blob: b1bc3299fd9b6cc50b391206bd59d95e3db8b49e [file] [log] [blame]
// Code generated by protoc-gen-go. DO NOT EDIT.
// source: google/cloud/automl/v1/prediction_service.proto
package automl
import (
context "context"
fmt "fmt"
math "math"
proto "github.com/golang/protobuf/proto"
_ "google.golang.org/genproto/googleapis/api/annotations"
longrunning "google.golang.org/genproto/googleapis/longrunning"
grpc "google.golang.org/grpc"
codes "google.golang.org/grpc/codes"
status "google.golang.org/grpc/status"
)
// 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
// Request message for
// [PredictionService.Predict][google.cloud.automl.v1.PredictionService.Predict].
type PredictRequest struct {
// Name of the model requested to serve the prediction.
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
// Required. Payload to perform a prediction on. The payload must match the
// problem type that the model was trained to solve.
Payload *ExamplePayload `protobuf:"bytes,2,opt,name=payload,proto3" json:"payload,omitempty"`
// Additional domain-specific parameters, any string must be up to 25000
// characters long.
//
// * For Image Classification:
//
// `score_threshold` - (float) A value from 0.0 to 1.0. When the model
// makes predictions for an image, it will only produce results that have
// at least this confidence score. The default is 0.5.
//
// * For Image Object Detection:
// `score_threshold` - (float) When Model detects objects on the image,
// it will only produce bounding boxes which have at least this
// confidence score. Value in 0 to 1 range, default is 0.5.
// `max_bounding_box_count` - (int64) No more than this number of bounding
// boxes will be returned in the response. Default is 100, the
// requested value may be limited by server.
Params map[string]string `protobuf:"bytes,3,rep,name=params,proto3" json:"params,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 *PredictRequest) Reset() { *m = PredictRequest{} }
func (m *PredictRequest) String() string { return proto.CompactTextString(m) }
func (*PredictRequest) ProtoMessage() {}
func (*PredictRequest) Descriptor() ([]byte, []int) {
return fileDescriptor_a60105ec759f54a4, []int{0}
}
func (m *PredictRequest) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_PredictRequest.Unmarshal(m, b)
}
func (m *PredictRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_PredictRequest.Marshal(b, m, deterministic)
}
func (m *PredictRequest) XXX_Merge(src proto.Message) {
xxx_messageInfo_PredictRequest.Merge(m, src)
}
func (m *PredictRequest) XXX_Size() int {
return xxx_messageInfo_PredictRequest.Size(m)
}
func (m *PredictRequest) XXX_DiscardUnknown() {
xxx_messageInfo_PredictRequest.DiscardUnknown(m)
}
var xxx_messageInfo_PredictRequest proto.InternalMessageInfo
func (m *PredictRequest) GetName() string {
if m != nil {
return m.Name
}
return ""
}
func (m *PredictRequest) GetPayload() *ExamplePayload {
if m != nil {
return m.Payload
}
return nil
}
func (m *PredictRequest) GetParams() map[string]string {
if m != nil {
return m.Params
}
return nil
}
// Response message for
// [PredictionService.Predict][google.cloud.automl.v1.PredictionService.Predict].
type PredictResponse struct {
// Prediction result.
// Translation and Text Sentiment will return precisely one payload.
Payload []*AnnotationPayload `protobuf:"bytes,1,rep,name=payload,proto3" json:"payload,omitempty"`
// The preprocessed example that AutoML actually makes prediction on.
// Empty if AutoML does not preprocess the input example.
// * For Text Extraction:
// If the input is a .pdf file, the OCR'ed text will be provided in
// [document_text][google.cloud.automl.v1.Document.document_text].
//
// * For Text Classification:
// If the input is a .pdf file, the OCR'ed trucated text will be provided in
// [document_text][google.cloud.automl.v1.Document.document_text].
//
// * For Text Sentiment:
// If the input is a .pdf file, the OCR'ed trucated text will be provided in
// [document_text][google.cloud.automl.v1.Document.document_text].
PreprocessedInput *ExamplePayload `protobuf:"bytes,3,opt,name=preprocessed_input,json=preprocessedInput,proto3" json:"preprocessed_input,omitempty"`
// Additional domain-specific prediction response metadata.
//
// * For Image Object Detection:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// image could have been returned.
//
// * For Text Sentiment:
// `sentiment_score` - (float, deprecated) A value between -1 and 1,
// -1 maps to least positive sentiment, while 1 maps to the most positive
// one and the higher the score, the more positive the sentiment in the
// document is. Yet these values are relative to the training data, so
// e.g. if all data was positive then -1 will be also positive (though
// the least).
// The sentiment_score shouldn't be confused with "score" or "magnitude"
// from the previous Natural Language Sentiment Analysis API.
Metadata map[string]string `protobuf:"bytes,2,rep,name=metadata,proto3" json:"metadata,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 *PredictResponse) Reset() { *m = PredictResponse{} }
func (m *PredictResponse) String() string { return proto.CompactTextString(m) }
func (*PredictResponse) ProtoMessage() {}
func (*PredictResponse) Descriptor() ([]byte, []int) {
return fileDescriptor_a60105ec759f54a4, []int{1}
}
func (m *PredictResponse) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_PredictResponse.Unmarshal(m, b)
}
func (m *PredictResponse) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_PredictResponse.Marshal(b, m, deterministic)
}
func (m *PredictResponse) XXX_Merge(src proto.Message) {
xxx_messageInfo_PredictResponse.Merge(m, src)
}
func (m *PredictResponse) XXX_Size() int {
return xxx_messageInfo_PredictResponse.Size(m)
}
func (m *PredictResponse) XXX_DiscardUnknown() {
xxx_messageInfo_PredictResponse.DiscardUnknown(m)
}
var xxx_messageInfo_PredictResponse proto.InternalMessageInfo
func (m *PredictResponse) GetPayload() []*AnnotationPayload {
if m != nil {
return m.Payload
}
return nil
}
func (m *PredictResponse) GetPreprocessedInput() *ExamplePayload {
if m != nil {
return m.PreprocessedInput
}
return nil
}
func (m *PredictResponse) GetMetadata() map[string]string {
if m != nil {
return m.Metadata
}
return nil
}
// Request message for
// [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict].
type BatchPredictRequest struct {
// Name of the model requested to serve the batch prediction.
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
// Required. The input configuration for batch prediction.
InputConfig *BatchPredictInputConfig `protobuf:"bytes,3,opt,name=input_config,json=inputConfig,proto3" json:"input_config,omitempty"`
// Required. The Configuration specifying where output predictions should
// be written.
OutputConfig *BatchPredictOutputConfig `protobuf:"bytes,4,opt,name=output_config,json=outputConfig,proto3" json:"output_config,omitempty"`
// Additional domain-specific parameters for the predictions, any string must
// be up to 25000 characters long.
//
// * For Text Classification:
//
// `score_threshold` - (float) A value from 0.0 to 1.0. When the model
// makes predictions for a text snippet, it will only produce results
// that have at least this confidence score. The default is 0.5.
//
// * For Image Classification:
//
// `score_threshold` - (float) A value from 0.0 to 1.0. When the model
// makes predictions for an image, it will only produce results that
// have at least this confidence score. The default is 0.5.
//
// * For Image Object Detection:
//
// `score_threshold` - (float) When Model detects objects on the image,
// it will only produce bounding boxes which have at least this
// confidence score. Value in 0 to 1 range, default is 0.5.
// `max_bounding_box_count` - (int64) No more than this number of bounding
// boxes will be produced per image. Default is 100, the
// requested value may be limited by server.
Params map[string]string `protobuf:"bytes,5,rep,name=params,proto3" json:"params,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 *BatchPredictRequest) Reset() { *m = BatchPredictRequest{} }
func (m *BatchPredictRequest) String() string { return proto.CompactTextString(m) }
func (*BatchPredictRequest) ProtoMessage() {}
func (*BatchPredictRequest) Descriptor() ([]byte, []int) {
return fileDescriptor_a60105ec759f54a4, []int{2}
}
func (m *BatchPredictRequest) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_BatchPredictRequest.Unmarshal(m, b)
}
func (m *BatchPredictRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_BatchPredictRequest.Marshal(b, m, deterministic)
}
func (m *BatchPredictRequest) XXX_Merge(src proto.Message) {
xxx_messageInfo_BatchPredictRequest.Merge(m, src)
}
func (m *BatchPredictRequest) XXX_Size() int {
return xxx_messageInfo_BatchPredictRequest.Size(m)
}
func (m *BatchPredictRequest) XXX_DiscardUnknown() {
xxx_messageInfo_BatchPredictRequest.DiscardUnknown(m)
}
var xxx_messageInfo_BatchPredictRequest proto.InternalMessageInfo
func (m *BatchPredictRequest) GetName() string {
if m != nil {
return m.Name
}
return ""
}
func (m *BatchPredictRequest) GetInputConfig() *BatchPredictInputConfig {
if m != nil {
return m.InputConfig
}
return nil
}
func (m *BatchPredictRequest) GetOutputConfig() *BatchPredictOutputConfig {
if m != nil {
return m.OutputConfig
}
return nil
}
func (m *BatchPredictRequest) GetParams() map[string]string {
if m != nil {
return m.Params
}
return nil
}
// Result of the Batch Predict. This message is returned in
// [response][google.longrunning.Operation.response] of the operation returned
// by the
// [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict].
type BatchPredictResult struct {
// Additional domain-specific prediction response metadata.
//
// * For Image Object Detection:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// image could have been returned.
Metadata map[string]string `protobuf:"bytes,1,rep,name=metadata,proto3" json:"metadata,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 *BatchPredictResult) Reset() { *m = BatchPredictResult{} }
func (m *BatchPredictResult) String() string { return proto.CompactTextString(m) }
func (*BatchPredictResult) ProtoMessage() {}
func (*BatchPredictResult) Descriptor() ([]byte, []int) {
return fileDescriptor_a60105ec759f54a4, []int{3}
}
func (m *BatchPredictResult) XXX_Unmarshal(b []byte) error {
return xxx_messageInfo_BatchPredictResult.Unmarshal(m, b)
}
func (m *BatchPredictResult) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
return xxx_messageInfo_BatchPredictResult.Marshal(b, m, deterministic)
}
func (m *BatchPredictResult) XXX_Merge(src proto.Message) {
xxx_messageInfo_BatchPredictResult.Merge(m, src)
}
func (m *BatchPredictResult) XXX_Size() int {
return xxx_messageInfo_BatchPredictResult.Size(m)
}
func (m *BatchPredictResult) XXX_DiscardUnknown() {
xxx_messageInfo_BatchPredictResult.DiscardUnknown(m)
}
var xxx_messageInfo_BatchPredictResult proto.InternalMessageInfo
func (m *BatchPredictResult) GetMetadata() map[string]string {
if m != nil {
return m.Metadata
}
return nil
}
func init() {
proto.RegisterType((*PredictRequest)(nil), "google.cloud.automl.v1.PredictRequest")
proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1.PredictRequest.ParamsEntry")
proto.RegisterType((*PredictResponse)(nil), "google.cloud.automl.v1.PredictResponse")
proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1.PredictResponse.MetadataEntry")
proto.RegisterType((*BatchPredictRequest)(nil), "google.cloud.automl.v1.BatchPredictRequest")
proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1.BatchPredictRequest.ParamsEntry")
proto.RegisterType((*BatchPredictResult)(nil), "google.cloud.automl.v1.BatchPredictResult")
proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1.BatchPredictResult.MetadataEntry")
}
func init() {
proto.RegisterFile("google/cloud/automl/v1/prediction_service.proto", fileDescriptor_a60105ec759f54a4)
}
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// Reference imports to suppress errors if they are not otherwise used.
var _ context.Context
var _ grpc.ClientConnInterface
// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
const _ = grpc.SupportPackageIsVersion6
// PredictionServiceClient is the client API for PredictionService service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
type PredictionServiceClient interface {
// Perform an online prediction. The prediction result will be directly
// returned in the response.
// Available for following ML problems, and their expected request payloads:
// * Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Text Classification - TextSnippet, content up to 60,000 characters,
// UTF-8 encoded.
// * Text Extraction - TextSnippet, content up to 30,000 characters,
// UTF-8 NFC encoded.
// * Translation - TextSnippet, content up to 25,000 characters, UTF-8
// encoded.
// * Text Sentiment - TextSnippet, content up 500 characters, UTF-8
// encoded.
Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*PredictResponse, error)
// Perform a batch prediction. Unlike the online
// [Predict][google.cloud.automl.v1.PredictionService.Predict], batch
// prediction result won't be immediately available in the response. Instead,
// a long running operation object is returned. User can poll the operation
// result via [GetOperation][google.longrunning.Operations.GetOperation]
// method. Once the operation is done,
// [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned
// in the [response][google.longrunning.Operation.response] field. Available
// for following ML problems:
// * Image Classification
// * Image Object Detection
// * Text Extraction
BatchPredict(ctx context.Context, in *BatchPredictRequest, opts ...grpc.CallOption) (*longrunning.Operation, error)
}
type predictionServiceClient struct {
cc grpc.ClientConnInterface
}
func NewPredictionServiceClient(cc grpc.ClientConnInterface) PredictionServiceClient {
return &predictionServiceClient{cc}
}
func (c *predictionServiceClient) Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*PredictResponse, error) {
out := new(PredictResponse)
err := c.cc.Invoke(ctx, "/google.cloud.automl.v1.PredictionService/Predict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *predictionServiceClient) BatchPredict(ctx context.Context, in *BatchPredictRequest, opts ...grpc.CallOption) (*longrunning.Operation, error) {
out := new(longrunning.Operation)
err := c.cc.Invoke(ctx, "/google.cloud.automl.v1.PredictionService/BatchPredict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
// PredictionServiceServer is the server API for PredictionService service.
type PredictionServiceServer interface {
// Perform an online prediction. The prediction result will be directly
// returned in the response.
// Available for following ML problems, and their expected request payloads:
// * Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Text Classification - TextSnippet, content up to 60,000 characters,
// UTF-8 encoded.
// * Text Extraction - TextSnippet, content up to 30,000 characters,
// UTF-8 NFC encoded.
// * Translation - TextSnippet, content up to 25,000 characters, UTF-8
// encoded.
// * Text Sentiment - TextSnippet, content up 500 characters, UTF-8
// encoded.
Predict(context.Context, *PredictRequest) (*PredictResponse, error)
// Perform a batch prediction. Unlike the online
// [Predict][google.cloud.automl.v1.PredictionService.Predict], batch
// prediction result won't be immediately available in the response. Instead,
// a long running operation object is returned. User can poll the operation
// result via [GetOperation][google.longrunning.Operations.GetOperation]
// method. Once the operation is done,
// [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned
// in the [response][google.longrunning.Operation.response] field. Available
// for following ML problems:
// * Image Classification
// * Image Object Detection
// * Text Extraction
BatchPredict(context.Context, *BatchPredictRequest) (*longrunning.Operation, error)
}
// UnimplementedPredictionServiceServer can be embedded to have forward compatible implementations.
type UnimplementedPredictionServiceServer struct {
}
func (*UnimplementedPredictionServiceServer) Predict(ctx context.Context, req *PredictRequest) (*PredictResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
}
func (*UnimplementedPredictionServiceServer) BatchPredict(ctx context.Context, req *BatchPredictRequest) (*longrunning.Operation, error) {
return nil, status.Errorf(codes.Unimplemented, "method BatchPredict not implemented")
}
func RegisterPredictionServiceServer(s *grpc.Server, srv PredictionServiceServer) {
s.RegisterService(&_PredictionService_serviceDesc, srv)
}
func _PredictionService_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).Predict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.automl.v1.PredictionService/Predict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).Predict(ctx, req.(*PredictRequest))
}
return interceptor(ctx, in, info, handler)
}
func _PredictionService_BatchPredict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(BatchPredictRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).BatchPredict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.automl.v1.PredictionService/BatchPredict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).BatchPredict(ctx, req.(*BatchPredictRequest))
}
return interceptor(ctx, in, info, handler)
}
var _PredictionService_serviceDesc = grpc.ServiceDesc{
ServiceName: "google.cloud.automl.v1.PredictionService",
HandlerType: (*PredictionServiceServer)(nil),
Methods: []grpc.MethodDesc{
{
MethodName: "Predict",
Handler: _PredictionService_Predict_Handler,
},
{
MethodName: "BatchPredict",
Handler: _PredictionService_BatchPredict_Handler,
},
},
Streams: []grpc.StreamDesc{},
Metadata: "google/cloud/automl/v1/prediction_service.proto",
}