Interface OnnxMl.AttributeProtoOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
OnnxMl.AttributeProto, OnnxMl.AttributeProto.Builder
Enclosing class:
OnnxMl
public static interface OnnxMl.AttributeProtoOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • hasName

      boolean hasName()
       The name field MUST be present for this version of the IR.
      optional string name = 1;
      Returns:
      Whether the name field is set.

    • getName

      String getName()
       The name field MUST be present for this version of the IR.
      optional string name = 1;
      Returns:
      The name.

    • getNameBytes

      com.google.protobuf.ByteString getNameBytes()
       The name field MUST be present for this version of the IR.
      optional string name = 1;
      Returns:
      The bytes for name.

    • hasRefAttrName

      boolean hasRefAttrName()
       if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
 In this case, this AttributeProto does not contain data, and it's a reference of attribute
 in parent scope.
 NOTE: This should ONLY be used in function (sub-graph). It's invalid to be used in main graph.
      optional string ref_attr_name = 21;
      Returns:
      Whether the refAttrName field is set.

    • getRefAttrName

      String getRefAttrName()
       if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
 In this case, this AttributeProto does not contain data, and it's a reference of attribute
 in parent scope.
 NOTE: This should ONLY be used in function (sub-graph). It's invalid to be used in main graph.
      optional string ref_attr_name = 21;
      Returns:
      The refAttrName.

    • getRefAttrNameBytes

      com.google.protobuf.ByteString getRefAttrNameBytes()
       if ref_attr_name is not empty, ref_attr_name is the attribute name in parent function.
 In this case, this AttributeProto does not contain data, and it's a reference of attribute
 in parent scope.
 NOTE: This should ONLY be used in function (sub-graph). It's invalid to be used in main graph.
      optional string ref_attr_name = 21;
      Returns:
      The bytes for refAttrName.

    • hasDocString

      boolean hasDocString()
       A human-readable documentation for this attribute. Markdown is allowed.
      optional string doc_string = 13;
      Returns:
      Whether the docString field is set.

    • getDocString

      String getDocString()
       A human-readable documentation for this attribute. Markdown is allowed.
      optional string doc_string = 13;
      Returns:
      The docString.

    • getDocStringBytes

      com.google.protobuf.ByteString getDocStringBytes()
       A human-readable documentation for this attribute. Markdown is allowed.
      optional string doc_string = 13;
      Returns:
      The bytes for docString.

    • hasType

      boolean hasType()
       The type field MUST be present for this version of the IR.
 For 0.0.1 versions of the IR, this field was not defined, and
 implementations needed to use has_field heuristics to determine
 which value field was in use.  For IR_VERSION 0.0.2 or later, this
 field MUST be set and match the f|i|s|t|... field in use.  This
 change was made to accommodate proto3 implementations.
      optional .onnx.AttributeProto.AttributeType type = 20;
      Returns:
      Whether the type field is set.

    • getType

      OnnxMl.AttributeProto.AttributeType getType()
       The type field MUST be present for this version of the IR.
 For 0.0.1 versions of the IR, this field was not defined, and
 implementations needed to use has_field heuristics to determine
 which value field was in use.  For IR_VERSION 0.0.2 or later, this
 field MUST be set and match the f|i|s|t|... field in use.  This
 change was made to accommodate proto3 implementations.
      optional .onnx.AttributeProto.AttributeType type = 20;
      Returns:
      The type.

    • hasF

      boolean hasF()
       Exactly ONE of the following fields must be present for this version of the IR
      optional float f = 2;
      Returns:
      Whether the f field is set.

    • getF

      float getF()
       Exactly ONE of the following fields must be present for this version of the IR
      optional float f = 2;
      Returns:
      The f.

    • hasI

      boolean hasI()
       int
      optional int64 i = 3;
      Returns:
      Whether the i field is set.

    • getI

      long getI()
       int
      optional int64 i = 3;
      Returns:
      The i.

    • hasS

      boolean hasS()
       UTF-8 string
      optional bytes s = 4;
      Returns:
      Whether the s field is set.

    • getS

      com.google.protobuf.ByteString getS()
       UTF-8 string
      optional bytes s = 4;
      Returns:
      The s.

    • hasT

      boolean hasT()
       tensor value
      optional .onnx.TensorProto t = 5;
      Returns:
      Whether the t field is set.

    • getT

      OnnxMl.TensorProto getT()
       tensor value
      optional .onnx.TensorProto t = 5;
      Returns:
      The t.

    • getTOrBuilder

      OnnxMl.TensorProtoOrBuilder getTOrBuilder()
       tensor value
      optional .onnx.TensorProto t = 5;

    • hasG

      boolean hasG()
       graph
      optional .onnx.GraphProto g = 6;
      Returns:
      Whether the g field is set.

    • getG

      OnnxMl.GraphProto getG()
       graph
      optional .onnx.GraphProto g = 6;
      Returns:
      The g.

    • getGOrBuilder

      OnnxMl.GraphProtoOrBuilder getGOrBuilder()
       graph
      optional .onnx.GraphProto g = 6;

    • hasSparseTensor

      boolean hasSparseTensor()
       sparse tensor value
      optional .onnx.SparseTensorProto sparse_tensor = 22;
      Returns:
      Whether the sparseTensor field is set.

    • getSparseTensor

      OnnxMl.SparseTensorProto getSparseTensor()
       sparse tensor value
      optional .onnx.SparseTensorProto sparse_tensor = 22;
      Returns:
      The sparseTensor.

    • getSparseTensorOrBuilder

      OnnxMl.SparseTensorProtoOrBuilder getSparseTensorOrBuilder()
       sparse tensor value
      optional .onnx.SparseTensorProto sparse_tensor = 22;

    • getFloatsList

      List<Float> getFloatsList()
       list of floats
      repeated float floats = 7;
      Returns:
      A list containing the floats.

    • getFloatsCount

      int getFloatsCount()
       list of floats
      repeated float floats = 7;
      Returns:
      The count of floats.

    • getFloats

      float getFloats(int index)
       list of floats
      repeated float floats = 7;
      Parameters:
      index - The index of the element to return.
      Returns:
      The floats at the given index.

    • getIntsList

      List<Long> getIntsList()
       list of ints
      repeated int64 ints = 8;
      Returns:
      A list containing the ints.

    • getIntsCount

      int getIntsCount()
       list of ints
      repeated int64 ints = 8;
      Returns:
      The count of ints.

    • getInts

      long getInts(int index)
       list of ints
      repeated int64 ints = 8;
      Parameters:
      index - The index of the element to return.
      Returns:
      The ints at the given index.

    • getStringsList

      List<com.google.protobuf.ByteString> getStringsList()
       list of UTF-8 strings
      repeated bytes strings = 9;
      Returns:
      A list containing the strings.

    • getStringsCount

      int getStringsCount()
       list of UTF-8 strings
      repeated bytes strings = 9;
      Returns:
      The count of strings.

    • getStrings

      com.google.protobuf.ByteString getStrings(int index)
       list of UTF-8 strings
      repeated bytes strings = 9;
      Parameters:
      index - The index of the element to return.
      Returns:
      The strings at the given index.

    • getTensorsList

      List<OnnxMl.TensorProto> getTensorsList()
       list of tensors
      repeated .onnx.TensorProto tensors = 10;

    • getTensors

      OnnxMl.TensorProto getTensors(int index)
       list of tensors
      repeated .onnx.TensorProto tensors = 10;

    • getTensorsCount

      int getTensorsCount()
       list of tensors
      repeated .onnx.TensorProto tensors = 10;

    • getTensorsOrBuilderList

      List<? extends OnnxMl.TensorProtoOrBuilder> getTensorsOrBuilderList()
       list of tensors
      repeated .onnx.TensorProto tensors = 10;

    • getTensorsOrBuilder

      OnnxMl.TensorProtoOrBuilder getTensorsOrBuilder(int index)
       list of tensors
      repeated .onnx.TensorProto tensors = 10;

    • getGraphsList

      List<OnnxMl.GraphProto> getGraphsList()
       list of graph
      repeated .onnx.GraphProto graphs = 11;

    • getGraphs

      OnnxMl.GraphProto getGraphs(int index)
       list of graph
      repeated .onnx.GraphProto graphs = 11;

    • getGraphsCount

      int getGraphsCount()
       list of graph
      repeated .onnx.GraphProto graphs = 11;

    • getGraphsOrBuilderList

      List<? extends OnnxMl.GraphProtoOrBuilder> getGraphsOrBuilderList()
       list of graph
      repeated .onnx.GraphProto graphs = 11;

    • getGraphsOrBuilder

      OnnxMl.GraphProtoOrBuilder getGraphsOrBuilder(int index)
       list of graph
      repeated .onnx.GraphProto graphs = 11;

    • getSparseTensorsList

      List<OnnxMl.SparseTensorProto> getSparseTensorsList()
       list of sparse tensors
      repeated .onnx.SparseTensorProto sparse_tensors = 23;

    • getSparseTensors

      OnnxMl.SparseTensorProto getSparseTensors(int index)
       list of sparse tensors
      repeated .onnx.SparseTensorProto sparse_tensors = 23;

    • getSparseTensorsCount

      int getSparseTensorsCount()
       list of sparse tensors
      repeated .onnx.SparseTensorProto sparse_tensors = 23;

    • getSparseTensorsOrBuilderList

      List<? extends OnnxMl.SparseTensorProtoOrBuilder> getSparseTensorsOrBuilderList()
       list of sparse tensors
      repeated .onnx.SparseTensorProto sparse_tensors = 23;

    • getSparseTensorsOrBuilder

      OnnxMl.SparseTensorProtoOrBuilder getSparseTensorsOrBuilder(int index)
       list of sparse tensors
      repeated .onnx.SparseTensorProto sparse_tensors = 23;