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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
#[allow(missing_docs)] // documentation missing in model
#[non_exhaustive]
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::fmt::Debug)]
pub struct CreateEndpointInput {
    /// <p>This is the descriptive suffix that becomes part of the <code>EndpointArn</code> used for all subsequent requests to this resource. </p>
    pub endpoint_name: ::std::option::Option<::std::string::String>,
    /// <p>The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.</p>
    pub model_arn: ::std::option::Option<::std::string::String>,
    /// <p> The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.</p>
    pub desired_inference_units: ::std::option::Option<i32>,
    /// <p>An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a <code>ResourceInUseException</code>. </p>
    pub client_request_token: ::std::option::Option<::std::string::String>,
    /// <p>Tags to associate with the endpoint. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department. </p>
    pub tags: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>,
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).</p>
    pub data_access_role_arn: ::std::option::Option<::std::string::String>,
    /// <p>The Amazon Resource Number (ARN) of the flywheel to which the endpoint will be attached.</p>
    pub flywheel_arn: ::std::option::Option<::std::string::String>,
}
impl CreateEndpointInput {
    /// <p>This is the descriptive suffix that becomes part of the <code>EndpointArn</code> used for all subsequent requests to this resource. </p>
    pub fn endpoint_name(&self) -> ::std::option::Option<&str> {
        self.endpoint_name.as_deref()
    }
    /// <p>The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.</p>
    pub fn model_arn(&self) -> ::std::option::Option<&str> {
        self.model_arn.as_deref()
    }
    /// <p> The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.</p>
    pub fn desired_inference_units(&self) -> ::std::option::Option<i32> {
        self.desired_inference_units
    }
    /// <p>An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a <code>ResourceInUseException</code>. </p>
    pub fn client_request_token(&self) -> ::std::option::Option<&str> {
        self.client_request_token.as_deref()
    }
    /// <p>Tags to associate with the endpoint. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department. </p>
    pub fn tags(&self) -> ::std::option::Option<&[crate::types::Tag]> {
        self.tags.as_deref()
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).</p>
    pub fn data_access_role_arn(&self) -> ::std::option::Option<&str> {
        self.data_access_role_arn.as_deref()
    }
    /// <p>The Amazon Resource Number (ARN) of the flywheel to which the endpoint will be attached.</p>
    pub fn flywheel_arn(&self) -> ::std::option::Option<&str> {
        self.flywheel_arn.as_deref()
    }
}
impl CreateEndpointInput {
    /// Creates a new builder-style object to manufacture [`CreateEndpointInput`](crate::operation::create_endpoint::CreateEndpointInput).
    pub fn builder() -> crate::operation::create_endpoint::builders::CreateEndpointInputBuilder {
        crate::operation::create_endpoint::builders::CreateEndpointInputBuilder::default()
    }
}

/// A builder for [`CreateEndpointInput`](crate::operation::create_endpoint::CreateEndpointInput).
#[non_exhaustive]
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default, ::std::fmt::Debug)]
pub struct CreateEndpointInputBuilder {
    pub(crate) endpoint_name: ::std::option::Option<::std::string::String>,
    pub(crate) model_arn: ::std::option::Option<::std::string::String>,
    pub(crate) desired_inference_units: ::std::option::Option<i32>,
    pub(crate) client_request_token: ::std::option::Option<::std::string::String>,
    pub(crate) tags: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>,
    pub(crate) data_access_role_arn: ::std::option::Option<::std::string::String>,
    pub(crate) flywheel_arn: ::std::option::Option<::std::string::String>,
}
impl CreateEndpointInputBuilder {
    /// <p>This is the descriptive suffix that becomes part of the <code>EndpointArn</code> used for all subsequent requests to this resource. </p>
    pub fn endpoint_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.endpoint_name = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>This is the descriptive suffix that becomes part of the <code>EndpointArn</code> used for all subsequent requests to this resource. </p>
    pub fn set_endpoint_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.endpoint_name = input;
        self
    }
    /// <p>This is the descriptive suffix that becomes part of the <code>EndpointArn</code> used for all subsequent requests to this resource. </p>
    pub fn get_endpoint_name(&self) -> &::std::option::Option<::std::string::String> {
        &self.endpoint_name
    }
    /// <p>The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.</p>
    pub fn model_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.model_arn = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.</p>
    pub fn set_model_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.model_arn = input;
        self
    }
    /// <p>The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.</p>
    pub fn get_model_arn(&self) -> &::std::option::Option<::std::string::String> {
        &self.model_arn
    }
    /// <p> The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.</p>
    pub fn desired_inference_units(mut self, input: i32) -> Self {
        self.desired_inference_units = ::std::option::Option::Some(input);
        self
    }
    /// <p> The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.</p>
    pub fn set_desired_inference_units(mut self, input: ::std::option::Option<i32>) -> Self {
        self.desired_inference_units = input;
        self
    }
    /// <p> The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.</p>
    pub fn get_desired_inference_units(&self) -> &::std::option::Option<i32> {
        &self.desired_inference_units
    }
    /// <p>An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a <code>ResourceInUseException</code>. </p>
    pub fn client_request_token(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.client_request_token = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a <code>ResourceInUseException</code>. </p>
    pub fn set_client_request_token(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.client_request_token = input;
        self
    }
    /// <p>An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a <code>ResourceInUseException</code>. </p>
    pub fn get_client_request_token(&self) -> &::std::option::Option<::std::string::String> {
        &self.client_request_token
    }
    /// Appends an item to `tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>Tags to associate with the endpoint. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department. </p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        let mut v = self.tags.unwrap_or_default();
        v.push(input);
        self.tags = ::std::option::Option::Some(v);
        self
    }
    /// <p>Tags to associate with the endpoint. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department. </p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
        self.tags = input;
        self
    }
    /// <p>Tags to associate with the endpoint. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department. </p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        &self.tags
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).</p>
    pub fn data_access_role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.data_access_role_arn = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).</p>
    pub fn set_data_access_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.data_access_role_arn = input;
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).</p>
    pub fn get_data_access_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        &self.data_access_role_arn
    }
    /// <p>The Amazon Resource Number (ARN) of the flywheel to which the endpoint will be attached.</p>
    pub fn flywheel_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.flywheel_arn = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The Amazon Resource Number (ARN) of the flywheel to which the endpoint will be attached.</p>
    pub fn set_flywheel_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.flywheel_arn = input;
        self
    }
    /// <p>The Amazon Resource Number (ARN) of the flywheel to which the endpoint will be attached.</p>
    pub fn get_flywheel_arn(&self) -> &::std::option::Option<::std::string::String> {
        &self.flywheel_arn
    }
    /// Consumes the builder and constructs a [`CreateEndpointInput`](crate::operation::create_endpoint::CreateEndpointInput).
    pub fn build(
        self,
    ) -> ::std::result::Result<crate::operation::create_endpoint::CreateEndpointInput, ::aws_smithy_http::operation::error::BuildError> {
        ::std::result::Result::Ok(crate::operation::create_endpoint::CreateEndpointInput {
            endpoint_name: self.endpoint_name,
            model_arn: self.model_arn,
            desired_inference_units: self.desired_inference_units,
            client_request_token: self.client_request_token,
            tags: self.tags,
            data_access_role_arn: self.data_access_role_arn,
            flywheel_arn: self.flywheel_arn,
        })
    }
}