>
    pub fn get_network_config(&self) -> &::std::option::Option<crate::types::AiBenchmarkNetworkConfig> {
        self.inner.get_network_config()
    }
    ///
    /// Appends an item to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define.</p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
}