apis

package
v0.0.0-...-d1695c4 Latest Latest
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 Go to latest Published: Sep 29, 2021 License: Apache-2.0 Imports: 11 Imported by: 0

Documentation

Overview

Package apis is a generated protocol buffer package.

It is generated from these files: 

tensorflow_serving/apis/classification.proto
tensorflow_serving/apis/get_model_metadata.proto
tensorflow_serving/apis/inference.proto
tensorflow_serving/apis/input.proto
tensorflow_serving/apis/model.proto
tensorflow_serving/apis/predict.proto
tensorflow_serving/apis/prediction_service.proto
tensorflow_serving/apis/regression.proto

It has these top-level messages: 

Class
Classifications
ClassificationResult
ClassificationRequest
ClassificationResponse
SignatureDefMap
GetModelMetadataRequest
GetModelMetadataResponse
InferenceTask
InferenceResult
MultiInferenceRequest
MultiInferenceResponse
ExampleList
ExampleListWithContext
Input
ModelSpec
PredictRequest
PredictResponse
Regression
RegressionResult
RegressionRequest
RegressionResponse

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func RegisterPredictionServiceServer 

func RegisterPredictionServiceServer(s *grpc.Server, srv PredictionServiceServer)

Types

type Class 

type Class struct {
	// Label or name of the class.
	Label string `protobuf:"bytes,1,opt,name=label" json:"label,omitempty"`
	// Score for this class (e.g., the probability the item belongs to this
	// class).
	Score float32 `protobuf:"fixed32,2,opt,name=score" json:"score,omitempty"`
}

A single class.

func (*Class) Descriptor 

func (*Class) Descriptor() ([]byte, []int)

func (*Class) GetLabel 

func (m *Class) GetLabel() string

func (*Class) GetScore 

func (m *Class) GetScore() float32

func (*Class) ProtoMessage 

func (*Class) ProtoMessage()

func (*Class) Reset 

func (m *Class) Reset()

func (*Class) String 

func (m *Class) String() string

type ClassificationRequest 

type ClassificationRequest struct {
	// Model Specification.
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Input data.
	Input *Input `protobuf:"bytes,2,opt,name=input" json:"input,omitempty"`
}

func (*ClassificationRequest) Descriptor 

func (*ClassificationRequest) Descriptor() ([]byte, []int)

func (*ClassificationRequest) GetInput 

func (m *ClassificationRequest) GetInput() *Input

func (*ClassificationRequest) GetModelSpec 

func (m *ClassificationRequest) GetModelSpec() *ModelSpec

func (*ClassificationRequest) ProtoMessage 

func (*ClassificationRequest) ProtoMessage()

func (*ClassificationRequest) Reset 

func (m *ClassificationRequest) Reset()

func (*ClassificationRequest) String 

func (m *ClassificationRequest) String() string

type ClassificationResponse 

type ClassificationResponse struct {
	// Result of the classification.
	Result *ClassificationResult `protobuf:"bytes,1,opt,name=result" json:"result,omitempty"`
}

func (*ClassificationResponse) Descriptor 

func (*ClassificationResponse) Descriptor() ([]byte, []int)

func (*ClassificationResponse) GetResult 

func (m *ClassificationResponse) GetResult() *ClassificationResult

func (*ClassificationResponse) ProtoMessage 

func (*ClassificationResponse) ProtoMessage()

func (*ClassificationResponse) Reset 

func (m *ClassificationResponse) Reset()

func (*ClassificationResponse) String 

func (m *ClassificationResponse) String() string

type ClassificationResult 

type ClassificationResult struct {
	Classifications []*Classifications `protobuf:"bytes,1,rep,name=classifications" json:"classifications,omitempty"`
}

Contains one result per input example, in the same order as the input in ClassificationRequest.

func (*ClassificationResult) Descriptor 

func (*ClassificationResult) Descriptor() ([]byte, []int)

func (*ClassificationResult) GetClassifications 

func (m *ClassificationResult) GetClassifications() []*Classifications

func (*ClassificationResult) ProtoMessage 

func (*ClassificationResult) ProtoMessage()

func (*ClassificationResult) Reset 

func (m *ClassificationResult) Reset()

func (*ClassificationResult) String 

func (m *ClassificationResult) String() string

type Classifications 

type Classifications struct {
	Classes []*Class `protobuf:"bytes,1,rep,name=classes" json:"classes,omitempty"`
}

List of classes for a single item (tensorflow.Example).

func (*Classifications) Descriptor 

func (*Classifications) Descriptor() ([]byte, []int)

func (*Classifications) GetClasses 

func (m *Classifications) GetClasses() []*Class

func (*Classifications) ProtoMessage 

func (*Classifications) ProtoMessage()

func (*Classifications) Reset 

func (m *Classifications) Reset()

func (*Classifications) String 

func (m *Classifications) String() string

type ExampleList 

type ExampleList struct {
	Examples []*tensorflow1.Example `protobuf:"bytes,1,rep,name=examples" json:"examples,omitempty"`
}

Specifies one or more fully independent input Examples. See examples at: 

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/example/example.proto

func (*ExampleList) Descriptor 

func (*ExampleList) Descriptor() ([]byte, []int)

func (*ExampleList) GetExamples 

func (m *ExampleList) GetExamples() []*tensorflow1.Example

func (*ExampleList) ProtoMessage 

func (*ExampleList) ProtoMessage()

func (*ExampleList) Reset 

func (m *ExampleList) Reset()

func (*ExampleList) String 

func (m *ExampleList) String() string

type ExampleListWithContext 

type ExampleListWithContext struct {
	Examples []*tensorflow1.Example `protobuf:"bytes,1,rep,name=examples" json:"examples,omitempty"`
	Context  *tensorflow1.Example   `protobuf:"bytes,2,opt,name=context" json:"context,omitempty"`
}

Specifies one or more independent input Examples, with a common context Example.

The common use case for context is to cleanly and optimally specify some features that are common across multiple examples.

See example below with a search query as the context and multiple restaurants to perform some inference on. 

context: {
  feature: {
    key  : "query"
    value: {
      bytes_list: {
        value: [ "pizza" ]
      }
    }
  }
}

examples: {
  feature: {
    key  : "cuisine"
    value: {
      bytes_list: {
        value: [ "Pizzeria" ]
      }
    }
  }
}

examples: {
  feature: {
    key  : "cuisine"
    value: {
      bytes_list: {
        value: [ "Taqueria" ]
      }
    }
  }
}

Implementations of ExampleListWithContext merge the context Example into each of the Examples. Note that feature keys must not be duplicated between the Examples and context Example, or the behavior is undefined.

See also: 

tensorflow/core/example/example.proto
https://developers.google.com/protocol-buffers/docs/proto3#maps

func (*ExampleListWithContext) Descriptor 

func (*ExampleListWithContext) Descriptor() ([]byte, []int)

func (*ExampleListWithContext) GetContext 

func (m *ExampleListWithContext) GetContext() *tensorflow1.Example

func (*ExampleListWithContext) GetExamples 

func (m *ExampleListWithContext) GetExamples() []*tensorflow1.Example

func (*ExampleListWithContext) ProtoMessage 

func (*ExampleListWithContext) ProtoMessage()

func (*ExampleListWithContext) Reset 

func (m *ExampleListWithContext) Reset()

func (*ExampleListWithContext) String 

func (m *ExampleListWithContext) String() string

type GetModelMetadataRequest 

type GetModelMetadataRequest struct {
	// Model Specification indicating which model we are querying for metadata.
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Metadata fields to get. Currently supported: "signature_def".
	MetadataField []string `protobuf:"bytes,2,rep,name=metadata_field,json=metadataField" json:"metadata_field,omitempty"`
}

func (*GetModelMetadataRequest) Descriptor 

func (*GetModelMetadataRequest) Descriptor() ([]byte, []int)

func (*GetModelMetadataRequest) GetMetadataField 

func (m *GetModelMetadataRequest) GetMetadataField() []string

func (*GetModelMetadataRequest) GetModelSpec 

func (m *GetModelMetadataRequest) GetModelSpec() *ModelSpec

func (*GetModelMetadataRequest) ProtoMessage 

func (*GetModelMetadataRequest) ProtoMessage()

func (*GetModelMetadataRequest) Reset 

func (m *GetModelMetadataRequest) Reset()

func (*GetModelMetadataRequest) String 

func (m *GetModelMetadataRequest) String() string

type GetModelMetadataResponse 

type GetModelMetadataResponse struct {
	// Model Specification indicating which model this metadata belongs to.
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Map of metadata field name to metadata field. The options for metadata
	// field name are listed in GetModelMetadataRequest. Currently supported:
	// "signature_def".
	Metadata map[string]*google_protobuf1.Any `` /* 136-byte string literal not displayed */
}

func (*GetModelMetadataResponse) Descriptor 

func (*GetModelMetadataResponse) Descriptor() ([]byte, []int)

func (*GetModelMetadataResponse) GetMetadata 

func (m *GetModelMetadataResponse) GetMetadata() map[string]*google_protobuf1.Any

func (*GetModelMetadataResponse) GetModelSpec 

func (m *GetModelMetadataResponse) GetModelSpec() *ModelSpec

func (*GetModelMetadataResponse) ProtoMessage 

func (*GetModelMetadataResponse) ProtoMessage()

func (*GetModelMetadataResponse) Reset 

func (m *GetModelMetadataResponse) Reset()

func (*GetModelMetadataResponse) String 

func (m *GetModelMetadataResponse) String() string

type InferenceResult 

type InferenceResult struct {
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Types that are valid to be assigned to Result:
	//	*InferenceResult_ClassificationResult
	//	*InferenceResult_RegressionResult
	Result isInferenceResult_Result `protobuf_oneof:"result"`
}

Inference result, matches the type of request or is an error.

func (*InferenceResult) Descriptor 

func (*InferenceResult) Descriptor() ([]byte, []int)

func (*InferenceResult) GetClassificationResult 

func (m *InferenceResult) GetClassificationResult() *ClassificationResult

func (*InferenceResult) GetModelSpec 

func (m *InferenceResult) GetModelSpec() *ModelSpec

func (*InferenceResult) GetRegressionResult 

func (m *InferenceResult) GetRegressionResult() *RegressionResult

func (*InferenceResult) GetResult 

func (m *InferenceResult) GetResult() isInferenceResult_Result

func (*InferenceResult) ProtoMessage 

func (*InferenceResult) ProtoMessage()

func (*InferenceResult) Reset 

func (m *InferenceResult) Reset()

func (*InferenceResult) String 

func (m *InferenceResult) String() string

func (*InferenceResult) XXX_OneofFuncs 

func (*InferenceResult) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{})

XXX_OneofFuncs is for the internal use of the proto package.

type InferenceResult_ClassificationResult 

type InferenceResult_ClassificationResult struct {
	ClassificationResult *ClassificationResult `protobuf:"bytes,2,opt,name=classification_result,json=classificationResult,oneof"`
}

type InferenceResult_RegressionResult 

type InferenceResult_RegressionResult struct {
	RegressionResult *RegressionResult `protobuf:"bytes,3,opt,name=regression_result,json=regressionResult,oneof"`
}

type InferenceTask 

type InferenceTask struct {
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Signature's method_name. Should be one of the method names defined in
	// third_party/tensorflow/python/saved_model/signature_constants.py.
	// e.g. "tensorflow/serving/classify".
	MethodName string `protobuf:"bytes,2,opt,name=method_name,json=methodName" json:"method_name,omitempty"`
}

Inference request such as classification, regression, etc...

func (*InferenceTask) Descriptor 

func (*InferenceTask) Descriptor() ([]byte, []int)

func (*InferenceTask) GetMethodName 

func (m *InferenceTask) GetMethodName() string

func (*InferenceTask) GetModelSpec 

func (m *InferenceTask) GetModelSpec() *ModelSpec

func (*InferenceTask) ProtoMessage 

func (*InferenceTask) ProtoMessage()

func (*InferenceTask) Reset 

func (m *InferenceTask) Reset()

func (*InferenceTask) String 

func (m *InferenceTask) String() string

type Input 

type Input struct {
	// Types that are valid to be assigned to Kind:
	//	*Input_ExampleList
	//	*Input_ExampleListWithContext
	Kind isInput_Kind `protobuf_oneof:"kind"`
}

func (*Input) Descriptor 

func (*Input) Descriptor() ([]byte, []int)

func (*Input) GetExampleList 

func (m *Input) GetExampleList() *ExampleList

func (*Input) GetExampleListWithContext 

func (m *Input) GetExampleListWithContext() *ExampleListWithContext

func (*Input) GetKind 

func (m *Input) GetKind() isInput_Kind

func (*Input) ProtoMessage 

func (*Input) ProtoMessage()

func (*Input) Reset 

func (m *Input) Reset()

func (*Input) String 

func (m *Input) String() string

func (*Input) XXX_OneofFuncs 

func (*Input) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{})

XXX_OneofFuncs is for the internal use of the proto package.

type Input_ExampleList 

type Input_ExampleList struct {
	ExampleList *ExampleList `protobuf:"bytes,1,opt,name=example_list,json=exampleList,oneof"`
}

type Input_ExampleListWithContext 

type Input_ExampleListWithContext struct {
	ExampleListWithContext *ExampleListWithContext `protobuf:"bytes,2,opt,name=example_list_with_context,json=exampleListWithContext,oneof"`
}

type ModelSpec 

type ModelSpec struct {
	// Required servable name.
	Name string `protobuf:"bytes,1,opt,name=name" json:"name,omitempty"`
	// Optional version. If unspecified, will use the latest (numerical) version.
	// Typically not needed unless coordinating across multiple models that were
	// co-trained and/or have inter-dependencies on the versions used at inference
	// time.
	Version *google_protobuf.Int64Value `protobuf:"bytes,2,opt,name=version" json:"version,omitempty"`
	// A named signature to evaluate. If unspecified, the default signature will
	// be used.
	SignatureName string `protobuf:"bytes,3,opt,name=signature_name,json=signatureName" json:"signature_name,omitempty"`
}

Metadata for an inference request such as the model name and version.

func (*ModelSpec) Descriptor 

func (*ModelSpec) Descriptor() ([]byte, []int)

func (*ModelSpec) GetName 

func (m *ModelSpec) GetName() string

func (*ModelSpec) GetSignatureName 

func (m *ModelSpec) GetSignatureName() string

func (*ModelSpec) GetVersion 

func (m *ModelSpec) GetVersion() *google_protobuf.Int64Value

func (*ModelSpec) ProtoMessage 

func (*ModelSpec) ProtoMessage()

func (*ModelSpec) Reset 

func (m *ModelSpec) Reset()

func (*ModelSpec) String 

func (m *ModelSpec) String() string

type MultiInferenceRequest 

type MultiInferenceRequest struct {
	// Inference tasks.
	Tasks []*InferenceTask `protobuf:"bytes,1,rep,name=tasks" json:"tasks,omitempty"`
	// Input data.
	Input *Input `protobuf:"bytes,2,opt,name=input" json:"input,omitempty"`
}

Inference request containing one or more requests.

func (*MultiInferenceRequest) Descriptor 

func (*MultiInferenceRequest) Descriptor() ([]byte, []int)

func (*MultiInferenceRequest) GetInput 

func (m *MultiInferenceRequest) GetInput() *Input

func (*MultiInferenceRequest) GetTasks 

func (m *MultiInferenceRequest) GetTasks() []*InferenceTask

func (*MultiInferenceRequest) ProtoMessage 

func (*MultiInferenceRequest) ProtoMessage()

func (*MultiInferenceRequest) Reset 

func (m *MultiInferenceRequest) Reset()

func (*MultiInferenceRequest) String 

func (m *MultiInferenceRequest) String() string

type MultiInferenceResponse 

type MultiInferenceResponse struct {
	// List of results; one for each InferenceTask in the request, returned in the
	// same order as the request.
	Results []*InferenceResult `protobuf:"bytes,1,rep,name=results" json:"results,omitempty"`
}

Inference request containing one or more responses.

func (*MultiInferenceResponse) Descriptor 

func (*MultiInferenceResponse) Descriptor() ([]byte, []int)

func (*MultiInferenceResponse) GetResults 

func (m *MultiInferenceResponse) GetResults() []*InferenceResult

func (*MultiInferenceResponse) ProtoMessage 

func (*MultiInferenceResponse) ProtoMessage()

func (*MultiInferenceResponse) Reset 

func (m *MultiInferenceResponse) Reset()

func (*MultiInferenceResponse) String 

func (m *MultiInferenceResponse) String() string

type PredictRequest 

type PredictRequest struct {
	// Model Specification.
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Input tensors.
	// Names of input tensor are alias names. The mapping from aliases to real
	// input tensor names is expected to be stored as named generic signature
	// under the key "inputs" in the model export.
	// Each alias listed in a generic signature named "inputs" should be provided
	// exactly once in order to run the prediction.
	Inputs map[string]*tensorflow5.TensorProto `` /* 132-byte string literal not displayed */
	// Output filter.
	// Names specified are alias names. The mapping from aliases to real output
	// tensor names is expected to be stored as named generic signature under
	// the key "outputs" in the model export.
	// Only tensors specified here will be run/fetched and returned, with the
	// exception that when none is specified, all tensors specified in the
	// named signature will be run/fetched and returned.
	OutputFilter []string `protobuf:"bytes,3,rep,name=output_filter,json=outputFilter" json:"output_filter,omitempty"`
}

PredictRequest specifies which TensorFlow model to run, as well as how inputs are mapped to tensors and how outputs are filtered before returning to user.

func (*PredictRequest) Descriptor 

func (*PredictRequest) Descriptor() ([]byte, []int)

func (*PredictRequest) GetInputs 

func (m *PredictRequest) GetInputs() map[string]*tensorflow5.TensorProto

func (*PredictRequest) GetModelSpec 

func (m *PredictRequest) GetModelSpec() *ModelSpec

func (*PredictRequest) GetOutputFilter 

func (m *PredictRequest) GetOutputFilter() []string

func (*PredictRequest) ProtoMessage 

func (*PredictRequest) ProtoMessage()

func (*PredictRequest) Reset 

func (m *PredictRequest) Reset()

func (*PredictRequest) String 

func (m *PredictRequest) String() string

type PredictResponse 

type PredictResponse struct {
	// Output tensors.
	Outputs map[string]*tensorflow5.TensorProto `` /* 134-byte string literal not displayed */
}

Response for PredictRequest on successful run.

func (*PredictResponse) Descriptor 

func (*PredictResponse) Descriptor() ([]byte, []int)

func (*PredictResponse) GetOutputs 

func (m *PredictResponse) GetOutputs() map[string]*tensorflow5.TensorProto

func (*PredictResponse) ProtoMessage 

func (*PredictResponse) ProtoMessage()

func (*PredictResponse) Reset 

func (m *PredictResponse) Reset()

func (*PredictResponse) String 

func (m *PredictResponse) String() string

type PredictionServiceClient 

type PredictionServiceClient interface {
	// Classify.
	Classify(ctx context.Context, in *ClassificationRequest, opts ...grpc.CallOption) (*ClassificationResponse, error)
	// Regress.
	Regress(ctx context.Context, in *RegressionRequest, opts ...grpc.CallOption) (*RegressionResponse, error)
	// Predict -- provides access to loaded TensorFlow model.
	Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*PredictResponse, error)
	// PredictJSON -- provides access to loaded TensorFlow model.
	PredictJSON(ctx context.Context, in *ml_serving.PredictJSONData, opts ...grpc.CallOption) (*ml_serving.PredictJSONData, error)
	// MultiInference API for multi-headed models.
	MultiInference(ctx context.Context, in *MultiInferenceRequest, opts ...grpc.CallOption) (*MultiInferenceResponse, error)
	// GetModelMetadata - provides access to metadata for loaded models.
	GetModelMetadata(ctx context.Context, in *GetModelMetadataRequest, opts ...grpc.CallOption) (*GetModelMetadataResponse, error)
}

func NewPredictionServiceClient 

func NewPredictionServiceClient(cc *grpc.ClientConn) PredictionServiceClient

type PredictionServiceServer 

type PredictionServiceServer interface {
	// Classify.
	Classify(context.Context, *ClassificationRequest) (*ClassificationResponse, error)
	// Regress.
	Regress(context.Context, *RegressionRequest) (*RegressionResponse, error)
	// Predict -- provides access to loaded TensorFlow model.
	Predict(context.Context, *PredictRequest) (*PredictResponse, error)
	// PredictJSON -- provides access to loaded TensorFlow model.
	PredictJSON(context.Context, *ml_serving.PredictJSONData) (*ml_serving.PredictJSONData, error)
	// MultiInference API for multi-headed models.
	MultiInference(context.Context, *MultiInferenceRequest) (*MultiInferenceResponse, error)
	// GetModelMetadata - provides access to metadata for loaded models.
	GetModelMetadata(context.Context, *GetModelMetadataRequest) (*GetModelMetadataResponse, error)
}

type Regression 

type Regression struct {
	Value float32 `protobuf:"fixed32,1,opt,name=value" json:"value,omitempty"`
}

Regression result for a single item (tensorflow.Example).

func (*Regression) Descriptor 

func (*Regression) Descriptor() ([]byte, []int)

func (*Regression) GetValue 

func (m *Regression) GetValue() float32

func (*Regression) ProtoMessage 

func (*Regression) ProtoMessage()

func (*Regression) Reset 

func (m *Regression) Reset()

func (*Regression) String 

func (m *Regression) String() string

type RegressionRequest 

type RegressionRequest struct {
	// Model Specification.
	ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec" json:"model_spec,omitempty"`
	// Input data.
	Input *Input `protobuf:"bytes,2,opt,name=input" json:"input,omitempty"`
}

func (*RegressionRequest) Descriptor 

func (*RegressionRequest) Descriptor() ([]byte, []int)

func (*RegressionRequest) GetInput 

func (m *RegressionRequest) GetInput() *Input

func (*RegressionRequest) GetModelSpec 

func (m *RegressionRequest) GetModelSpec() *ModelSpec

func (*RegressionRequest) ProtoMessage 

func (*RegressionRequest) ProtoMessage()

func (*RegressionRequest) Reset 

func (m *RegressionRequest) Reset()

func (*RegressionRequest) String 

func (m *RegressionRequest) String() string

type RegressionResponse 

type RegressionResponse struct {
	Result *RegressionResult `protobuf:"bytes,1,opt,name=result" json:"result,omitempty"`
}

func (*RegressionResponse) Descriptor 

func (*RegressionResponse) Descriptor() ([]byte, []int)

func (*RegressionResponse) GetResult 

func (m *RegressionResponse) GetResult() *RegressionResult

func (*RegressionResponse) ProtoMessage 

func (*RegressionResponse) ProtoMessage()

func (*RegressionResponse) Reset 

func (m *RegressionResponse) Reset()

func (*RegressionResponse) String 

func (m *RegressionResponse) String() string

type RegressionResult 

type RegressionResult struct {
	Regressions []*Regression `protobuf:"bytes,1,rep,name=regressions" json:"regressions,omitempty"`
}

Contains one result per input example, in the same order as the input in RegressionRequest.

func (*RegressionResult) Descriptor 

func (*RegressionResult) Descriptor() ([]byte, []int)

func (*RegressionResult) GetRegressions 

func (m *RegressionResult) GetRegressions() []*Regression

func (*RegressionResult) ProtoMessage 

func (*RegressionResult) ProtoMessage()

func (*RegressionResult) Reset 

func (m *RegressionResult) Reset()

func (*RegressionResult) String 

func (m *RegressionResult) String() string

type SignatureDefMap 

type SignatureDefMap struct {
	SignatureDef map[string]*tensorflow13.SignatureDef `` /* 164-byte string literal not displayed */
}

Message returned for "signature_def" field.

func (*SignatureDefMap) Descriptor 

func (*SignatureDefMap) Descriptor() ([]byte, []int)

func (*SignatureDefMap) GetSignatureDef 

func (m *SignatureDefMap) GetSignatureDef() map[string]*tensorflow13.SignatureDef

func (*SignatureDefMap) ProtoMessage 

func (*SignatureDefMap) ProtoMessage()

func (*SignatureDefMap) Reset 

func (m *SignatureDefMap) Reset()

func (*SignatureDefMap) String 

func (m *SignatureDefMap) String() string

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 Package internal is a generated protocol buffer package.

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