Package inference

Interface GrpcPredictV2.ModelInferResponseOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
GrpcPredictV2.ModelInferResponse, GrpcPredictV2.ModelInferResponse.Builder
Enclosing class:
GrpcPredictV2
public static interface GrpcPredictV2.ModelInferResponseOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • getModelName

      String getModelName()
       The name of the model used for inference.
      string model_name = 1;
      Returns:
      The modelName.

    • getModelNameBytes

      com.google.protobuf.ByteString getModelNameBytes()
       The name of the model used for inference.
      string model_name = 1;
      Returns:
      The bytes for modelName.

    • getModelVersion

      String getModelVersion()
       The version of the model used for inference.
      string model_version = 2;
      Returns:
      The modelVersion.

    • getModelVersionBytes

      com.google.protobuf.ByteString getModelVersionBytes()
       The version of the model used for inference.
      string model_version = 2;
      Returns:
      The bytes for modelVersion.

    • getId

      String getId()
       The id of the inference request if one was specified.
      string id = 3;
      Returns:
      The id.

    • getIdBytes

      com.google.protobuf.ByteString getIdBytes()
       The id of the inference request if one was specified.
      string id = 3;
      Returns:
      The bytes for id.

    • getParametersCount

      int getParametersCount()
       Optional inference response parameters.
      map<string, .inference.InferParameter> parameters = 4;

    • containsParameters

      boolean containsParameters(String key)
       Optional inference response parameters.
      map<string, .inference.InferParameter> parameters = 4;

    • getParameters

      @Deprecated Map<String,GrpcPredictV2.InferParameter> getParameters()
      Deprecated.
      Use getParametersMap() instead.

    • getParametersMap

      Map<String,GrpcPredictV2.InferParameter> getParametersMap()
       Optional inference response parameters.
      map<string, .inference.InferParameter> parameters = 4;

    • getParametersOrDefault

      GrpcPredictV2.InferParameter getParametersOrDefault(String key, GrpcPredictV2.InferParameter defaultValue)
       Optional inference response parameters.
      map<string, .inference.InferParameter> parameters = 4;

    • getParametersOrThrow

      GrpcPredictV2.InferParameter getParametersOrThrow(String key)
       Optional inference response parameters.
      map<string, .inference.InferParameter> parameters = 4;

    • getOutputsList

      List<GrpcPredictV2.ModelInferResponse.InferOutputTensor> getOutputsList()
       The output tensors holding inference results.
      repeated .inference.ModelInferResponse.InferOutputTensor outputs = 5;

    • getOutputs

      GrpcPredictV2.ModelInferResponse.InferOutputTensor getOutputs(int index)
       The output tensors holding inference results.
      repeated .inference.ModelInferResponse.InferOutputTensor outputs = 5;

    • getOutputsCount

      int getOutputsCount()
       The output tensors holding inference results.
      repeated .inference.ModelInferResponse.InferOutputTensor outputs = 5;

    • getOutputsOrBuilderList

      List<? extends GrpcPredictV2.ModelInferResponse.InferOutputTensorOrBuilder> getOutputsOrBuilderList()
       The output tensors holding inference results.
      repeated .inference.ModelInferResponse.InferOutputTensor outputs = 5;

    • getOutputsOrBuilder

      GrpcPredictV2.ModelInferResponse.InferOutputTensorOrBuilder getOutputsOrBuilder(int index)
       The output tensors holding inference results.
      repeated .inference.ModelInferResponse.InferOutputTensor outputs = 5;

    • getRawOutputContentsList

      List<com.google.protobuf.ByteString> getRawOutputContentsList()
       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 and BF16 data types 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.
      repeated bytes raw_output_contents = 6;
      Returns:
      A list containing the rawOutputContents.

    • getRawOutputContentsCount

      int getRawOutputContentsCount()
       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 and BF16 data types 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.
      repeated bytes raw_output_contents = 6;
      Returns:
      The count of rawOutputContents.

    • getRawOutputContents

      com.google.protobuf.ByteString getRawOutputContents(int index)
       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 and BF16 data types 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.
      repeated bytes raw_output_contents = 6;
      Parameters:
      index - The index of the element to return.
      Returns:
      The rawOutputContents at the given index.