// Code generated by protoc-gen-go. DO NOT EDIT.
// source: google/cloud/automl/v1beta1/model.proto

package automl // import "google.golang.org/genproto/googleapis/cloud/automl/v1beta1"

import proto "github.com/golang/protobuf/proto"
import fmt "fmt"
import math "math"
import timestamp "github.com/golang/protobuf/ptypes/timestamp"
import _ "google.golang.org/genproto/googleapis/api/annotations"

// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fmt.Errorf
var _ = math.Inf

// This is a compile-time assertion to ensure that this generated file
// is compatible with the proto package it is being compiled against.
// A compilation error at this line likely means your copy of the
// proto package needs to be updated.
const _ = proto.ProtoPackageIsVersion2 // please upgrade the proto package

// Deployment state of the model.
type Model_DeploymentState int32

const (
	// Should not be used, an un-set enum has this value by default.
	Model_DEPLOYMENT_STATE_UNSPECIFIED Model_DeploymentState = 0
	// Model is deployed.
	Model_DEPLOYED Model_DeploymentState = 1
	// Model is not deployed.
	Model_UNDEPLOYED Model_DeploymentState = 2
)

var Model_DeploymentState_name = map[int32]string{
	0: "DEPLOYMENT_STATE_UNSPECIFIED",
	1: "DEPLOYED",
	2: "UNDEPLOYED",
}
var Model_DeploymentState_value = map[string]int32{
	"DEPLOYMENT_STATE_UNSPECIFIED": 0,
	"DEPLOYED":                     1,
	"UNDEPLOYED":                   2,
}

func (x Model_DeploymentState) String() string {
	return proto.EnumName(Model_DeploymentState_name, int32(x))
}
func (Model_DeploymentState) EnumDescriptor() ([]byte, []int) {
	return fileDescriptor_model_045660f03fa00661, []int{0, 0}
}

// API proto representing a trained machine learning model.
type Model struct {
	// Required.
	// The model metadata that is specific to the problem type.
	// Must match the metadata type of the dataset used to train the model.
	//
	// Types that are valid to be assigned to ModelMetadata:
	//	*Model_TranslationModelMetadata
	//	*Model_ImageClassificationModelMetadata
	//	*Model_TextClassificationModelMetadata
	//	*Model_ImageObjectDetectionModelMetadata
	//	*Model_VideoClassificationModelMetadata
	//	*Model_TextExtractionModelMetadata
	//	*Model_TablesModelMetadata
	//	*Model_TextSentimentModelMetadata
	ModelMetadata isModel_ModelMetadata `protobuf_oneof:"model_metadata"`
	// Output only.
	// Resource name of the model.
	// Format: `projects/{project_id}/locations/{location_id}/models/{model_id}`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// Required. The name of the model to show in the interface. The name can be
	// up to 32 characters long and can consist only of ASCII Latin letters A-Z
	// and a-z, underscores
	// (_), and ASCII digits 0-9. It must start with a letter.
	DisplayName string `protobuf:"bytes,2,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"`
	// Required.
	// The resource ID of the dataset used to create the model. The dataset must
	// come from the same ancestor project and location.
	DatasetId string `protobuf:"bytes,3,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
	// Output only.
	// Timestamp when this model was created.
	CreateTime *timestamp.Timestamp `protobuf:"bytes,7,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only.
	// Timestamp when this model was last updated.
	UpdateTime *timestamp.Timestamp `protobuf:"bytes,11,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"`
	// Output only. Deployment state of the model. A model can only serve
	// prediction requests after it gets deployed.
	DeploymentState      Model_DeploymentState `protobuf:"varint,8,opt,name=deployment_state,json=deploymentState,proto3,enum=google.cloud.automl.v1beta1.Model_DeploymentState" json:"deployment_state,omitempty"`
	XXX_NoUnkeyedLiteral struct{}              `json:"-"`
	XXX_unrecognized     []byte                `json:"-"`
	XXX_sizecache        int32                 `json:"-"`
}

func (m *Model) Reset()         { *m = Model{} }
func (m *Model) String() string { return proto.CompactTextString(m) }
func (*Model) ProtoMessage()    {}
func (*Model) Descriptor() ([]byte, []int) {
	return fileDescriptor_model_045660f03fa00661, []int{0}
}
func (m *Model) XXX_Unmarshal(b []byte) error {
	return xxx_messageInfo_Model.Unmarshal(m, b)
}
func (m *Model) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
	return xxx_messageInfo_Model.Marshal(b, m, deterministic)
}
func (dst *Model) XXX_Merge(src proto.Message) {
	xxx_messageInfo_Model.Merge(dst, src)
}
func (m *Model) XXX_Size() int {
	return xxx_messageInfo_Model.Size(m)
}
func (m *Model) XXX_DiscardUnknown() {
	xxx_messageInfo_Model.DiscardUnknown(m)
}

var xxx_messageInfo_Model proto.InternalMessageInfo

type isModel_ModelMetadata interface {
	isModel_ModelMetadata()
}

type Model_TranslationModelMetadata struct {
	TranslationModelMetadata *TranslationModelMetadata `protobuf:"bytes,15,opt,name=translation_model_metadata,json=translationModelMetadata,proto3,oneof"`
}

type Model_ImageClassificationModelMetadata struct {
	ImageClassificationModelMetadata *ImageClassificationModelMetadata `protobuf:"bytes,13,opt,name=image_classification_model_metadata,json=imageClassificationModelMetadata,proto3,oneof"`
}

type Model_TextClassificationModelMetadata struct {
	TextClassificationModelMetadata *TextClassificationModelMetadata `protobuf:"bytes,14,opt,name=text_classification_model_metadata,json=textClassificationModelMetadata,proto3,oneof"`
}

type Model_ImageObjectDetectionModelMetadata struct {
	ImageObjectDetectionModelMetadata *ImageObjectDetectionModelMetadata `protobuf:"bytes,20,opt,name=image_object_detection_model_metadata,json=imageObjectDetectionModelMetadata,proto3,oneof"`
}

type Model_VideoClassificationModelMetadata struct {
	VideoClassificationModelMetadata *VideoClassificationModelMetadata `protobuf:"bytes,23,opt,name=video_classification_model_metadata,json=videoClassificationModelMetadata,proto3,oneof"`
}

type Model_TextExtractionModelMetadata struct {
	TextExtractionModelMetadata *TextExtractionModelMetadata `protobuf:"bytes,19,opt,name=text_extraction_model_metadata,json=textExtractionModelMetadata,proto3,oneof"`
}

type Model_TablesModelMetadata struct {
	TablesModelMetadata *TablesModelMetadata `protobuf:"bytes,24,opt,name=tables_model_metadata,json=tablesModelMetadata,proto3,oneof"`
}

type Model_TextSentimentModelMetadata struct {
	TextSentimentModelMetadata *TextSentimentModelMetadata `protobuf:"bytes,22,opt,name=text_sentiment_model_metadata,json=textSentimentModelMetadata,proto3,oneof"`
}

func (*Model_TranslationModelMetadata) isModel_ModelMetadata() {}

func (*Model_ImageClassificationModelMetadata) isModel_ModelMetadata() {}

func (*Model_TextClassificationModelMetadata) isModel_ModelMetadata() {}

func (*Model_ImageObjectDetectionModelMetadata) isModel_ModelMetadata() {}

func (*Model_VideoClassificationModelMetadata) isModel_ModelMetadata() {}

func (*Model_TextExtractionModelMetadata) isModel_ModelMetadata() {}

func (*Model_TablesModelMetadata) isModel_ModelMetadata() {}

func (*Model_TextSentimentModelMetadata) isModel_ModelMetadata() {}

func (m *Model) GetModelMetadata() isModel_ModelMetadata {
	if m != nil {
		return m.ModelMetadata
	}
	return nil
}

func (m *Model) GetTranslationModelMetadata() *TranslationModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_TranslationModelMetadata); ok {
		return x.TranslationModelMetadata
	}
	return nil
}

func (m *Model) GetImageClassificationModelMetadata() *ImageClassificationModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_ImageClassificationModelMetadata); ok {
		return x.ImageClassificationModelMetadata
	}
	return nil
}

func (m *Model) GetTextClassificationModelMetadata() *TextClassificationModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_TextClassificationModelMetadata); ok {
		return x.TextClassificationModelMetadata
	}
	return nil
}

func (m *Model) GetImageObjectDetectionModelMetadata() *ImageObjectDetectionModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_ImageObjectDetectionModelMetadata); ok {
		return x.ImageObjectDetectionModelMetadata
	}
	return nil
}

func (m *Model) GetVideoClassificationModelMetadata() *VideoClassificationModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_VideoClassificationModelMetadata); ok {
		return x.VideoClassificationModelMetadata
	}
	return nil
}

func (m *Model) GetTextExtractionModelMetadata() *TextExtractionModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_TextExtractionModelMetadata); ok {
		return x.TextExtractionModelMetadata
	}
	return nil
}

func (m *Model) GetTablesModelMetadata() *TablesModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_TablesModelMetadata); ok {
		return x.TablesModelMetadata
	}
	return nil
}

func (m *Model) GetTextSentimentModelMetadata() *TextSentimentModelMetadata {
	if x, ok := m.GetModelMetadata().(*Model_TextSentimentModelMetadata); ok {
		return x.TextSentimentModelMetadata
	}
	return nil
}

func (m *Model) GetName() string {
	if m != nil {
		return m.Name
	}
	return ""
}

func (m *Model) GetDisplayName() string {
	if m != nil {
		return m.DisplayName
	}
	return ""
}

func (m *Model) GetDatasetId() string {
	if m != nil {
		return m.DatasetId
	}
	return ""
}

func (m *Model) GetCreateTime() *timestamp.Timestamp {
	if m != nil {
		return m.CreateTime
	}
	return nil
}

func (m *Model) GetUpdateTime() *timestamp.Timestamp {
	if m != nil {
		return m.UpdateTime
	}
	return nil
}

func (m *Model) GetDeploymentState() Model_DeploymentState {
	if m != nil {
		return m.DeploymentState
	}
	return Model_DEPLOYMENT_STATE_UNSPECIFIED
}

// XXX_OneofFuncs is for the internal use of the proto package.
func (*Model) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{}) {
	return _Model_OneofMarshaler, _Model_OneofUnmarshaler, _Model_OneofSizer, []interface{}{
		(*Model_TranslationModelMetadata)(nil),
		(*Model_ImageClassificationModelMetadata)(nil),
		(*Model_TextClassificationModelMetadata)(nil),
		(*Model_ImageObjectDetectionModelMetadata)(nil),
		(*Model_VideoClassificationModelMetadata)(nil),
		(*Model_TextExtractionModelMetadata)(nil),
		(*Model_TablesModelMetadata)(nil),
		(*Model_TextSentimentModelMetadata)(nil),
	}
}

func _Model_OneofMarshaler(msg proto.Message, b *proto.Buffer) error {
	m := msg.(*Model)
	// model_metadata
	switch x := m.ModelMetadata.(type) {
	case *Model_TranslationModelMetadata:
		b.EncodeVarint(15<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.TranslationModelMetadata); err != nil {
			return err
		}
	case *Model_ImageClassificationModelMetadata:
		b.EncodeVarint(13<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.ImageClassificationModelMetadata); err != nil {
			return err
		}
	case *Model_TextClassificationModelMetadata:
		b.EncodeVarint(14<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.TextClassificationModelMetadata); err != nil {
			return err
		}
	case *Model_ImageObjectDetectionModelMetadata:
		b.EncodeVarint(20<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.ImageObjectDetectionModelMetadata); err != nil {
			return err
		}
	case *Model_VideoClassificationModelMetadata:
		b.EncodeVarint(23<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.VideoClassificationModelMetadata); err != nil {
			return err
		}
	case *Model_TextExtractionModelMetadata:
		b.EncodeVarint(19<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.TextExtractionModelMetadata); err != nil {
			return err
		}
	case *Model_TablesModelMetadata:
		b.EncodeVarint(24<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.TablesModelMetadata); err != nil {
			return err
		}
	case *Model_TextSentimentModelMetadata:
		b.EncodeVarint(22<<3 | proto.WireBytes)
		if err := b.EncodeMessage(x.TextSentimentModelMetadata); err != nil {
			return err
		}
	case nil:
	default:
		return fmt.Errorf("Model.ModelMetadata has unexpected type %T", x)
	}
	return nil
}

func _Model_OneofUnmarshaler(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error) {
	m := msg.(*Model)
	switch tag {
	case 15: // model_metadata.translation_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(TranslationModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_TranslationModelMetadata{msg}
		return true, err
	case 13: // model_metadata.image_classification_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(ImageClassificationModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_ImageClassificationModelMetadata{msg}
		return true, err
	case 14: // model_metadata.text_classification_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(TextClassificationModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_TextClassificationModelMetadata{msg}
		return true, err
	case 20: // model_metadata.image_object_detection_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(ImageObjectDetectionModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_ImageObjectDetectionModelMetadata{msg}
		return true, err
	case 23: // model_metadata.video_classification_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(VideoClassificationModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_VideoClassificationModelMetadata{msg}
		return true, err
	case 19: // model_metadata.text_extraction_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(TextExtractionModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_TextExtractionModelMetadata{msg}
		return true, err
	case 24: // model_metadata.tables_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(TablesModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_TablesModelMetadata{msg}
		return true, err
	case 22: // model_metadata.text_sentiment_model_metadata
		if wire != proto.WireBytes {
			return true, proto.ErrInternalBadWireType
		}
		msg := new(TextSentimentModelMetadata)
		err := b.DecodeMessage(msg)
		m.ModelMetadata = &Model_TextSentimentModelMetadata{msg}
		return true, err
	default:
		return false, nil
	}
}

func _Model_OneofSizer(msg proto.Message) (n int) {
	m := msg.(*Model)
	// model_metadata
	switch x := m.ModelMetadata.(type) {
	case *Model_TranslationModelMetadata:
		s := proto.Size(x.TranslationModelMetadata)
		n += 1 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_ImageClassificationModelMetadata:
		s := proto.Size(x.ImageClassificationModelMetadata)
		n += 1 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_TextClassificationModelMetadata:
		s := proto.Size(x.TextClassificationModelMetadata)
		n += 1 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_ImageObjectDetectionModelMetadata:
		s := proto.Size(x.ImageObjectDetectionModelMetadata)
		n += 2 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_VideoClassificationModelMetadata:
		s := proto.Size(x.VideoClassificationModelMetadata)
		n += 2 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_TextExtractionModelMetadata:
		s := proto.Size(x.TextExtractionModelMetadata)
		n += 2 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_TablesModelMetadata:
		s := proto.Size(x.TablesModelMetadata)
		n += 2 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case *Model_TextSentimentModelMetadata:
		s := proto.Size(x.TextSentimentModelMetadata)
		n += 2 // tag and wire
		n += proto.SizeVarint(uint64(s))
		n += s
	case nil:
	default:
		panic(fmt.Sprintf("proto: unexpected type %T in oneof", x))
	}
	return n
}

func init() {
	proto.RegisterType((*Model)(nil), "google.cloud.automl.v1beta1.Model")
	proto.RegisterEnum("google.cloud.automl.v1beta1.Model_DeploymentState", Model_DeploymentState_name, Model_DeploymentState_value)
}

func init() {
	proto.RegisterFile("google/cloud/automl/v1beta1/model.proto", fileDescriptor_model_045660f03fa00661)
}

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	0xcf, 0xee, 0xf6, 0x76, 0x7a, 0x96, 0x7d, 0xd8, 0xee, 0x1e, 0x58, 0x7b, 0xcd, 0x57, 0x4d, 0xab,
	0x51, 0x99, 0xa1, 0x0b, 0x64, 0x4e, 0x12, 0x56, 0xa3, 0xa2, 0xd1, 0x32, 0x21, 0x87, 0xed, 0xf1,
	0xf3, 0xec, 0x6e, 0x85, 0x94, 0x2f, 0x2e, 0x7c, 0xf7, 0xab, 0x46, 0xd6, 0x1c, 0x11, 0xaa, 0xfc,
	0x1e, 0x68, 0x1f, 0x76, 0xb2, 0xb2, 0x27, 0x02, 0x16, 0x79, 0x86, 0x18, 0x78, 0xa6, 0xc7, 0x23,
	0x8c, 0xc7, 0x94, 0x25, 0x16, 0xfb, 0xc9, 0xc4, 0xdf, 0x93, 0x6d, 0xf9, 0xf8, 0x6b, 0x76, 0xf9,
	0x35, 0x82, 0xc7, 0x7b, 0x29, 0x74, 0xbc, 0x33, 0x04, 0xd1, 0x0a, 0x8e, 0x8f, 0x24, 0xd4, 0xbf,
	0x8a, 0x5a, 0x8f, 0x7f, 0x07, 0x00, 0x00, 0xff, 0xff, 0xed, 0x1f, 0xbf, 0xcc, 0xa8, 0x07, 0x00,
	0x00,
}
