type TensorProto struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  Dtype DataType `protobuf:"varint,1,opt,name=dtype,proto3,enum=tensorflow.DataType" json:"dtype,omitempty"`
  // Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
  TensorShape *TensorShapeProto `protobuf:"bytes,2,opt,name=tensor_shape,json=tensorShape,proto3" json:"tensor_shape,omitempty"`
  // Version number.
  //
  // In version 0, if the "repeated xxx" representations contain only one
  // element, that element is repeated to fill the shape.  This makes it easy
  // to represent a constant Tensor with a single value.
  VersionNumber int32 `protobuf:"varint,3,opt,name=version_number,json=versionNumber,proto3" json:"version_number,omitempty"`
  // Serialized raw tensor content from either Tensor::AsProtoTensorContent or
  // memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
  // can be used for all tensor types. The purpose of this representation is to
  // reduce serialization overhead during RPC call by avoiding serialization of
  // many repeated small items.
  TensorContent []byte `protobuf:"bytes,4,opt,name=tensor_content,json=tensorContent,proto3" json:"tensor_content,omitempty"`
  // DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
  // have some pointless zero padding for each value here.
  HalfVal []int32 `protobuf:"varint,13,rep,packed,name=half_val,json=halfVal,proto3" json:"half_val,omitempty"`
  // DT_FLOAT.
  FloatVal []float32 `protobuf:"fixed32,5,rep,packed,name=float_val,json=floatVal,proto3" json:"float_val,omitempty"`
  // DT_DOUBLE.
  DoubleVal []float64 `protobuf:"fixed64,6,rep,packed,name=double_val,json=doubleVal,proto3" json:"double_val,omitempty"`
  // DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
  IntVal []int32 `protobuf:"varint,7,rep,packed,name=int_val,json=intVal,proto3" json:"int_val,omitempty"`
  // DT_STRING
  StringVal [][]byte `protobuf:"bytes,8,rep,name=string_val,json=stringVal,proto3" json:"string_val,omitempty"`
  // DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
  // and imaginary parts of i-th single precision complex.
  ScomplexVal []float32 `protobuf:"fixed32,9,rep,packed,name=scomplex_val,json=scomplexVal,proto3" json:"scomplex_val,omitempty"`
  // DT_INT64
  Int64Val []int64 `protobuf:"varint,10,rep,packed,name=int64_val,json=int64Val,proto3" json:"int64_val,omitempty"`
  // DT_BOOL
  BoolVal []bool `protobuf:"varint,11,rep,packed,name=bool_val,json=boolVal,proto3" json:"bool_val,omitempty"`
  // DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
  // and imaginary parts of i-th double precision complex.
  DcomplexVal []float64 `protobuf:"fixed64,12,rep,packed,name=dcomplex_val,json=dcomplexVal,proto3" json:"dcomplex_val,omitempty"`
  // DT_RESOURCE
  ResourceHandleVal []*ResourceHandleProto `protobuf:"bytes,14,rep,name=resource_handle_val,json=resourceHandleVal,proto3" json:"resource_handle_val,omitempty"`
  // DT_VARIANT
  VariantVal []*VariantTensorDataProto `protobuf:"bytes,15,rep,name=variant_val,json=variantVal,proto3" json:"variant_val,omitempty"`
  // DT_UINT32
  Uint32Val []uint32 `protobuf:"varint,16,rep,packed,name=uint32_val,json=uint32Val,proto3" json:"uint32_val,omitempty"`
  // DT_UINT64
  Uint64Val []uint64 `protobuf:"varint,17,rep,packed,name=uint64_val,json=uint64Val,proto3" json:"uint64_val,omitempty"`
}

type PredictRequest struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  // Model Specification. If version is not specified, will use the latest
  // (numerical) version.
  ModelSpec *ModelSpec `protobuf:"bytes,1,opt,name=model_spec,json=modelSpec,proto3" json:"model_spec,omitempty"`
  // Input tensors.
  // Names of input tensor are alias names. The mapping from aliases to real
  // input tensor names is stored in the SavedModel export as a prediction
  // SignatureDef under the 'inputs' field.
  Inputs map[string]*framework.TensorProto `protobuf:"bytes,2,rep,name=inputs,proto3" json:"inputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
  // Output filter.
  // Names specified are alias names. The mapping from aliases to real output
  // tensor names is stored in the SavedModel export as a prediction
  // SignatureDef under the 'outputs' field.
  // 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,proto3" json:"output_filter,omitempty"`
}

// Response for PredictRequest on successful run.
type PredictResponse struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  // Effective Model Specification used to process PredictRequest.
  ModelSpec *ModelSpec `protobuf:"bytes,2,opt,name=model_spec,json=modelSpec,proto3" json:"model_spec,omitempty"`
  // Output tensors.
  Outputs map[string]*framework.TensorProto `protobuf:"bytes,1,rep,name=outputs,proto3" json:"outputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
}

// Metadata for an inference request such as the model name and version.
type ModelSpec struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  // Required servable name.
  Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
  // Optional choice of which version of the model to use.
  //
  // Recommended to be left unset in the common case. Should be specified only
  // when there is a strong version consistency requirement.
  //
  // When left unspecified, the system will serve the best available version.
  // This is typically the latest version, though during version transitions,
  // notably when serving on a fleet of instances, may be either the previous or
  // new version.
  //
  // Types that are assignable to VersionChoice:
  //	*ModelSpec_Version
  //	*ModelSpec_VersionLabel
  VersionChoice isModelSpec_VersionChoice `protobuf_oneof:"version_choice"`
  // A named signature to evaluate. If unspecified, the default signature will
  // be used.
  SignatureName string `protobuf:"bytes,3,opt,name=signature_name,json=signatureName,proto3" json:"signature_name,omitempty"`
}
// for VersionChoice
type ModelSpec_Version struct {
  // Use this specific version number.
  Version *wrappers.Int64Value `protobuf:"bytes,2,opt,name=version,proto3,oneof"`
}

type ModelSpec_VersionLabel struct {
  // Use the version associated with the given label.
  VersionLabel string `protobuf:"bytes,4,opt,name=version_label,json=versionLabel,proto3,oneof"`
}

type PredictLog struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  Request  *PredictRequest  `protobuf:"bytes,1,opt,name=request,proto3" json:"request,omitempty"`
  Response *PredictResponse `protobuf:"bytes,2,opt,name=response,proto3" json:"response,omitempty"`
}

type MultiInferenceLog struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  Request  *MultiInferenceRequest  `protobuf:"bytes,1,opt,name=request,proto3" json:"request,omitempty"`
  Response *MultiInferenceResponse `protobuf:"bytes,2,opt,name=response,proto3" json:"response,omitempty"`
}

// Logged model inference request.
type PredictionLog struct {
  state         protoimpl.MessageState
  sizeCache     protoimpl.SizeCache
  unknownFields protoimpl.UnknownFields

  LogMetadata *LogMetadata `protobuf:"bytes,1,opt,name=log_metadata,json=logMetadata,proto3" json:"log_metadata,omitempty"`
  // Types that are assignable to LogType:
  //	*PredictionLog_ClassifyLog
  //	*PredictionLog_RegressLog
  //	*PredictionLog_PredictLog
  //	*PredictionLog_MultiInferenceLog
  //	*PredictionLog_SessionRunLog
  LogType isPredictionLog_LogType `protobuf_oneof:"log_type"`
}