| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // source: google/cloud/automl/v1beta1/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.v1beta1.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. |
| // * For Tables: |
| // `feature_importance` - (boolean) Whether |
| // |
| // [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance] |
| // should be populated in the returned |
| // |
| // [TablesAnnotation(-s)][[google.cloud.automl.v1beta1.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"` |
| 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_59a9dba5da3c687d, []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.v1beta1.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.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"` |
| 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_59a9dba5da3c687d, []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.v1beta1.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. |
| // |
| // * 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 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"` |
| 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_59a9dba5da3c687d, []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.v1beta1.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. |
| // |
| // * 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"` |
| 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_59a9dba5da3c687d, []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.v1beta1.PredictRequest") |
| proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1beta1.PredictRequest.ParamsEntry") |
| proto.RegisterType((*PredictResponse)(nil), "google.cloud.automl.v1beta1.PredictResponse") |
| proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1beta1.PredictResponse.MetadataEntry") |
| proto.RegisterType((*BatchPredictRequest)(nil), "google.cloud.automl.v1beta1.BatchPredictRequest") |
| proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1beta1.BatchPredictRequest.ParamsEntry") |
| proto.RegisterType((*BatchPredictResult)(nil), "google.cloud.automl.v1beta1.BatchPredictResult") |
| proto.RegisterMapType((map[string]string)(nil), "google.cloud.automl.v1beta1.BatchPredictResult.MetadataEntry") |
| } |
| |
| func init() { |
| proto.RegisterFile("google/cloud/automl/v1beta1/prediction_service.proto", fileDescriptor_59a9dba5da3c687d) |
| } |
| |
| var fileDescriptor_59a9dba5da3c687d = []byte{ |
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| 0x55, 0x6b, 0x1b, 0x7e, 0x34, 0xc0, 0xa8, 0xfe, 0x17, 0xce, 0xe6, 0xd8, 0x06, 0xe5, 0xb9, 0x3c, |
| 0x23, 0x5f, 0xa9, 0xbf, 0xff, 0xfe, 0xe3, 0x83, 0xb9, 0x52, 0x59, 0xea, 0xae, 0xcb, 0xb7, 0xc9, |
| 0x24, 0xae, 0xf2, 0x90, 0xbd, 0xc4, 0xae, 0x88, 0xec, 0xaa, 0x4d, 0x98, 0xab, 0x36, 0xa3, 0x5d, |
| 0xb5, 0x03, 0xd6, 0xc6, 0x24, 0xb2, 0xab, 0xef, 0x1c, 0x7d, 0x69, 0x1c, 0xa3, 0x9a, 0x48, 0x1d, |
| 0x4f, 0x9b, 0x05, 0xef, 0xe5, 0x9d, 0x80, 0xf2, 0x8d, 0x0e, 0x22, 0xb5, 0x93, 0xad, 0xed, 0xce, |
| 0x4e, 0xae, 0x6c, 0x48, 0x95, 0xb5, 0xca, 0x4a, 0x5e, 0x95, 0xfb, 0xa9, 0x5a, 0x8e, 0x51, 0x2d, |
| 0x6f, 0x9e, 0xd6, 0xae, 0x68, 0x39, 0xaa, 0x20, 0xe2, 0x7e, 0x64, 0xb9, 0x2c, 0xf8, 0x56, 0xb3, |
| 0x0e, 0x85, 0xe0, 0x91, 0x63, 0xdb, 0xc7, 0xc7, 0xc7, 0x7f, 0x05, 0x93, 0x8b, 0x72, 0xa8, 0x8e, |
| 0xcb, 0x5d, 0x4e, 0x90, 0x38, 0x60, 0x61, 0x50, 0xff, 0x62, 0x80, 0x5b, 0x2e, 0x0b, 0xb2, 0x5a, |
| 0xad, 0x5f, 0x3d, 0xf3, 0x5d, 0x1b, 0xc9, 0x71, 0x69, 0x18, 0xbb, 0x35, 0x0d, 0xf3, 0x18, 0x41, |
| 0xd4, 0xb3, 0x58, 0xe8, 0xd9, 0x1e, 0xa6, 0xf2, 0xf4, 0xd8, 0xbd, 0xe2, 0xff, 0x3c, 0x68, 0xcb, |
| 0xea, 0x79, 0x6a, 0x4e, 0x6d, 0xc8, 0xc4, 0xbd, 0xb5, 0x24, 0x69, 0xaf, 0x16, 0x0b, 0xb6, 0x45, |
| 0xf6, 0x76, 0x54, 0xd2, 0x4f, 0xf3, 0xa6, 0x8a, 0x3a, 0x8e, 0x0c, 0x3b, 0x8e, 0x8c, 0x3f, 0x71, |
| 0x1c, 0x9d, 0xb0, 0x3f, 0x22, 0x8b, 0xdd, 0xff, 0x13, 0x00, 0x00, 0xff, 0xff, 0xc5, 0xb8, 0x8c, |
| 0xfa, 0x50, 0x08, 0x00, 0x00, |
| } |
| |
| // 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(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.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", |
| } |
