googleapis/cloud/automl/v1beta1/image.pb.go

// Code generated by protoc-gen-go. DO NOT EDIT.
// source: google/cloud/automl/v1beta1/image.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 _ "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

// Dataset metadata that is specific to image classification.
type ImageClassificationDatasetMetadata struct {
	// Required.
	// Type of the classification problem.
	ClassificationType   ClassificationType `protobuf:"varint,1,opt,name=classification_type,json=classificationType,proto3,enum=google.cloud.automl.v1beta1.ClassificationType" json:"classification_type,omitempty"`
	XXX_NoUnkeyedLiteral struct{}           `json:"-"`
	XXX_unrecognized     []byte             `json:"-"`
	XXX_sizecache        int32              `json:"-"`
}

func (m *ImageClassificationDatasetMetadata) Reset()         { *m = ImageClassificationDatasetMetadata{} }
func (m *ImageClassificationDatasetMetadata) String() string { return proto.CompactTextString(m) }
func (*ImageClassificationDatasetMetadata) ProtoMessage()    {}
func (*ImageClassificationDatasetMetadata) Descriptor() ([]byte, []int) {
	return fileDescriptor_image_154474385dd5e971, []int{0}
}
func (m *ImageClassificationDatasetMetadata) XXX_Unmarshal(b []byte) error {
	return xxx_messageInfo_ImageClassificationDatasetMetadata.Unmarshal(m, b)
}
func (m *ImageClassificationDatasetMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
	return xxx_messageInfo_ImageClassificationDatasetMetadata.Marshal(b, m, deterministic)
}
func (dst *ImageClassificationDatasetMetadata) XXX_Merge(src proto.Message) {
	xxx_messageInfo_ImageClassificationDatasetMetadata.Merge(dst, src)
}
func (m *ImageClassificationDatasetMetadata) XXX_Size() int {
	return xxx_messageInfo_ImageClassificationDatasetMetadata.Size(m)
}
func (m *ImageClassificationDatasetMetadata) XXX_DiscardUnknown() {
	xxx_messageInfo_ImageClassificationDatasetMetadata.DiscardUnknown(m)
}

var xxx_messageInfo_ImageClassificationDatasetMetadata proto.InternalMessageInfo

func (m *ImageClassificationDatasetMetadata) GetClassificationType() ClassificationType {
	if m != nil {
		return m.ClassificationType
	}
	return ClassificationType_CLASSIFICATION_TYPE_UNSPECIFIED
}

// Model metadata for image classification.
type ImageClassificationModelMetadata struct {
	// Optional. The ID of the `base` model. If it is specified, the new model
	// will be created based on the `base` model. Otherwise, the new model will be
	// created from scratch. The `base` model is expected to be in the same
	// `project` and `location` as the new model to create.
	BaseModelId string `protobuf:"bytes,1,opt,name=base_model_id,json=baseModelId,proto3" json:"base_model_id,omitempty"`
	// Required. The train budget of creating this model. The actual
	// `train_cost` will be equal or less than this value.
	TrainBudget int64 `protobuf:"varint,2,opt,name=train_budget,json=trainBudget,proto3" json:"train_budget,omitempty"`
	// Output only. The actual train cost of creating this model. If this
	// model is created from a `base` model, the train cost used to create the
	// `base` model are not included.
	TrainCost int64 `protobuf:"varint,3,opt,name=train_cost,json=trainCost,proto3" json:"train_cost,omitempty"`
	// Output only. The reason that this create model operation stopped,
	// e.g. BUDGET_REACHED, CONVERGED.
	StopReason           string   `protobuf:"bytes,5,opt,name=stop_reason,json=stopReason,proto3" json:"stop_reason,omitempty"`
	XXX_NoUnkeyedLiteral struct{} `json:"-"`
	XXX_unrecognized     []byte   `json:"-"`
	XXX_sizecache        int32    `json:"-"`
}

func (m *ImageClassificationModelMetadata) Reset()         { *m = ImageClassificationModelMetadata{} }
func (m *ImageClassificationModelMetadata) String() string { return proto.CompactTextString(m) }
func (*ImageClassificationModelMetadata) ProtoMessage()    {}
func (*ImageClassificationModelMetadata) Descriptor() ([]byte, []int) {
	return fileDescriptor_image_154474385dd5e971, []int{1}
}
func (m *ImageClassificationModelMetadata) XXX_Unmarshal(b []byte) error {
	return xxx_messageInfo_ImageClassificationModelMetadata.Unmarshal(m, b)
}
func (m *ImageClassificationModelMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
	return xxx_messageInfo_ImageClassificationModelMetadata.Marshal(b, m, deterministic)
}
func (dst *ImageClassificationModelMetadata) XXX_Merge(src proto.Message) {
	xxx_messageInfo_ImageClassificationModelMetadata.Merge(dst, src)
}
func (m *ImageClassificationModelMetadata) XXX_Size() int {
	return xxx_messageInfo_ImageClassificationModelMetadata.Size(m)
}
func (m *ImageClassificationModelMetadata) XXX_DiscardUnknown() {
	xxx_messageInfo_ImageClassificationModelMetadata.DiscardUnknown(m)
}

var xxx_messageInfo_ImageClassificationModelMetadata proto.InternalMessageInfo

func (m *ImageClassificationModelMetadata) GetBaseModelId() string {
	if m != nil {
		return m.BaseModelId
	}
	return ""
}

func (m *ImageClassificationModelMetadata) GetTrainBudget() int64 {
	if m != nil {
		return m.TrainBudget
	}
	return 0
}

func (m *ImageClassificationModelMetadata) GetTrainCost() int64 {
	if m != nil {
		return m.TrainCost
	}
	return 0
}

func (m *ImageClassificationModelMetadata) GetStopReason() string {
	if m != nil {
		return m.StopReason
	}
	return ""
}

func init() {
	proto.RegisterType((*ImageClassificationDatasetMetadata)(nil), "google.cloud.automl.v1beta1.ImageClassificationDatasetMetadata")
	proto.RegisterType((*ImageClassificationModelMetadata)(nil), "google.cloud.automl.v1beta1.ImageClassificationModelMetadata")
}

func init() {
	proto.RegisterFile("google/cloud/automl/v1beta1/image.proto", fileDescriptor_image_154474385dd5e971)
}

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