| // 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 v3.12.2 |
| // 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_imp<span>ortan</span>ce - (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_imp<span>ortan</span>ce - (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 |
| |
| var file_google_cloud_automl_v1beta1_prediction_service_proto_rawDesc = []byte{ |
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| 0x6f, 0x74, 0x6f, 0x33, |
| } |
| |
| 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", |
| } |
