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- // Code generated by protoc-gen-go. DO NOT EDIT.
- // source: google/cloud/ml/v1/prediction_service.proto
-
- package ml // import "google.golang.org/genproto/googleapis/cloud/ml/v1"
-
- import proto "github.com/golang/protobuf/proto"
- import fmt "fmt"
- import math "math"
- import _ "google.golang.org/genproto/googleapis/api/annotations"
- import httpbody "google.golang.org/genproto/googleapis/api/httpbody"
-
- import (
- context "golang.org/x/net/context"
- grpc "google.golang.org/grpc"
- )
-
- // 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.ProtoPackageIsVersion2 // please upgrade the proto package
-
- // Request for predictions to be issued against a trained model.
- //
- // The body of the request is a single JSON object with a single top-level
- // field:
- //
- // <dl>
- // <dt>instances</dt>
- // <dd>A JSON array containing values representing the instances to use for
- // prediction.</dd>
- // </dl>
- //
- // The structure of each element of the instances list is determined by your
- // model's input definition. Instances can include named inputs or can contain
- // only unlabeled values.
- //
- // Not all data includes named inputs. Some instances will be simple
- // JSON values (boolean, number, or string). However, instances are often lists
- // of simple values, or complex nested lists. Here are some examples of request
- // bodies:
- //
- // CSV data with each row encoded as a string value:
- // <pre>
- // {"instances": ["1.0,true,\\"x\\"", "-2.0,false,\\"y\\""]}
- // </pre>
- // Plain text:
- // <pre>
- // {"instances": ["the quick brown fox", "la bruja le dio"]}
- // </pre>
- // Sentences encoded as lists of words (vectors of strings):
- // <pre>
- // {
- // "instances": [
- // ["the","quick","brown"],
- // ["la","bruja","le"],
- // ...
- // ]
- // }
- // </pre>
- // Floating point scalar values:
- // <pre>
- // {"instances": [0.0, 1.1, 2.2]}
- // </pre>
- // Vectors of integers:
- // <pre>
- // {
- // "instances": [
- // [0, 1, 2],
- // [3, 4, 5],
- // ...
- // ]
- // }
- // </pre>
- // Tensors (in this case, two-dimensional tensors):
- // <pre>
- // {
- // "instances": [
- // [
- // [0, 1, 2],
- // [3, 4, 5]
- // ],
- // ...
- // ]
- // }
- // </pre>
- // Images can be represented different ways. In this encoding scheme the first
- // two dimensions represent the rows and columns of the image, and the third
- // contains lists (vectors) of the R, G, and B values for each pixel.
- // <pre>
- // {
- // "instances": [
- // [
- // [
- // [138, 30, 66],
- // [130, 20, 56],
- // ...
- // ],
- // [
- // [126, 38, 61],
- // [122, 24, 57],
- // ...
- // ],
- // ...
- // ],
- // ...
- // ]
- // }
- // </pre>
- // JSON strings must be encoded as UTF-8. To send binary data, you must
- // base64-encode the data and mark it as binary. To mark a JSON string
- // as binary, replace it with a JSON object with a single attribute named `b64`:
- // <pre>{"b64": "..."} </pre>
- // For example:
- //
- // Two Serialized tf.Examples (fake data, for illustrative purposes only):
- // <pre>
- // {"instances": [{"b64": "X5ad6u"}, {"b64": "IA9j4nx"}]}
- // </pre>
- // Two JPEG image byte strings (fake data, for illustrative purposes only):
- // <pre>
- // {"instances": [{"b64": "ASa8asdf"}, {"b64": "JLK7ljk3"}]}
- // </pre>
- // If your data includes named references, format each instance as a JSON object
- // with the named references as the keys:
- //
- // JSON input data to be preprocessed:
- // <pre>
- // {
- // "instances": [
- // {
- // "a": 1.0,
- // "b": true,
- // "c": "x"
- // },
- // {
- // "a": -2.0,
- // "b": false,
- // "c": "y"
- // }
- // ]
- // }
- // </pre>
- // Some models have an underlying TensorFlow graph that accepts multiple input
- // tensors. In this case, you should use the names of JSON name/value pairs to
- // identify the input tensors, as shown in the following exmaples:
- //
- // For a graph with input tensor aliases "tag" (string) and "image"
- // (base64-encoded string):
- // <pre>
- // {
- // "instances": [
- // {
- // "tag": "beach",
- // "image": {"b64": "ASa8asdf"}
- // },
- // {
- // "tag": "car",
- // "image": {"b64": "JLK7ljk3"}
- // }
- // ]
- // }
- // </pre>
- // For a graph with input tensor aliases "tag" (string) and "image"
- // (3-dimensional array of 8-bit ints):
- // <pre>
- // {
- // "instances": [
- // {
- // "tag": "beach",
- // "image": [
- // [
- // [138, 30, 66],
- // [130, 20, 56],
- // ...
- // ],
- // [
- // [126, 38, 61],
- // [122, 24, 57],
- // ...
- // ],
- // ...
- // ]
- // },
- // {
- // "tag": "car",
- // "image": [
- // [
- // [255, 0, 102],
- // [255, 0, 97],
- // ...
- // ],
- // [
- // [254, 1, 101],
- // [254, 2, 93],
- // ...
- // ],
- // ...
- // ]
- // },
- // ...
- // ]
- // }
- // </pre>
- // If the call is successful, the response body will contain one prediction
- // entry per instance in the request body. If prediction fails for any
- // instance, the response body will contain no predictions and will contian
- // a single error entry instead.
- type PredictRequest struct {
- // Required. The resource name of a model or a version.
- //
- // Authorization: requires `Viewer` role on the parent project.
- Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
- //
- // Required. The prediction request body.
- HttpBody *httpbody.HttpBody `protobuf:"bytes,2,opt,name=http_body,json=httpBody,proto3" json:"http_body,omitempty"`
- 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_prediction_service_917133d9a7213060, []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 (dst *PredictRequest) XXX_Merge(src proto.Message) {
- xxx_messageInfo_PredictRequest.Merge(dst, 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) GetHttpBody() *httpbody.HttpBody {
- if m != nil {
- return m.HttpBody
- }
- return nil
- }
-
- func init() {
- proto.RegisterType((*PredictRequest)(nil), "google.cloud.ml.v1.PredictRequest")
- }
-
- // Reference imports to suppress errors if they are not otherwise used.
- var _ context.Context
- var _ grpc.ClientConn
-
- // 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.SupportPackageIsVersion4
-
- // OnlinePredictionServiceClient is the client API for OnlinePredictionService service.
- //
- // For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
- type OnlinePredictionServiceClient interface {
- // Performs prediction on the data in the request.
- //
- // **** REMOVE FROM GENERATED DOCUMENTATION
- Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*httpbody.HttpBody, error)
- }
-
- type onlinePredictionServiceClient struct {
- cc *grpc.ClientConn
- }
-
- func NewOnlinePredictionServiceClient(cc *grpc.ClientConn) OnlinePredictionServiceClient {
- return &onlinePredictionServiceClient{cc}
- }
-
- func (c *onlinePredictionServiceClient) Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*httpbody.HttpBody, error) {
- out := new(httpbody.HttpBody)
- err := c.cc.Invoke(ctx, "/google.cloud.ml.v1.OnlinePredictionService/Predict", in, out, opts...)
- if err != nil {
- return nil, err
- }
- return out, nil
- }
-
- // OnlinePredictionServiceServer is the server API for OnlinePredictionService service.
- type OnlinePredictionServiceServer interface {
- // Performs prediction on the data in the request.
- //
- // **** REMOVE FROM GENERATED DOCUMENTATION
- Predict(context.Context, *PredictRequest) (*httpbody.HttpBody, error)
- }
-
- func RegisterOnlinePredictionServiceServer(s *grpc.Server, srv OnlinePredictionServiceServer) {
- s.RegisterService(&_OnlinePredictionService_serviceDesc, srv)
- }
-
- func _OnlinePredictionService_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.(OnlinePredictionServiceServer).Predict(ctx, in)
- }
- info := &grpc.UnaryServerInfo{
- Server: srv,
- FullMethod: "/google.cloud.ml.v1.OnlinePredictionService/Predict",
- }
- handler := func(ctx context.Context, req interface{}) (interface{}, error) {
- return srv.(OnlinePredictionServiceServer).Predict(ctx, req.(*PredictRequest))
- }
- return interceptor(ctx, in, info, handler)
- }
-
- var _OnlinePredictionService_serviceDesc = grpc.ServiceDesc{
- ServiceName: "google.cloud.ml.v1.OnlinePredictionService",
- HandlerType: (*OnlinePredictionServiceServer)(nil),
- Methods: []grpc.MethodDesc{
- {
- MethodName: "Predict",
- Handler: _OnlinePredictionService_Predict_Handler,
- },
- },
- Streams: []grpc.StreamDesc{},
- Metadata: "google/cloud/ml/v1/prediction_service.proto",
- }
-
- func init() {
- proto.RegisterFile("google/cloud/ml/v1/prediction_service.proto", fileDescriptor_prediction_service_917133d9a7213060)
- }
-
- var fileDescriptor_prediction_service_917133d9a7213060 = []byte{
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