Uses of Class
ai.onnx.proto.OnnxMl.TensorProto.Builder
Packages that use OnnxMl.TensorProto.Builder
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Uses of OnnxMl.TensorProto.Builder in ai.onnx.proto
Methods in ai.onnx.proto that return OnnxMl.TensorProto.BuilderModifier and TypeMethodDescriptionOnnxMl.TensorProto.Builder.addAllDims(Iterable<? extends Long> values) The shape of the tensor.OnnxMl.TensorProto.Builder.addAllDoubleData(Iterable<? extends Double> values) For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.addAllExternalData(Iterable<? extends OnnxMl.StringStringEntryProto> values) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.addAllFloatData(Iterable<? extends Float> values) For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.addAllInt32Data(Iterable<? extends Integer> values) For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.OnnxMl.TensorProto.Builder.addAllInt64Data(Iterable<? extends Long> values) For int64.OnnxMl.TensorProto.Builder.addAllStringData(Iterable<? extends com.google.protobuf.ByteString> values) For strings.OnnxMl.TensorProto.Builder.addAllUint64Data(Iterable<? extends Long> values) For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.Builder.addDims(long value) The shape of the tensor.OnnxMl.TensorProto.Builder.addDoubleData(double value) For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.addExternalData(int index, OnnxMl.StringStringEntryProto value) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.addExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.addExternalData(OnnxMl.StringStringEntryProto value) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.addExternalData(OnnxMl.StringStringEntryProto.Builder builderForValue) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.addFloatData(float value) For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.GraphProto.Builder.addInitializerBuilder()A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.GraphProto.Builder.addInitializerBuilder(int index) A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.TensorProto.Builder.addInt32Data(int value) For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.OnnxMl.TensorProto.Builder.addInt64Data(long value) For int64.OnnxMl.TensorProto.Builder.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OnnxMl.TensorProto.Builder.addStringData(com.google.protobuf.ByteString value) For strings.OnnxMl.AttributeProto.Builder.addTensorsBuilder()list of tensorsOnnxMl.AttributeProto.Builder.addTensorsBuilder(int index) list of tensorsOnnxMl.TensorProto.Builder.addUint64Data(long value) For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.Builder.clear()OnnxMl.TensorProto.Builder.clearDataLocation()If value not set, data is stored in raw_data (if set) otherwise in type-specified field.OnnxMl.TensorProto.Builder.clearDataType()The data type of the tensor.OnnxMl.TensorProto.Builder.clearDims()The shape of the tensor.OnnxMl.TensorProto.Builder.clearDocString()A human-readable documentation for this tensor.OnnxMl.TensorProto.Builder.clearDoubleData()For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.clearExternalData()Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.clearField(com.google.protobuf.Descriptors.FieldDescriptor field) OnnxMl.TensorProto.Builder.clearFloatData()For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.clearInt32Data()For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.OnnxMl.TensorProto.Builder.clearInt64Data()For int64.OnnxMl.TensorProto.Builder.clearName()Optionally, a name for the tensor.OnnxMl.TensorProto.Builder.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) OnnxMl.TensorProto.Builder.clearRawData()Serializations can either use one of the fields above, or use this raw bytes field.OnnxMl.TensorProto.Builder.clearSegment()optional .onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.Builder.clearStringData()For strings.OnnxMl.TensorProto.Builder.clearUint64Data()For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.Builder.clone()OnnxMl.SparseTensorProto.Builder.getIndicesBuilder()The indices of the non-default values, which may be stored in one of two formats.OnnxMl.GraphProto.Builder.getInitializerBuilder(int index) A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.AttributeProto.Builder.getTBuilder()tensor valueOnnxMl.AttributeProto.Builder.getTensorsBuilder(int index) list of tensorsOnnxMl.SparseTensorProto.Builder.getValuesBuilder()The sequence of non-default values are encoded as a tensor of shape [NNZ].OnnxMl.TensorProto.Builder.mergeFrom(OnnxMl.TensorProto other) OnnxMl.TensorProto.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) OnnxMl.TensorProto.Builder.mergeFrom(com.google.protobuf.Message other) OnnxMl.TensorProto.Builder.mergeSegment(OnnxMl.TensorProto.Segment value) optional .onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.Builder.mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) static OnnxMl.TensorProto.BuilderOnnxMl.TensorProto.newBuilder()static OnnxMl.TensorProto.BuilderOnnxMl.TensorProto.newBuilder(OnnxMl.TensorProto prototype) OnnxMl.TensorProto.newBuilderForType()protected OnnxMl.TensorProto.BuilderOnnxMl.TensorProto.newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) OnnxMl.TensorProto.Builder.removeExternalData(int index) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.setDataLocation(OnnxMl.TensorProto.DataLocation value) If value not set, data is stored in raw_data (if set) otherwise in type-specified field.OnnxMl.TensorProto.Builder.setDataType(int value) The data type of the tensor.OnnxMl.TensorProto.Builder.setDims(int index, long value) The shape of the tensor.OnnxMl.TensorProto.Builder.setDocString(String value) A human-readable documentation for this tensor.OnnxMl.TensorProto.Builder.setDocStringBytes(com.google.protobuf.ByteString value) A human-readable documentation for this tensor.OnnxMl.TensorProto.Builder.setDoubleData(int index, double value) For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.setExternalData(int index, OnnxMl.StringStringEntryProto value) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.setExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.Builder.setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OnnxMl.TensorProto.Builder.setFloatData(int index, float value) For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.OnnxMl.TensorProto.Builder.setInt32Data(int index, int value) For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.OnnxMl.TensorProto.Builder.setInt64Data(int index, long value) For int64.Optionally, a name for the tensor.OnnxMl.TensorProto.Builder.setNameBytes(com.google.protobuf.ByteString value) Optionally, a name for the tensor.OnnxMl.TensorProto.Builder.setRawData(com.google.protobuf.ByteString value) Serializations can either use one of the fields above, or use this raw bytes field.OnnxMl.TensorProto.Builder.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) OnnxMl.TensorProto.Builder.setSegment(OnnxMl.TensorProto.Segment value) optional .onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.Builder.setSegment(OnnxMl.TensorProto.Segment.Builder builderForValue) optional .onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.Builder.setStringData(int index, com.google.protobuf.ByteString value) For strings.OnnxMl.TensorProto.Builder.setUint64Data(int index, long value) For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.Builder.setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) OnnxMl.TensorProto.toBuilder()Methods in ai.onnx.proto that return types with arguments of type OnnxMl.TensorProto.BuilderModifier and TypeMethodDescriptionOnnxMl.GraphProto.Builder.getInitializerBuilderList()A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.AttributeProto.Builder.getTensorsBuilderList()list of tensorsMethods in ai.onnx.proto with parameters of type OnnxMl.TensorProto.BuilderModifier and TypeMethodDescriptionOnnxMl.GraphProto.Builder.addInitializer(int index, OnnxMl.TensorProto.Builder builderForValue) A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.GraphProto.Builder.addInitializer(OnnxMl.TensorProto.Builder builderForValue) A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.AttributeProto.Builder.addTensors(int index, OnnxMl.TensorProto.Builder builderForValue) list of tensorsOnnxMl.AttributeProto.Builder.addTensors(OnnxMl.TensorProto.Builder builderForValue) list of tensorsOnnxMl.SparseTensorProto.Builder.setIndices(OnnxMl.TensorProto.Builder builderForValue) The indices of the non-default values, which may be stored in one of two formats.OnnxMl.GraphProto.Builder.setInitializer(int index, OnnxMl.TensorProto.Builder builderForValue) A list of named tensor values, used to specify constant inputs of the graph.OnnxMl.AttributeProto.Builder.setT(OnnxMl.TensorProto.Builder builderForValue) tensor valueOnnxMl.AttributeProto.Builder.setTensors(int index, OnnxMl.TensorProto.Builder builderForValue) list of tensorsOnnxMl.SparseTensorProto.Builder.setValues(OnnxMl.TensorProto.Builder builderForValue) The sequence of non-default values are encoded as a tensor of shape [NNZ].