Package ai.onnx.proto

Interface OnnxMl.GraphProtoOrBuilder

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

  • Method Details

    • getNodeList

      List<OnnxMl.NodeProto> getNodeList()
       The nodes in the graph, sorted topologically.
      repeated .onnx.NodeProto node = 1;

    • getNode

      OnnxMl.NodeProto getNode(int index)
       The nodes in the graph, sorted topologically.
      repeated .onnx.NodeProto node = 1;

    • getNodeCount

      int getNodeCount()
       The nodes in the graph, sorted topologically.
      repeated .onnx.NodeProto node = 1;

    • getNodeOrBuilderList

      List<? extends OnnxMl.NodeProtoOrBuilder> getNodeOrBuilderList()
       The nodes in the graph, sorted topologically.
      repeated .onnx.NodeProto node = 1;

    • getNodeOrBuilder

      OnnxMl.NodeProtoOrBuilder getNodeOrBuilder(int index)
       The nodes in the graph, sorted topologically.
      repeated .onnx.NodeProto node = 1;

    • hasName

      boolean hasName()
       The name of the graph.
      optional string name = 2;
      Returns:
      Whether the name field is set.

    • getName

      String getName()
       The name of the graph.
      optional string name = 2;
      Returns:
      The name.

    • getNameBytes

      com.google.protobuf.ByteString getNameBytes()
       The name of the graph.
      optional string name = 2;
      Returns:
      The bytes for name.

    • getInitializerList

      List<OnnxMl.TensorProto> getInitializerList()
       A list of named tensor values, used to specify constant inputs of the graph.
 Each initializer (both TensorProto as well SparseTensorProto) MUST have a name.
 The name MUST be unique across both initializer and sparse_initializer,
 but the name MAY also appear in the input list.
      repeated .onnx.TensorProto initializer = 5;

    • getInitializer

      OnnxMl.TensorProto getInitializer(int index)
       A list of named tensor values, used to specify constant inputs of the graph.
 Each initializer (both TensorProto as well SparseTensorProto) MUST have a name.
 The name MUST be unique across both initializer and sparse_initializer,
 but the name MAY also appear in the input list.
      repeated .onnx.TensorProto initializer = 5;

    • getInitializerCount

      int getInitializerCount()
       A list of named tensor values, used to specify constant inputs of the graph.
 Each initializer (both TensorProto as well SparseTensorProto) MUST have a name.
 The name MUST be unique across both initializer and sparse_initializer,
 but the name MAY also appear in the input list.
      repeated .onnx.TensorProto initializer = 5;

    • getInitializerOrBuilderList

      List<? extends OnnxMl.TensorProtoOrBuilder> getInitializerOrBuilderList()
       A list of named tensor values, used to specify constant inputs of the graph.
 Each initializer (both TensorProto as well SparseTensorProto) MUST have a name.
 The name MUST be unique across both initializer and sparse_initializer,
 but the name MAY also appear in the input list.
      repeated .onnx.TensorProto initializer = 5;

    • getInitializerOrBuilder

      OnnxMl.TensorProtoOrBuilder getInitializerOrBuilder(int index)
       A list of named tensor values, used to specify constant inputs of the graph.
 Each initializer (both TensorProto as well SparseTensorProto) MUST have a name.
 The name MUST be unique across both initializer and sparse_initializer,
 but the name MAY also appear in the input list.
      repeated .onnx.TensorProto initializer = 5;

    • getSparseInitializerList

      List<OnnxMl.SparseTensorProto> getSparseInitializerList()
       Initializers (see above) stored in sparse format.
      repeated .onnx.SparseTensorProto sparse_initializer = 15;

    • getSparseInitializer

      OnnxMl.SparseTensorProto getSparseInitializer(int index)
       Initializers (see above) stored in sparse format.
      repeated .onnx.SparseTensorProto sparse_initializer = 15;

    • getSparseInitializerCount

      int getSparseInitializerCount()
       Initializers (see above) stored in sparse format.
      repeated .onnx.SparseTensorProto sparse_initializer = 15;

    • getSparseInitializerOrBuilderList

      List<? extends OnnxMl.SparseTensorProtoOrBuilder> getSparseInitializerOrBuilderList()
       Initializers (see above) stored in sparse format.
      repeated .onnx.SparseTensorProto sparse_initializer = 15;

    • getSparseInitializerOrBuilder

      OnnxMl.SparseTensorProtoOrBuilder getSparseInitializerOrBuilder(int index)
       Initializers (see above) stored in sparse format.
      repeated .onnx.SparseTensorProto sparse_initializer = 15;

    • hasDocString

      boolean hasDocString()
       A human-readable documentation for this graph. Markdown is allowed.
      optional string doc_string = 10;
      Returns:
      Whether the docString field is set.

    • getDocString

      String getDocString()
       A human-readable documentation for this graph. Markdown is allowed.
      optional string doc_string = 10;
      Returns:
      The docString.

    • getDocStringBytes

      com.google.protobuf.ByteString getDocStringBytes()
       A human-readable documentation for this graph. Markdown is allowed.
      optional string doc_string = 10;
      Returns:
      The bytes for docString.

    • getInputList

      List<OnnxMl.ValueInfoProto> getInputList()
       The inputs and outputs of the graph.
      repeated .onnx.ValueInfoProto input = 11;

    • getInput

      OnnxMl.ValueInfoProto getInput(int index)
       The inputs and outputs of the graph.
      repeated .onnx.ValueInfoProto input = 11;

    • getInputCount

      int getInputCount()
       The inputs and outputs of the graph.
      repeated .onnx.ValueInfoProto input = 11;

    • getInputOrBuilderList

      List<? extends OnnxMl.ValueInfoProtoOrBuilder> getInputOrBuilderList()
       The inputs and outputs of the graph.
      repeated .onnx.ValueInfoProto input = 11;

    • getInputOrBuilder

      OnnxMl.ValueInfoProtoOrBuilder getInputOrBuilder(int index)
       The inputs and outputs of the graph.
      repeated .onnx.ValueInfoProto input = 11;

    • getOutputList

      List<OnnxMl.ValueInfoProto> getOutputList()
      repeated .onnx.ValueInfoProto output = 12;

    • getOutput

      OnnxMl.ValueInfoProto getOutput(int index)
      repeated .onnx.ValueInfoProto output = 12;

    • getOutputCount

      int getOutputCount()
      repeated .onnx.ValueInfoProto output = 12;

    • getOutputOrBuilderList

      List<? extends OnnxMl.ValueInfoProtoOrBuilder> getOutputOrBuilderList()
      repeated .onnx.ValueInfoProto output = 12;

    • getOutputOrBuilder

      OnnxMl.ValueInfoProtoOrBuilder getOutputOrBuilder(int index)
      repeated .onnx.ValueInfoProto output = 12;

    • getValueInfoList

      List<OnnxMl.ValueInfoProto> getValueInfoList()
       Information for the values in the graph. The ValueInfoProto.name's
 must be distinct. It is optional for a value to appear in value_info list.
      repeated .onnx.ValueInfoProto value_info = 13;

    • getValueInfo

      OnnxMl.ValueInfoProto getValueInfo(int index)
       Information for the values in the graph. The ValueInfoProto.name's
 must be distinct. It is optional for a value to appear in value_info list.
      repeated .onnx.ValueInfoProto value_info = 13;

    • getValueInfoCount

      int getValueInfoCount()
       Information for the values in the graph. The ValueInfoProto.name's
 must be distinct. It is optional for a value to appear in value_info list.
      repeated .onnx.ValueInfoProto value_info = 13;

    • getValueInfoOrBuilderList

      List<? extends OnnxMl.ValueInfoProtoOrBuilder> getValueInfoOrBuilderList()
       Information for the values in the graph. The ValueInfoProto.name's
 must be distinct. It is optional for a value to appear in value_info list.
      repeated .onnx.ValueInfoProto value_info = 13;

    • getValueInfoOrBuilder

      OnnxMl.ValueInfoProtoOrBuilder getValueInfoOrBuilder(int index)
       Information for the values in the graph. The ValueInfoProto.name's
 must be distinct. It is optional for a value to appear in value_info list.
      repeated .onnx.ValueInfoProto value_info = 13;

    • getQuantizationAnnotationList

      List<OnnxMl.TensorAnnotation> getQuantizationAnnotationList()
       This field carries information to indicate the mapping among a tensor and its
 quantization parameter tensors. For example:
 For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated,
 which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
      repeated .onnx.TensorAnnotation quantization_annotation = 14;

    • getQuantizationAnnotation

      OnnxMl.TensorAnnotation getQuantizationAnnotation(int index)
       This field carries information to indicate the mapping among a tensor and its
 quantization parameter tensors. For example:
 For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated,
 which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
      repeated .onnx.TensorAnnotation quantization_annotation = 14;

    • getQuantizationAnnotationCount

      int getQuantizationAnnotationCount()
       This field carries information to indicate the mapping among a tensor and its
 quantization parameter tensors. For example:
 For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated,
 which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
      repeated .onnx.TensorAnnotation quantization_annotation = 14;

    • getQuantizationAnnotationOrBuilderList

      List<? extends OnnxMl.TensorAnnotationOrBuilder> getQuantizationAnnotationOrBuilderList()
       This field carries information to indicate the mapping among a tensor and its
 quantization parameter tensors. For example:
 For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated,
 which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
      repeated .onnx.TensorAnnotation quantization_annotation = 14;

    • getQuantizationAnnotationOrBuilder

      OnnxMl.TensorAnnotationOrBuilder getQuantizationAnnotationOrBuilder(int index)
       This field carries information to indicate the mapping among a tensor and its
 quantization parameter tensors. For example:
 For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated,
 which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
      repeated .onnx.TensorAnnotation quantization_annotation = 14;