predictv2

type GRPCInferenceServiceClient interface {
	// The ServerLive API indicates if the inference server is able to receive
	// and respond to metadata and inference requests.
	ServerLive(ctx context.Context, in *ServerLiveRequest, opts ...grpc.CallOption) (*ServerLiveResponse, error)
	// The ServerReady API indicates if the server is ready for inferencing.
	ServerReady(ctx context.Context, in *ServerReadyRequest, opts ...grpc.CallOption) (*ServerReadyResponse, error)
	// The ModelReady API indicates if a specific model is ready for inferencing.
	ModelReady(ctx context.Context, in *ModelReadyRequest, opts ...grpc.CallOption) (*ModelReadyResponse, error)
	// The ServerMetadata API provides information about the server. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ServerMetadata(ctx context.Context, in *ServerMetadataRequest, opts ...grpc.CallOption) (*ServerMetadataResponse, error)
	// The per-model metadata API provides information about a model. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ModelMetadata(ctx context.Context, in *ModelMetadataRequest, opts ...grpc.CallOption) (*ModelMetadataResponse, error)
	// The ModelInfer API performs inference using the specified model. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ModelInfer(ctx context.Context, in *ModelInferRequest, opts ...grpc.CallOption) (*ModelInferResponse, error)
}

type GRPCInferenceServiceServer interface {
	// The ServerLive API indicates if the inference server is able to receive
	// and respond to metadata and inference requests.
	ServerLive(context.Context, *ServerLiveRequest) (*ServerLiveResponse, error)
	// The ServerReady API indicates if the server is ready for inferencing.
	ServerReady(context.Context, *ServerReadyRequest) (*ServerReadyResponse, error)
	// The ModelReady API indicates if a specific model is ready for inferencing.
	ModelReady(context.Context, *ModelReadyRequest) (*ModelReadyResponse, error)
	// The ServerMetadata API provides information about the server. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ServerMetadata(context.Context, *ServerMetadataRequest) (*ServerMetadataResponse, error)
	// The per-model metadata API provides information about a model. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ModelMetadata(context.Context, *ModelMetadataRequest) (*ModelMetadataResponse, error)
	// The ModelInfer API performs inference using the specified model. Errors are
	// indicated by the google.rpc.Status returned for the request. The OK code
	// indicates success and other codes indicate failure.
	ModelInfer(context.Context, *ModelInferRequest) (*ModelInferResponse, error)
	// contains filtered or unexported methods
}

type InferParameter struct {

	// The parameter value can be a string, an int64, a boolean
	// or a message specific to a predefined parameter.
	//
	// Types that are assignable to ParameterChoice:
	//	*InferParameter_BoolParam
	//	*InferParameter_Int64Param
	//	*InferParameter_StringParam
	ParameterChoice isInferParameter_ParameterChoice `protobuf_oneof:"parameter_choice"`
	// contains filtered or unexported fields
}

type InferParameter_BoolParam struct {
	// A boolean parameter value.
	BoolParam bool `protobuf:"varint,1,opt,name=bool_param,json=boolParam,proto3,oneof"`
}

type InferParameter_Int64Param struct {
	// An int64 parameter value.
	Int64Param int64 `protobuf:"varint,2,opt,name=int64_param,json=int64Param,proto3,oneof"`
}

type InferParameter_StringParam struct {
	// A string parameter value.
	StringParam string `protobuf:"bytes,3,opt,name=string_param,json=stringParam,proto3,oneof"`
}

type InferTensorContents struct {

	// Representation for BOOL data type. The size must match what is
	// expected by the tensor's shape. The contents must be the flattened,
	// one-dimensional, row-major order of the tensor elements.
	BoolContents []bool `protobuf:"varint,1,rep,packed,name=bool_contents,json=boolContents,proto3" json:"bool_contents,omitempty"`
	// Representation for INT8, INT16, and INT32 data types. The size
	// must match what is expected by the tensor's shape. The contents
	// must be the flattened, one-dimensional, row-major order of the
	// tensor elements.
	IntContents []int32 `protobuf:"varint,2,rep,packed,name=int_contents,json=intContents,proto3" json:"int_contents,omitempty"`
	// Representation for INT64 data types. The size must match what
	// is expected by the tensor's shape. The contents must be the
	// flattened, one-dimensional, row-major order of the tensor elements.
	Int64Contents []int64 `protobuf:"varint,3,rep,packed,name=int64_contents,json=int64Contents,proto3" json:"int64_contents,omitempty"`
	// Representation for UINT8, UINT16, and UINT32 data types. The size
	// must match what is expected by the tensor's shape. The contents
	// must be the flattened, one-dimensional, row-major order of the
	// tensor elements.
	UintContents []uint32 `protobuf:"varint,4,rep,packed,name=uint_contents,json=uintContents,proto3" json:"uint_contents,omitempty"`
	// Representation for UINT64 data types. The size must match what
	// is expected by the tensor's shape. The contents must be the
	// flattened, one-dimensional, row-major order of the tensor elements.
	Uint64Contents []uint64 `protobuf:"varint,5,rep,packed,name=uint64_contents,json=uint64Contents,proto3" json:"uint64_contents,omitempty"`
	// Representation for FP32 data type. The size must match what is
	// expected by the tensor's shape. The contents must be the flattened,
	// one-dimensional, row-major order of the tensor elements.
	Fp32Contents []float32 `protobuf:"fixed32,6,rep,packed,name=fp32_contents,json=fp32Contents,proto3" json:"fp32_contents,omitempty"`
	// Representation for FP64 data type. The size must match what is
	// expected by the tensor's shape. The contents must be the flattened,
	// one-dimensional, row-major order of the tensor elements.
	Fp64Contents []float64 `protobuf:"fixed64,7,rep,packed,name=fp64_contents,json=fp64Contents,proto3" json:"fp64_contents,omitempty"`
	// Representation for BYTES data type. The size must match what is
	// expected by the tensor's shape. The contents must be the flattened,
	// one-dimensional, row-major order of the tensor elements.
	BytesContents [][]byte `protobuf:"bytes,8,rep,name=bytes_contents,json=bytesContents,proto3" json:"bytes_contents,omitempty"`
	// contains filtered or unexported fields
}

type ModelInferRequest struct {

	// The name of the model to use for inferencing.
	ModelName string `protobuf:"bytes,1,opt,name=model_name,json=modelName,proto3" json:"model_name,omitempty"`
	// The version of the model to use for inference. If not given the
	// server will choose a version based on the model and internal policy.
	ModelVersion string `protobuf:"bytes,2,opt,name=model_version,json=modelVersion,proto3" json:"model_version,omitempty"`
	// Optional identifier for the request. If specified will be
	// returned in the response.
	Id string `protobuf:"bytes,3,opt,name=id,proto3" json:"id,omitempty"`
	// Optional inference parameters.
	Parameters map[string]*InferParameter `` /* 161-byte string literal not displayed */
	// The input tensors for the inference.
	Inputs []*ModelInferRequest_InferInputTensor `protobuf:"bytes,5,rep,name=inputs,proto3" json:"inputs,omitempty"`
	// The requested output tensors for the inference. Optional, if not
	// specified all outputs produced by the model will be returned.
	Outputs []*ModelInferRequest_InferRequestedOutputTensor `protobuf:"bytes,6,rep,name=outputs,proto3" json:"outputs,omitempty"`
	// The data contained in an input tensor can be represented in "raw"
	// bytes form or in the repeated type that matches the tensor's data
	// type. To use the raw representation 'raw_input_contents' must be
	// initialized with data for each tensor in the same order as
	// 'inputs'. For each tensor, the size of this content must match
	// what is expected by the tensor's shape and data type. The raw
	// data must be the flattened, one-dimensional, row-major order of
	// the tensor elements without any stride or padding between the
	// elements. Note that the FP16 data type must be represented as raw
	// content as there is no specific data type for a 16-bit float
	// type.
	//
	// If this field is specified then InferInputTensor::contents must
	// not be specified for any input tensor.
	RawInputContents [][]byte `protobuf:"bytes,7,rep,name=raw_input_contents,json=rawInputContents,proto3" json:"raw_input_contents,omitempty"`
	// contains filtered or unexported fields
}

type ModelInferRequest_InferInputTensor struct {

	// The tensor name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The tensor data type.
	Datatype string `protobuf:"bytes,2,opt,name=datatype,proto3" json:"datatype,omitempty"`
	// The tensor shape.
	Shape []int64 `protobuf:"varint,3,rep,packed,name=shape,proto3" json:"shape,omitempty"`
	// Optional inference input tensor parameters.
	Parameters map[string]*InferParameter `` /* 161-byte string literal not displayed */
	// The tensor contents using a data-type format. This field must
	// not be specified if "raw" tensor contents are being used for
	// the inference request.
	Contents *InferTensorContents `protobuf:"bytes,5,opt,name=contents,proto3" json:"contents,omitempty"`
	// contains filtered or unexported fields
}

type ModelInferRequest_InferRequestedOutputTensor struct {

	// The tensor name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// Optional requested output tensor parameters.
	Parameters map[string]*InferParameter `` /* 161-byte string literal not displayed */
	// contains filtered or unexported fields
}

type ModelInferResponse struct {

	// The name of the model used for inference.
	ModelName string `protobuf:"bytes,1,opt,name=model_name,json=modelName,proto3" json:"model_name,omitempty"`
	// The version of the model used for inference.
	ModelVersion string `protobuf:"bytes,2,opt,name=model_version,json=modelVersion,proto3" json:"model_version,omitempty"`
	// The id of the inference request if one was specified.
	Id string `protobuf:"bytes,3,opt,name=id,proto3" json:"id,omitempty"`
	// Optional inference response parameters.
	Parameters map[string]*InferParameter `` /* 161-byte string literal not displayed */
	// The output tensors holding inference results.
	Outputs []*ModelInferResponse_InferOutputTensor `protobuf:"bytes,5,rep,name=outputs,proto3" json:"outputs,omitempty"`
	// The data contained in an output tensor can be represented in
	// "raw" bytes form or in the repeated type that matches the
	// tensor's data type. To use the raw representation 'raw_output_contents'
	// must be initialized with data for each tensor in the same order as
	// 'outputs'. For each tensor, the size of this content must match
	// what is expected by the tensor's shape and data type. The raw
	// data must be the flattened, one-dimensional, row-major order of
	// the tensor elements without any stride or padding between the
	// elements. Note that the FP16 data type must be represented as raw
	// content as there is no specific data type for a 16-bit float
	// type.
	//
	// If this field is specified then InferOutputTensor::contents must
	// not be specified for any output tensor.
	RawOutputContents [][]byte `protobuf:"bytes,6,rep,name=raw_output_contents,json=rawOutputContents,proto3" json:"raw_output_contents,omitempty"`
	// contains filtered or unexported fields
}

type ModelInferResponse_InferOutputTensor struct {

	// The tensor name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The tensor data type.
	Datatype string `protobuf:"bytes,2,opt,name=datatype,proto3" json:"datatype,omitempty"`
	// The tensor shape.
	Shape []int64 `protobuf:"varint,3,rep,packed,name=shape,proto3" json:"shape,omitempty"`
	// Optional output tensor parameters.
	Parameters map[string]*InferParameter `` /* 161-byte string literal not displayed */
	// The tensor contents using a data-type format. This field must
	// not be specified if "raw" tensor contents are being used for
	// the inference response.
	Contents *InferTensorContents `protobuf:"bytes,5,opt,name=contents,proto3" json:"contents,omitempty"`
	// contains filtered or unexported fields
}

type ModelMetadataRequest struct {

	// The name of the model.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The version of the model to check for readiness. If not given the
	// server will choose a version based on the model and internal policy.
	Version string `protobuf:"bytes,2,opt,name=version,proto3" json:"version,omitempty"`
	// contains filtered or unexported fields
}

type ModelMetadataResponse struct {

	// The model name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The versions of the model available on the server.
	Versions []string `protobuf:"bytes,2,rep,name=versions,proto3" json:"versions,omitempty"`
	// The model's platform. See Platforms.
	Platform string `protobuf:"bytes,3,opt,name=platform,proto3" json:"platform,omitempty"`
	// The model's inputs.
	Inputs []*ModelMetadataResponse_TensorMetadata `protobuf:"bytes,4,rep,name=inputs,proto3" json:"inputs,omitempty"`
	// The model's outputs.
	Outputs []*ModelMetadataResponse_TensorMetadata `protobuf:"bytes,5,rep,name=outputs,proto3" json:"outputs,omitempty"`
	// contains filtered or unexported fields
}

type ModelMetadataResponse_TensorMetadata struct {

	// The tensor name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The tensor data type.
	Datatype string `protobuf:"bytes,2,opt,name=datatype,proto3" json:"datatype,omitempty"`
	// The tensor shape. A variable-size dimension is represented
	// by a -1 value.
	Shape []int64 `protobuf:"varint,3,rep,packed,name=shape,proto3" json:"shape,omitempty"`
	// contains filtered or unexported fields
}

type ModelReadyRequest struct {

	// The name of the model to check for readiness.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The version of the model to check for readiness. If not given the
	// server will choose a version based on the model and internal policy.
	Version string `protobuf:"bytes,2,opt,name=version,proto3" json:"version,omitempty"`
	// contains filtered or unexported fields
}

type ModelReadyResponse struct {

	// True if the model is ready, false if not ready.
	Ready bool `protobuf:"varint,1,opt,name=ready,proto3" json:"ready,omitempty"`
	// contains filtered or unexported fields
}

type ServerLiveRequest struct {
	// contains filtered or unexported fields
}

type ServerLiveResponse struct {

	// True if the inference server is live, false if not live.
	Live bool `protobuf:"varint,1,opt,name=live,proto3" json:"live,omitempty"`
	// contains filtered or unexported fields
}

type ServerMetadataRequest struct {
	// contains filtered or unexported fields
}

type ServerMetadataResponse struct {

	// The server name.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The server version.
	Version string `protobuf:"bytes,2,opt,name=version,proto3" json:"version,omitempty"`
	// The extensions supported by the server.
	Extensions []string `protobuf:"bytes,3,rep,name=extensions,proto3" json:"extensions,omitempty"`
	// contains filtered or unexported fields
}

type ServerReadyRequest struct {
	// contains filtered or unexported fields
}

type ServerReadyResponse struct {

	// True if the inference server is ready, false if not ready.
	Ready bool `protobuf:"varint,1,opt,name=ready,proto3" json:"ready,omitempty"`
	// contains filtered or unexported fields
}

type UnimplementedGRPCInferenceServiceServer struct {
}

type UnsafeGRPCInferenceServiceServer interface {
	// contains filtered or unexported methods
}