// Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.22.0
// protoc v3.11.2
// source: google/cloud/automl/v1beta1/prediction_service.proto
package automl
import (
context "context"
reflect "reflect"
sync "sync"
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"
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
)
const (
// Verify that this generated code is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
// Verify that runtime/protoimpl is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
// This is a compile-time assertion that a sufficiently up-to-date version
// of the legacy proto package is being used.
const _ = proto.ProtoPackageIsVersion4
// Request message for [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
type PredictRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. 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.
// * For Tables:
// feature_importance - (boolean) Whether feature importance
// should be populated in the returned TablesAnnotation.
// The default is false.
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"`
}
func (x *PredictRequest) Reset() {
*x = PredictRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *PredictRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*PredictRequest) ProtoMessage() {}
func (x *PredictRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[0]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use PredictRequest.ProtoReflect.Descriptor instead.
func (*PredictRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescGZIP(), []int{0}
}
func (x *PredictRequest) GetName() string {
if x != nil {
return x.Name
}
return ""
}
func (x *PredictRequest) GetPayload() *ExamplePayload {
if x != nil {
return x.Payload
}
return nil
}
func (x *PredictRequest) GetParams() map[string]string {
if x != nil {
return x.Params
}
return nil
}
// Response message for [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
type PredictResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// 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.v1beta1.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"`
}
func (x *PredictResponse) Reset() {
*x = PredictResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *PredictResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*PredictResponse) ProtoMessage() {}
func (x *PredictResponse) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[1]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use PredictResponse.ProtoReflect.Descriptor instead.
func (*PredictResponse) Descriptor() ([]byte, []int) {
return file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescGZIP(), []int{1}
}
func (x *PredictResponse) GetPayload() []*AnnotationPayload {
if x != nil {
return x.Payload
}
return nil
}
func (x *PredictResponse) GetPreprocessedInput() *ExamplePayload {
if x != nil {
return x.PreprocessedInput
}
return nil
}
func (x *PredictResponse) GetMetadata() map[string]string {
if x != nil {
return x.Metadata
}
return nil
}
// Request message for [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
type BatchPredictRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. 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"`
// Required. 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.
//
// * For Video Classification :
//
// `score_threshold` - (float) A value from 0.0 to 1.0. When the model
// makes predictions for a video, it will only produce results that
// have at least this confidence score. The default is 0.5.
// `segment_classification` - (boolean) Set to true to request
// segment-level classification. AutoML Video Intelligence returns
// labels and their confidence scores for the entire segment of the
// video that user specified in the request configuration.
// The default is "true".
// `shot_classification` - (boolean) Set to true to request shot-level
// classification. AutoML Video Intelligence determines the boundaries
// for each camera shot in the entire segment of the video that user
// specified in the request configuration. AutoML Video Intelligence
// then returns labels and their confidence scores for each detected
// shot, along with the start and end time of the shot.
// WARNING: Model evaluation is not done for this classification type,
// the quality of it depends on training data, but there are no metrics
// provided to describe that quality. The default is "false".
// `1s_interval_classification` - (boolean) Set to true to request
// classification for a video at one-second intervals. AutoML Video
// Intelligence returns labels and their confidence scores for each
// second of the entire segment of the video that user specified in the
// request configuration.
// WARNING: Model evaluation is not done for this classification
// type, the quality of it depends on training data, but there are no
// metrics provided to describe that quality. The default is
// "false".
//
// * For Tables:
//
// feature_importance - (boolean) Whether feature importance
// should be populated in the returned TablesAnnotations. The
// default is false.
//
// * For Video Object Tracking:
//
// `score_threshold` - (float) When Model detects objects on video frames,
// 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 per frame. Default is 100, the requested
// value may be limited by server.
// `min_bounding_box_size` - (float) Only bounding boxes with shortest edge
// at least that long as a relative value of video frame size will be
// returned. Value in 0 to 1 range. Default is 0.
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"`
}
func (x *BatchPredictRequest) Reset() {
*x = BatchPredictRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictRequest) ProtoMessage() {}
func (x *BatchPredictRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[2]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use BatchPredictRequest.ProtoReflect.Descriptor instead.
func (*BatchPredictRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescGZIP(), []int{2}
}
func (x *BatchPredictRequest) GetName() string {
if x != nil {
return x.Name
}
return ""
}
func (x *BatchPredictRequest) GetInputConfig() *BatchPredictInputConfig {
if x != nil {
return x.InputConfig
}
return nil
}
func (x *BatchPredictRequest) GetOutputConfig() *BatchPredictOutputConfig {
if x != nil {
return x.OutputConfig
}
return nil
}
func (x *BatchPredictRequest) GetParams() map[string]string {
if x != nil {
return x.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.v1beta1.PredictionService.BatchPredict].
type BatchPredictResult struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// 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 Video Object Tracking:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// frame 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"`
}
func (x *BatchPredictResult) Reset() {
*x = BatchPredictResult{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictResult) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictResult) ProtoMessage() {}
func (x *BatchPredictResult) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[3]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use BatchPredictResult.ProtoReflect.Descriptor instead.
func (*BatchPredictResult) Descriptor() ([]byte, []int) {
return file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescGZIP(), []int{3}
}
func (x *BatchPredictResult) GetMetadata() map[string]string {
if x != nil {
return x.Metadata
}
return nil
}
var File_google_cloud_automl_v1beta1_prediction_service_proto protoreflect.FileDescriptor
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}
var (
file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescOnce sync.Once
file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescData = file_google_cloud_automl_v1beta1_prediction_service_proto_rawDesc
)
func file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescGZIP() []byte {
file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescOnce.Do(func() {
file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescData)
})
return file_google_cloud_automl_v1beta1_prediction_service_proto_rawDescData
}
var file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes = make([]protoimpl.MessageInfo, 8)
var file_google_cloud_automl_v1beta1_prediction_service_proto_goTypes = []interface{}{
(*PredictRequest)(nil), // 0: google.cloud.automl.v1beta1.PredictRequest
(*PredictResponse)(nil), // 1: google.cloud.automl.v1beta1.PredictResponse
(*BatchPredictRequest)(nil), // 2: google.cloud.automl.v1beta1.BatchPredictRequest
(*BatchPredictResult)(nil), // 3: google.cloud.automl.v1beta1.BatchPredictResult
nil, // 4: google.cloud.automl.v1beta1.PredictRequest.ParamsEntry
nil, // 5: google.cloud.automl.v1beta1.PredictResponse.MetadataEntry
nil, // 6: google.cloud.automl.v1beta1.BatchPredictRequest.ParamsEntry
nil, // 7: google.cloud.automl.v1beta1.BatchPredictResult.MetadataEntry
(*ExamplePayload)(nil), // 8: google.cloud.automl.v1beta1.ExamplePayload
(*AnnotationPayload)(nil), // 9: google.cloud.automl.v1beta1.AnnotationPayload
(*BatchPredictInputConfig)(nil), // 10: google.cloud.automl.v1beta1.BatchPredictInputConfig
(*BatchPredictOutputConfig)(nil), // 11: google.cloud.automl.v1beta1.BatchPredictOutputConfig
(*longrunning.Operation)(nil), // 12: google.longrunning.Operation
}
var file_google_cloud_automl_v1beta1_prediction_service_proto_depIdxs = []int32{
8, // 0: google.cloud.automl.v1beta1.PredictRequest.payload:type_name -> google.cloud.automl.v1beta1.ExamplePayload
4, // 1: google.cloud.automl.v1beta1.PredictRequest.params:type_name -> google.cloud.automl.v1beta1.PredictRequest.ParamsEntry
9, // 2: google.cloud.automl.v1beta1.PredictResponse.payload:type_name -> google.cloud.automl.v1beta1.AnnotationPayload
8, // 3: google.cloud.automl.v1beta1.PredictResponse.preprocessed_input:type_name -> google.cloud.automl.v1beta1.ExamplePayload
5, // 4: google.cloud.automl.v1beta1.PredictResponse.metadata:type_name -> google.cloud.automl.v1beta1.PredictResponse.MetadataEntry
10, // 5: google.cloud.automl.v1beta1.BatchPredictRequest.input_config:type_name -> google.cloud.automl.v1beta1.BatchPredictInputConfig
11, // 6: google.cloud.automl.v1beta1.BatchPredictRequest.output_config:type_name -> google.cloud.automl.v1beta1.BatchPredictOutputConfig
6, // 7: google.cloud.automl.v1beta1.BatchPredictRequest.params:type_name -> google.cloud.automl.v1beta1.BatchPredictRequest.ParamsEntry
7, // 8: google.cloud.automl.v1beta1.BatchPredictResult.metadata:type_name -> google.cloud.automl.v1beta1.BatchPredictResult.MetadataEntry
0, // 9: google.cloud.automl.v1beta1.PredictionService.Predict:input_type -> google.cloud.automl.v1beta1.PredictRequest
2, // 10: google.cloud.automl.v1beta1.PredictionService.BatchPredict:input_type -> google.cloud.automl.v1beta1.BatchPredictRequest
1, // 11: google.cloud.automl.v1beta1.PredictionService.Predict:output_type -> google.cloud.automl.v1beta1.PredictResponse
12, // 12: google.cloud.automl.v1beta1.PredictionService.BatchPredict:output_type -> google.longrunning.Operation
11, // [11:13] is the sub-list for method output_type
9, // [9:11] is the sub-list for method input_type
9, // [9:9] is the sub-list for extension type_name
9, // [9:9] is the sub-list for extension extendee
0, // [0:9] is the sub-list for field type_name
}
func init() { file_google_cloud_automl_v1beta1_prediction_service_proto_init() }
func file_google_cloud_automl_v1beta1_prediction_service_proto_init() {
if File_google_cloud_automl_v1beta1_prediction_service_proto != nil {
return
}
file_google_cloud_automl_v1beta1_annotation_payload_proto_init()
file_google_cloud_automl_v1beta1_data_items_proto_init()
file_google_cloud_automl_v1beta1_io_proto_init()
file_google_cloud_automl_v1beta1_operations_proto_init()
if !protoimpl.UnsafeEnabled {
file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*PredictRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*PredictResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*BatchPredictRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*BatchPredictResult); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
}
type x struct{}
out := protoimpl.TypeBuilder{
File: protoimpl.DescBuilder{
GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_google_cloud_automl_v1beta1_prediction_service_proto_rawDesc,
NumEnums: 0,
NumMessages: 8,
NumExtensions: 0,
NumServices: 1,
},
GoTypes: file_google_cloud_automl_v1beta1_prediction_service_proto_goTypes,
DependencyIndexes: file_google_cloud_automl_v1beta1_prediction_service_proto_depIdxs,
MessageInfos: file_google_cloud_automl_v1beta1_prediction_service_proto_msgTypes,
}.Build()
File_google_cloud_automl_v1beta1_prediction_service_proto = out.File
file_google_cloud_automl_v1beta1_prediction_service_proto_rawDesc = nil
file_google_cloud_automl_v1beta1_prediction_service_proto_goTypes = nil
file_google_cloud_automl_v1beta1_prediction_service_proto_depIdxs = nil
}
// 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.
// * Tables - Row, with column values matching the columns of the model,
// up to 5MB. Not available for FORECASTING
//
// [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type].
// * 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.v1beta1.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.v1beta1.BatchPredictResult] is returned in
// the [response][google.longrunning.Operation.response] field.
// Available for following ML problems:
// * Image Classification
// * Image Object Detection
// * Video Classification
// * Video Object Tracking * Text Extraction
// * Tables
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.v1beta1.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.v1beta1.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.
// * Tables - Row, with column values matching the columns of the model,
// up to 5MB. Not available for FORECASTING
//
// [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type].
// * 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.v1beta1.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.v1beta1.BatchPredictResult] is returned in
// the [response][google.longrunning.Operation.response] field.
// Available for following ML problems:
// * Image Classification
// * Image Object Detection
// * Video Classification
// * Video Object Tracking * Text Extraction
// * Tables
BatchPredict(context.Context, *BatchPredictRequest) (*longrunning.Operation, error)
}
// UnimplementedPredictionServiceServer can be embedded to have forward compatible implementations.
type UnimplementedPredictionServiceServer struct {
}
func (*UnimplementedPredictionServiceServer) Predict(context.Context, *PredictRequest) (*PredictResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
}
func (*UnimplementedPredictionServiceServer) BatchPredict(context.Context, *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.v1beta1.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.v1beta1.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.v1beta1.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/v1beta1/prediction_service.proto",
}