// Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT.

package machinelearning

import (
	"context"

	"github.com/aws/aws-sdk-go-v2/aws"
	"github.com/aws/aws-sdk-go-v2/internal/awsutil"
)

type UpdateMLModelInput struct {
	_ struct{} `type:"structure"`

	// The ID assigned to the MLModel during creation.
	//
	// MLModelId is a required field
	MLModelId *string `min:"1" type:"string" required:"true"`

	// A user-supplied name or description of the MLModel.
	MLModelName *string `type:"string"`

	// The ScoreThreshold used in binary classification MLModel that marks the boundary
	// between a positive prediction and a negative prediction.
	//
	// Output values greater than or equal to the ScoreThreshold receive a positive
	// result from the MLModel, such as true. Output values less than the ScoreThreshold
	// receive a negative response from the MLModel, such as false.
	ScoreThreshold *float64 `type:"float"`
}

// String returns the string representation
func (s UpdateMLModelInput) String() string {
	return awsutil.Prettify(s)
}

// Validate inspects the fields of the type to determine if they are valid.
func (s *UpdateMLModelInput) Validate() error {
	invalidParams := aws.ErrInvalidParams{Context: "UpdateMLModelInput"}

	if s.MLModelId == nil {
		invalidParams.Add(aws.NewErrParamRequired("MLModelId"))
	}
	if s.MLModelId != nil && len(*s.MLModelId) < 1 {
		invalidParams.Add(aws.NewErrParamMinLen("MLModelId", 1))
	}

	if invalidParams.Len() > 0 {
		return invalidParams
	}
	return nil
}

// Represents the output of an UpdateMLModel operation.
//
// You can see the updated content by using the GetMLModel operation.
type UpdateMLModelOutput struct {
	_ struct{} `type:"structure"`

	// The ID assigned to the MLModel during creation. This value should be identical
	// to the value of the MLModelID in the request.
	MLModelId *string `min:"1" type:"string"`
}

// String returns the string representation
func (s UpdateMLModelOutput) String() string {
	return awsutil.Prettify(s)
}

const opUpdateMLModel = "UpdateMLModel"

// UpdateMLModelRequest returns a request value for making API operation for
// Amazon Machine Learning.
//
// Updates the MLModelName and the ScoreThreshold of an MLModel.
//
// You can use the GetMLModel operation to view the contents of the updated
// data element.
//
//    // Example sending a request using UpdateMLModelRequest.
//    req := client.UpdateMLModelRequest(params)
//    resp, err := req.Send(context.TODO())
//    if err == nil {
//        fmt.Println(resp)
//    }
func (c *Client) UpdateMLModelRequest(input *UpdateMLModelInput) UpdateMLModelRequest {
	op := &aws.Operation{
		Name:       opUpdateMLModel,
		HTTPMethod: "POST",
		HTTPPath:   "/",
	}

	if input == nil {
		input = &UpdateMLModelInput{}
	}

	req := c.newRequest(op, input, &UpdateMLModelOutput{})

	return UpdateMLModelRequest{Request: req, Input: input, Copy: c.UpdateMLModelRequest}
}

// UpdateMLModelRequest is the request type for the
// UpdateMLModel API operation.
type UpdateMLModelRequest struct {
	*aws.Request
	Input *UpdateMLModelInput
	Copy  func(*UpdateMLModelInput) UpdateMLModelRequest
}

// Send marshals and sends the UpdateMLModel API request.
func (r UpdateMLModelRequest) Send(ctx context.Context) (*UpdateMLModelResponse, error) {
	r.Request.SetContext(ctx)
	err := r.Request.Send()
	if err != nil {
		return nil, err
	}

	resp := &UpdateMLModelResponse{
		UpdateMLModelOutput: r.Request.Data.(*UpdateMLModelOutput),
		response:            &aws.Response{Request: r.Request},
	}

	return resp, nil
}

// UpdateMLModelResponse is the response type for the
// UpdateMLModel API operation.
type UpdateMLModelResponse struct {
	*UpdateMLModelOutput

	response *aws.Response
}

// SDKResponseMetdata returns the response metadata for the
// UpdateMLModel request.
func (r *UpdateMLModelResponse) SDKResponseMetdata() *aws.Response {
	return r.response
}