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// Code generated by protoc-gen-go. DO NOT EDIT.
// source: google/cloud/automl/v1/model.proto
package automl
import (
fmt "fmt"
math "math"
proto "github.com/golang/protobuf/proto"
timestamp "github.com/golang/protobuf/ptypes/timestamp"
_ "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.ProtoPackageIsVersion3 // 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_452845e4ed6fce9d, []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_TextExtractionModelMetadata
// *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 the model training finished and can be used for prediction.
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.v1.Model_DeploymentState" json:"deployment_state,omitempty"`
// Used to perform a consistent read-modify-write updates. If not set, a blind
// "overwrite" update happens.
Etag string `protobuf:"bytes,10,opt,name=etag,proto3" json:"etag,omitempty"`
// Optional. The labels with user-defined metadata to organize your model.
//
// Label keys and values can be no longer than 64 characters
// (Unicode codepoints), can only contain lowercase letters, numeric
// characters, underscores and dashes. International characters are allowed.
// Label values are optional. Label keys must start with a letter.
//
// See https://goo.gl/xmQnxf for more information on and examples of labels.
Labels map[string]string `protobuf:"bytes,34,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
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_452845e4ed6fce9d, []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 (m *Model) XXX_Merge(src proto.Message) {
xxx_messageInfo_Model.Merge(m, 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_TextExtractionModelMetadata struct {
TextExtractionModelMetadata *TextExtractionModelMetadata `protobuf:"bytes,19,opt,name=text_extraction_model_metadata,json=textExtractionModelMetadata,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_TextExtractionModelMetadata) 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) GetTextExtractionModelMetadata() *TextExtractionModelMetadata {
if x, ok := m.GetModelMetadata().(*Model_TextExtractionModelMetadata); ok {
return x.TextExtractionModelMetadata
}
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
}
func (m *Model) GetEtag() string {
if m != nil {
return m.Etag
}
return ""
}
func (m *Model) GetLabels() map[string]string {
if m != nil {
return m.Labels
}
return nil
}
// XXX_OneofWrappers is for the internal use of the proto package.
func (*Model) XXX_OneofWrappers() []interface{} {
return []interface{}{
(*Model_TranslationModelMetadata)(nil),
(*Model_ImageClassificationModelMetadata)(nil),
(*Model_TextClassificationModelMetadata)(nil),
(*Model_ImageObjectDetectionModelMetadata)(nil),
(*Model_TextExtractionModelMetadata)(nil),
(*Model_TextSentimentModelMetadata)(nil),
}
}
func init() {
proto.RegisterEnum("google.cloud.automl.v1.Model_DeploymentState", Model_DeploymentState_name, Model_DeploymentState_value)
proto.RegisterType((*Model)(nil), "google.cloud.automl.v1.Model")
proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1.Model.LabelsEntry")
}
func init() {
proto.RegisterFile("google/cloud/automl/v1/model.proto", fileDescriptor_452845e4ed6fce9d)
}
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