| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // source: google/cloud/automl/v1/text.proto |
| |
| package automl |
| |
| import ( |
| fmt "fmt" |
| math "math" |
| |
| proto "github.com/golang/protobuf/proto" |
| _ "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 |
| |
| // Dataset metadata for classification. |
| type TextClassificationDatasetMetadata struct { |
| // Required. Type of the classification problem. |
| ClassificationType ClassificationType `protobuf:"varint,1,opt,name=classification_type,json=classificationType,proto3,enum=google.cloud.automl.v1.ClassificationType" json:"classification_type,omitempty"` |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextClassificationDatasetMetadata) Reset() { *m = TextClassificationDatasetMetadata{} } |
| func (m *TextClassificationDatasetMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextClassificationDatasetMetadata) ProtoMessage() {} |
| func (*TextClassificationDatasetMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{0} |
| } |
| |
| func (m *TextClassificationDatasetMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextClassificationDatasetMetadata.Unmarshal(m, b) |
| } |
| func (m *TextClassificationDatasetMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextClassificationDatasetMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextClassificationDatasetMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextClassificationDatasetMetadata.Merge(m, src) |
| } |
| func (m *TextClassificationDatasetMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextClassificationDatasetMetadata.Size(m) |
| } |
| func (m *TextClassificationDatasetMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextClassificationDatasetMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextClassificationDatasetMetadata proto.InternalMessageInfo |
| |
| func (m *TextClassificationDatasetMetadata) GetClassificationType() ClassificationType { |
| if m != nil { |
| return m.ClassificationType |
| } |
| return ClassificationType_CLASSIFICATION_TYPE_UNSPECIFIED |
| } |
| |
| // Model metadata that is specific to text classification. |
| type TextClassificationModelMetadata struct { |
| // Output only. Classification type of the dataset used to train this model. |
| ClassificationType ClassificationType `protobuf:"varint,3,opt,name=classification_type,json=classificationType,proto3,enum=google.cloud.automl.v1.ClassificationType" json:"classification_type,omitempty"` |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextClassificationModelMetadata) Reset() { *m = TextClassificationModelMetadata{} } |
| func (m *TextClassificationModelMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextClassificationModelMetadata) ProtoMessage() {} |
| func (*TextClassificationModelMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{1} |
| } |
| |
| func (m *TextClassificationModelMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextClassificationModelMetadata.Unmarshal(m, b) |
| } |
| func (m *TextClassificationModelMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextClassificationModelMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextClassificationModelMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextClassificationModelMetadata.Merge(m, src) |
| } |
| func (m *TextClassificationModelMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextClassificationModelMetadata.Size(m) |
| } |
| func (m *TextClassificationModelMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextClassificationModelMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextClassificationModelMetadata proto.InternalMessageInfo |
| |
| func (m *TextClassificationModelMetadata) GetClassificationType() ClassificationType { |
| if m != nil { |
| return m.ClassificationType |
| } |
| return ClassificationType_CLASSIFICATION_TYPE_UNSPECIFIED |
| } |
| |
| // Dataset metadata that is specific to text extraction |
| type TextExtractionDatasetMetadata struct { |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextExtractionDatasetMetadata) Reset() { *m = TextExtractionDatasetMetadata{} } |
| func (m *TextExtractionDatasetMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextExtractionDatasetMetadata) ProtoMessage() {} |
| func (*TextExtractionDatasetMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{2} |
| } |
| |
| func (m *TextExtractionDatasetMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextExtractionDatasetMetadata.Unmarshal(m, b) |
| } |
| func (m *TextExtractionDatasetMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextExtractionDatasetMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextExtractionDatasetMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextExtractionDatasetMetadata.Merge(m, src) |
| } |
| func (m *TextExtractionDatasetMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextExtractionDatasetMetadata.Size(m) |
| } |
| func (m *TextExtractionDatasetMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextExtractionDatasetMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextExtractionDatasetMetadata proto.InternalMessageInfo |
| |
| // Model metadata that is specific to text extraction. |
| type TextExtractionModelMetadata struct { |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextExtractionModelMetadata) Reset() { *m = TextExtractionModelMetadata{} } |
| func (m *TextExtractionModelMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextExtractionModelMetadata) ProtoMessage() {} |
| func (*TextExtractionModelMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{3} |
| } |
| |
| func (m *TextExtractionModelMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextExtractionModelMetadata.Unmarshal(m, b) |
| } |
| func (m *TextExtractionModelMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextExtractionModelMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextExtractionModelMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextExtractionModelMetadata.Merge(m, src) |
| } |
| func (m *TextExtractionModelMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextExtractionModelMetadata.Size(m) |
| } |
| func (m *TextExtractionModelMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextExtractionModelMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextExtractionModelMetadata proto.InternalMessageInfo |
| |
| // Dataset metadata for text sentiment. |
| type TextSentimentDatasetMetadata struct { |
| // Required. A sentiment is expressed as an integer ordinal, where higher |
| // value means a more positive sentiment. The range of sentiments that will be |
| // used is between 0 and sentiment_max (inclusive on both ends), and all the |
| // values in the range must be represented in the dataset before a model can |
| // be created. sentiment_max value must be between 1 and 10 (inclusive). |
| SentimentMax int32 `protobuf:"varint,1,opt,name=sentiment_max,json=sentimentMax,proto3" json:"sentiment_max,omitempty"` |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextSentimentDatasetMetadata) Reset() { *m = TextSentimentDatasetMetadata{} } |
| func (m *TextSentimentDatasetMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextSentimentDatasetMetadata) ProtoMessage() {} |
| func (*TextSentimentDatasetMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{4} |
| } |
| |
| func (m *TextSentimentDatasetMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextSentimentDatasetMetadata.Unmarshal(m, b) |
| } |
| func (m *TextSentimentDatasetMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextSentimentDatasetMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextSentimentDatasetMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextSentimentDatasetMetadata.Merge(m, src) |
| } |
| func (m *TextSentimentDatasetMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextSentimentDatasetMetadata.Size(m) |
| } |
| func (m *TextSentimentDatasetMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextSentimentDatasetMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextSentimentDatasetMetadata proto.InternalMessageInfo |
| |
| func (m *TextSentimentDatasetMetadata) GetSentimentMax() int32 { |
| if m != nil { |
| return m.SentimentMax |
| } |
| return 0 |
| } |
| |
| // Model metadata that is specific to text sentiment. |
| type TextSentimentModelMetadata struct { |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *TextSentimentModelMetadata) Reset() { *m = TextSentimentModelMetadata{} } |
| func (m *TextSentimentModelMetadata) String() string { return proto.CompactTextString(m) } |
| func (*TextSentimentModelMetadata) ProtoMessage() {} |
| func (*TextSentimentModelMetadata) Descriptor() ([]byte, []int) { |
| return fileDescriptor_ffc003fc1ed6094b, []int{5} |
| } |
| |
| func (m *TextSentimentModelMetadata) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_TextSentimentModelMetadata.Unmarshal(m, b) |
| } |
| func (m *TextSentimentModelMetadata) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_TextSentimentModelMetadata.Marshal(b, m, deterministic) |
| } |
| func (m *TextSentimentModelMetadata) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_TextSentimentModelMetadata.Merge(m, src) |
| } |
| func (m *TextSentimentModelMetadata) XXX_Size() int { |
| return xxx_messageInfo_TextSentimentModelMetadata.Size(m) |
| } |
| func (m *TextSentimentModelMetadata) XXX_DiscardUnknown() { |
| xxx_messageInfo_TextSentimentModelMetadata.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_TextSentimentModelMetadata proto.InternalMessageInfo |
| |
| func init() { |
| proto.RegisterType((*TextClassificationDatasetMetadata)(nil), "google.cloud.automl.v1.TextClassificationDatasetMetadata") |
| proto.RegisterType((*TextClassificationModelMetadata)(nil), "google.cloud.automl.v1.TextClassificationModelMetadata") |
| proto.RegisterType((*TextExtractionDatasetMetadata)(nil), "google.cloud.automl.v1.TextExtractionDatasetMetadata") |
| proto.RegisterType((*TextExtractionModelMetadata)(nil), "google.cloud.automl.v1.TextExtractionModelMetadata") |
| proto.RegisterType((*TextSentimentDatasetMetadata)(nil), "google.cloud.automl.v1.TextSentimentDatasetMetadata") |
| proto.RegisterType((*TextSentimentModelMetadata)(nil), "google.cloud.automl.v1.TextSentimentModelMetadata") |
| } |
| |
| func init() { |
| proto.RegisterFile("google/cloud/automl/v1/text.proto", fileDescriptor_ffc003fc1ed6094b) |
| } |
| |
| var fileDescriptor_ffc003fc1ed6094b = []byte{ |
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