// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::update_inference_experiment::_update_inference_experiment_output::UpdateInferenceExperimentOutputBuilder;

pub use crate::operation::update_inference_experiment::_update_inference_experiment_input::UpdateInferenceExperimentInputBuilder;

impl UpdateInferenceExperimentInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::update_inference_experiment::UpdateInferenceExperimentOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::update_inference_experiment::UpdateInferenceExperimentError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.update_inference_experiment();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `UpdateInferenceExperiment`.
///
/// <p> Updates an inference experiment that you created. The status of the inference experiment has to be either <code>Created</code>, <code>Running</code>. For more information on the status of an inference experiment, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeInferenceExperiment.html">DescribeInferenceExperiment</a>. </p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct UpdateInferenceExperimentFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::update_inference_experiment::builders::UpdateInferenceExperimentInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::update_inference_experiment::UpdateInferenceExperimentOutput,
        crate::operation::update_inference_experiment::UpdateInferenceExperimentError,
    > for UpdateInferenceExperimentFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::update_inference_experiment::UpdateInferenceExperimentOutput,
            crate::operation::update_inference_experiment::UpdateInferenceExperimentError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl UpdateInferenceExperimentFluentBuilder {
    /// Creates a new `UpdateInferenceExperiment`.
    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 UpdateInferenceExperiment as a reference.
    pub fn as_input(&self) -> &crate::operation::update_inference_experiment::builders::UpdateInferenceExperimentInputBuilder {
        &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::update_inference_experiment::UpdateInferenceExperimentOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::update_inference_experiment::UpdateInferenceExperimentError,
            ::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::update_inference_experiment::UpdateInferenceExperiment::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::update_inference_experiment::UpdateInferenceExperiment::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::update_inference_experiment::UpdateInferenceExperimentOutput,
        crate::operation::update_inference_experiment::UpdateInferenceExperimentError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl Into<crate::config::Builder>) -> Self {
        self.set_config_override(Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The name of the inference experiment to be updated.</p>
    pub fn name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.name(input.into());
        self
    }
    /// <p>The name of the inference experiment to be updated.</p>
    pub fn set_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_name(input);
        self
    }
    /// <p>The name of the inference experiment to be updated.</p>
    pub fn get_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_name()
    }
    /// <p> The duration for which the inference experiment will run. If the status of the inference experiment is <code>Created</code>, then you can update both the start and end dates. If the status of the inference experiment is <code>Running</code>, then you can update only the end date. </p>
    pub fn schedule(mut self, input: crate::types::InferenceExperimentSchedule) -> Self {
        self.inner = self.inner.schedule(input);
        self
    }
    /// <p> The duration for which the inference experiment will run. If the status of the inference experiment is <code>Created</code>, then you can update both the start and end dates. If the status of the inference experiment is <code>Running</code>, then you can update only the end date. </p>
    pub fn set_schedule(mut self, input: ::std::option::Option<crate::types::InferenceExperimentSchedule>) -> Self {
        self.inner = self.inner.set_schedule(input);
        self
    }
    /// <p> The duration for which the inference experiment will run. If the status of the inference experiment is <code>Created</code>, then you can update both the start and end dates. If the status of the inference experiment is <code>Running</code>, then you can update only the end date. </p>
    pub fn get_schedule(&self) -> &::std::option::Option<crate::types::InferenceExperimentSchedule> {
        self.inner.get_schedule()
    }
    /// <p>The description of the inference experiment.</p>
    pub fn description(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.description(input.into());
        self
    }
    /// <p>The description of the inference experiment.</p>
    pub fn set_description(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_description(input);
        self
    }
    /// <p>The description of the inference experiment.</p>
    pub fn get_description(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_description()
    }
    /// Appends an item to `ModelVariants`.
    ///
    /// To override the contents of this collection use [`set_model_variants`](Self::set_model_variants).
    ///
    /// <p> An array of <code>ModelVariantConfig</code> objects. There is one for each variant, whose infrastructure configuration you want to update. </p>
    pub fn model_variants(mut self, input: crate::types::ModelVariantConfig) -> Self {
        self.inner = self.inner.model_variants(input);
        self
    }
    /// <p> An array of <code>ModelVariantConfig</code> objects. There is one for each variant, whose infrastructure configuration you want to update. </p>
    pub fn set_model_variants(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::ModelVariantConfig>>) -> Self {
        self.inner = self.inner.set_model_variants(input);
        self
    }
    /// <p> An array of <code>ModelVariantConfig</code> objects. There is one for each variant, whose infrastructure configuration you want to update. </p>
    pub fn get_model_variants(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::ModelVariantConfig>> {
        self.inner.get_model_variants()
    }
    /// <p>The Amazon S3 location and configuration for storing inference request and response data.</p>
    pub fn data_storage_config(mut self, input: crate::types::InferenceExperimentDataStorageConfig) -> Self {
        self.inner = self.inner.data_storage_config(input);
        self
    }
    /// <p>The Amazon S3 location and configuration for storing inference request and response data.</p>
    pub fn set_data_storage_config(mut self, input: ::std::option::Option<crate::types::InferenceExperimentDataStorageConfig>) -> Self {
        self.inner = self.inner.set_data_storage_config(input);
        self
    }
    /// <p>The Amazon S3 location and configuration for storing inference request and response data.</p>
    pub fn get_data_storage_config(&self) -> &::std::option::Option<crate::types::InferenceExperimentDataStorageConfig> {
        self.inner.get_data_storage_config()
    }
    /// <p> The configuration of <code>ShadowMode</code> inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates. </p>
    pub fn shadow_mode_config(mut self, input: crate::types::ShadowModeConfig) -> Self {
        self.inner = self.inner.shadow_mode_config(input);
        self
    }
    /// <p> The configuration of <code>ShadowMode</code> inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates. </p>
    pub fn set_shadow_mode_config(mut self, input: ::std::option::Option<crate::types::ShadowModeConfig>) -> Self {
        self.inner = self.inner.set_shadow_mode_config(input);
        self
    }
    /// <p> The configuration of <code>ShadowMode</code> inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates. </p>
    pub fn get_shadow_mode_config(&self) -> &::std::option::Option<crate::types::ShadowModeConfig> {
        self.inner.get_shadow_mode_config()
    }
}