Package onnx
Class OnnxMl.TensorProto.Builder
- java.lang.Object
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- org.nd4j.shade.protobuf.AbstractMessageLite.Builder
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- org.nd4j.shade.protobuf.AbstractMessage.Builder<BuilderType>
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- org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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- onnx.OnnxMl.TensorProto.Builder
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- All Implemented Interfaces:
Cloneable,OnnxMl.TensorProtoOrBuilder,org.nd4j.shade.protobuf.Message.Builder,org.nd4j.shade.protobuf.MessageLite.Builder,org.nd4j.shade.protobuf.MessageLiteOrBuilder,org.nd4j.shade.protobuf.MessageOrBuilder
- Enclosing class:
- OnnxMl.TensorProto
public static final class OnnxMl.TensorProto.Builder extends org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder> implements OnnxMl.TensorProtoOrBuilder
Tensors A serialized tensor value.
Protobuf typeonnx.TensorProto
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description OnnxMl.TensorProto.BuilderaddAllDims(Iterable<? extends Long> values)The shape of the tensor.OnnxMl.TensorProto.BuilderaddAllDoubleData(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.BuilderaddAllExternalData(Iterable<? extends OnnxMl.StringStringEntryProto> values)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderaddAllFloatData(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.BuilderaddAllInt32Data(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.BuilderaddAllInt64Data(Iterable<? extends Long> values)For int64.OnnxMl.TensorProto.BuilderaddAllStringData(Iterable<? extends org.nd4j.shade.protobuf.ByteString> values)For strings.OnnxMl.TensorProto.BuilderaddAllUint64Data(Iterable<? extends Long> values)For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.BuilderaddDims(long value)The shape of the tensor.OnnxMl.TensorProto.BuilderaddDoubleData(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.BuilderaddExternalData(int index, OnnxMl.StringStringEntryProto value)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderaddExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderaddExternalData(OnnxMl.StringStringEntryProto value)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderaddExternalData(OnnxMl.StringStringEntryProto.Builder builderForValue)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.StringStringEntryProto.BuilderaddExternalDataBuilder()Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.StringStringEntryProto.BuilderaddExternalDataBuilder(int index)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderaddFloatData(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.BuilderaddInt32Data(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.BuilderaddInt64Data(long value)For int64.OnnxMl.TensorProto.BuilderaddRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)OnnxMl.TensorProto.BuilderaddStringData(org.nd4j.shade.protobuf.ByteString value)For strings.OnnxMl.TensorProto.BuilderaddUint64Data(long value)For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProtobuild()OnnxMl.TensorProtobuildPartial()OnnxMl.TensorProto.Builderclear()OnnxMl.TensorProto.BuilderclearDataLocation()If value not set, data is stored in raw_data (if set) otherwise in type-specified field.OnnxMl.TensorProto.BuilderclearDataType()The data type of the tensor.OnnxMl.TensorProto.BuilderclearDims()The shape of the tensor.OnnxMl.TensorProto.BuilderclearDocString()A human-readable documentation for this tensor.OnnxMl.TensorProto.BuilderclearDoubleData()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.BuilderclearExternalData()Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuilderclearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)OnnxMl.TensorProto.BuilderclearFloatData()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.BuilderclearInt32Data()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.BuilderclearInt64Data()For int64.OnnxMl.TensorProto.BuilderclearName()Optionally, a name for the tensor.OnnxMl.TensorProto.BuilderclearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)OnnxMl.TensorProto.BuilderclearRawData()Serializations can either use one of the fields above, or use this raw bytes field.OnnxMl.TensorProto.BuilderclearSegment().onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.BuilderclearStringData()For strings.OnnxMl.TensorProto.BuilderclearUint64Data()For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.Builderclone()OnnxMl.TensorProto.DataLocationgetDataLocation()If value not set, data is stored in raw_data (if set) otherwise in type-specified field.intgetDataLocationValue()If value not set, data is stored in raw_data (if set) otherwise in type-specified field.intgetDataType()The data type of the tensor.OnnxMl.TensorProtogetDefaultInstanceForType()static org.nd4j.shade.protobuf.Descriptors.DescriptorgetDescriptor()org.nd4j.shade.protobuf.Descriptors.DescriptorgetDescriptorForType()longgetDims(int index)The shape of the tensor.intgetDimsCount()The shape of the tensor.List<Long>getDimsList()The shape of the tensor.StringgetDocString()A human-readable documentation for this tensor.org.nd4j.shade.protobuf.ByteStringgetDocStringBytes()A human-readable documentation for this tensor.doublegetDoubleData(int index)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.intgetDoubleDataCount()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.List<Double>getDoubleDataList()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.StringStringEntryProtogetExternalData(int index)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.StringStringEntryProto.BuildergetExternalDataBuilder(int index)Data can be stored inside the protobuf file using type-specific fields or raw_data.List<OnnxMl.StringStringEntryProto.Builder>getExternalDataBuilderList()Data can be stored inside the protobuf file using type-specific fields or raw_data.intgetExternalDataCount()Data can be stored inside the protobuf file using type-specific fields or raw_data.List<OnnxMl.StringStringEntryProto>getExternalDataList()Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.StringStringEntryProtoOrBuildergetExternalDataOrBuilder(int index)Data can be stored inside the protobuf file using type-specific fields or raw_data.List<? extends OnnxMl.StringStringEntryProtoOrBuilder>getExternalDataOrBuilderList()Data can be stored inside the protobuf file using type-specific fields or raw_data.floatgetFloatData(int index)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.intgetFloatDataCount()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.List<Float>getFloatDataList()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.intgetInt32Data(int index)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.intgetInt32DataCount()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.List<Integer>getInt32DataList()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.longgetInt64Data(int index)For int64.intgetInt64DataCount()For int64.List<Long>getInt64DataList()For int64.StringgetName()Optionally, a name for the tensor.org.nd4j.shade.protobuf.ByteStringgetNameBytes()Optionally, a name for the tensor.org.nd4j.shade.protobuf.ByteStringgetRawData()Serializations can either use one of the fields above, or use this raw bytes field.OnnxMl.TensorProto.SegmentgetSegment().onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.Segment.BuildergetSegmentBuilder().onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.SegmentOrBuildergetSegmentOrBuilder().onnx.TensorProto.Segment segment = 3;org.nd4j.shade.protobuf.ByteStringgetStringData(int index)For strings.intgetStringDataCount()For strings.List<org.nd4j.shade.protobuf.ByteString>getStringDataList()For strings.longgetUint64Data(int index)For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64intgetUint64DataCount()For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64List<Long>getUint64DataList()For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64booleanhasSegment().onnx.TensorProto.Segment segment = 3;protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTableinternalGetFieldAccessorTable()booleanisInitialized()OnnxMl.TensorProto.BuildermergeFrom(OnnxMl.TensorProto other)OnnxMl.TensorProto.BuildermergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)OnnxMl.TensorProto.BuildermergeFrom(org.nd4j.shade.protobuf.Message other)OnnxMl.TensorProto.BuildermergeSegment(OnnxMl.TensorProto.Segment value).onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.BuildermergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)OnnxMl.TensorProto.BuilderremoveExternalData(int index)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuildersetDataLocation(OnnxMl.TensorProto.DataLocation value)If value not set, data is stored in raw_data (if set) otherwise in type-specified field.OnnxMl.TensorProto.BuildersetDataLocationValue(int value)If value not set, data is stored in raw_data (if set) otherwise in type-specified field.OnnxMl.TensorProto.BuildersetDataType(int value)The data type of the tensor.OnnxMl.TensorProto.BuildersetDims(int index, long value)The shape of the tensor.OnnxMl.TensorProto.BuildersetDocString(String value)A human-readable documentation for this tensor.OnnxMl.TensorProto.BuildersetDocStringBytes(org.nd4j.shade.protobuf.ByteString value)A human-readable documentation for this tensor.OnnxMl.TensorProto.BuildersetDoubleData(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.BuildersetExternalData(int index, OnnxMl.StringStringEntryProto value)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuildersetExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue)Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.BuildersetField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)OnnxMl.TensorProto.BuildersetFloatData(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.BuildersetInt32Data(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.BuildersetInt64Data(int index, long value)For int64.OnnxMl.TensorProto.BuildersetName(String value)Optionally, a name for the tensor.OnnxMl.TensorProto.BuildersetNameBytes(org.nd4j.shade.protobuf.ByteString value)Optionally, a name for the tensor.OnnxMl.TensorProto.BuildersetRawData(org.nd4j.shade.protobuf.ByteString value)Serializations can either use one of the fields above, or use this raw bytes field.OnnxMl.TensorProto.BuildersetRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)OnnxMl.TensorProto.BuildersetSegment(OnnxMl.TensorProto.Segment value).onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.BuildersetSegment(OnnxMl.TensorProto.Segment.Builder builderForValue).onnx.TensorProto.Segment segment = 3;OnnxMl.TensorProto.BuildersetStringData(int index, org.nd4j.shade.protobuf.ByteString value)For strings.OnnxMl.TensorProto.BuildersetUint64Data(int index, long value)For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64OnnxMl.TensorProto.BuildersetUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)-
Methods inherited from class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3
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Methods inherited from class org.nd4j.shade.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString
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Methods inherited from class org.nd4j.shade.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException
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Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Method Detail
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getDescriptor
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()
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internalGetFieldAccessorTable
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
- Specified by:
internalGetFieldAccessorTablein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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clear
public OnnxMl.TensorProto.Builder clear()
- Specified by:
clearin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
clearin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
clearin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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getDescriptorForType
public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
- Specified by:
getDescriptorForTypein interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfaceorg.nd4j.shade.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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getDefaultInstanceForType
public OnnxMl.TensorProto getDefaultInstanceForType()
- Specified by:
getDefaultInstanceForTypein interfaceorg.nd4j.shade.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfaceorg.nd4j.shade.protobuf.MessageOrBuilder
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build
public OnnxMl.TensorProto build()
- Specified by:
buildin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
buildin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder
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buildPartial
public OnnxMl.TensorProto buildPartial()
- Specified by:
buildPartialin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
buildPartialin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder
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clone
public OnnxMl.TensorProto.Builder clone()
- Specified by:
clonein interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
clonein interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
clonein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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setField
public OnnxMl.TensorProto.Builder setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
setFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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clearField
public OnnxMl.TensorProto.Builder clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
- Specified by:
clearFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
clearFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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clearOneof
public OnnxMl.TensorProto.Builder clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
- Specified by:
clearOneofin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
clearOneofin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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setRepeatedField
public OnnxMl.TensorProto.Builder setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
- Specified by:
setRepeatedFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setRepeatedFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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addRepeatedField
public OnnxMl.TensorProto.Builder addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
addRepeatedFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
addRepeatedFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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mergeFrom
public OnnxMl.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.Message other)
- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
mergeFromin classorg.nd4j.shade.protobuf.AbstractMessage.Builder<OnnxMl.TensorProto.Builder>
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mergeFrom
public OnnxMl.TensorProto.Builder mergeFrom(OnnxMl.TensorProto other)
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isInitialized
public final boolean isInitialized()
- Specified by:
isInitializedin interfaceorg.nd4j.shade.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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mergeFrom
public OnnxMl.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
mergeFromin classorg.nd4j.shade.protobuf.AbstractMessage.Builder<OnnxMl.TensorProto.Builder>- Throws:
IOException
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getDimsList
public List<Long> getDimsList()
The shape of the tensor.
repeated int64 dims = 1;- Specified by:
getDimsListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the dims.
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getDimsCount
public int getDimsCount()
The shape of the tensor.
repeated int64 dims = 1;- Specified by:
getDimsCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of dims.
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getDims
public long getDims(int index)
The shape of the tensor.
repeated int64 dims = 1;- Specified by:
getDimsin interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The dims at the given index.
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setDims
public OnnxMl.TensorProto.Builder setDims(int index, long value)
The shape of the tensor.
repeated int64 dims = 1;- Parameters:
index- The index to set the value at.value- The dims to set.- Returns:
- This builder for chaining.
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addDims
public OnnxMl.TensorProto.Builder addDims(long value)
The shape of the tensor.
repeated int64 dims = 1;- Parameters:
value- The dims to add.- Returns:
- This builder for chaining.
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addAllDims
public OnnxMl.TensorProto.Builder addAllDims(Iterable<? extends Long> values)
The shape of the tensor.
repeated int64 dims = 1;- Parameters:
values- The dims to add.- Returns:
- This builder for chaining.
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clearDims
public OnnxMl.TensorProto.Builder clearDims()
The shape of the tensor.
repeated int64 dims = 1;- Returns:
- This builder for chaining.
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getDataType
public int getDataType()
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;- Specified by:
getDataTypein interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The dataType.
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setDataType
public OnnxMl.TensorProto.Builder setDataType(int value)
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;- Parameters:
value- The dataType to set.- Returns:
- This builder for chaining.
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clearDataType
public OnnxMl.TensorProto.Builder clearDataType()
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;- Returns:
- This builder for chaining.
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hasSegment
public boolean hasSegment()
.onnx.TensorProto.Segment segment = 3;- Specified by:
hasSegmentin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- Whether the segment field is set.
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getSegment
public OnnxMl.TensorProto.Segment getSegment()
.onnx.TensorProto.Segment segment = 3;- Specified by:
getSegmentin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The segment.
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setSegment
public OnnxMl.TensorProto.Builder setSegment(OnnxMl.TensorProto.Segment value)
.onnx.TensorProto.Segment segment = 3;
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setSegment
public OnnxMl.TensorProto.Builder setSegment(OnnxMl.TensorProto.Segment.Builder builderForValue)
.onnx.TensorProto.Segment segment = 3;
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mergeSegment
public OnnxMl.TensorProto.Builder mergeSegment(OnnxMl.TensorProto.Segment value)
.onnx.TensorProto.Segment segment = 3;
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clearSegment
public OnnxMl.TensorProto.Builder clearSegment()
.onnx.TensorProto.Segment segment = 3;
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getSegmentBuilder
public OnnxMl.TensorProto.Segment.Builder getSegmentBuilder()
.onnx.TensorProto.Segment segment = 3;
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getSegmentOrBuilder
public OnnxMl.TensorProto.SegmentOrBuilder getSegmentOrBuilder()
.onnx.TensorProto.Segment segment = 3;- Specified by:
getSegmentOrBuilderin interfaceOnnxMl.TensorProtoOrBuilder
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getFloatDataList
public List<Float> getFloatDataList()
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Specified by:
getFloatDataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the floatData.
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getFloatDataCount
public int getFloatDataCount()
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Specified by:
getFloatDataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of floatData.
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getFloatData
public float getFloatData(int index)
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Specified by:
getFloatDatain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The floatData at the given index.
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setFloatData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Parameters:
index- The index to set the value at.value- The floatData to set.- Returns:
- This builder for chaining.
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addFloatData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Parameters:
value- The floatData to add.- Returns:
- This builder for chaining.
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addAllFloatData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Parameters:
values- The floatData to add.- Returns:
- This builder for chaining.
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clearFloatData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be FLOAT or COMPLEX64.
repeated float float_data = 4 [packed = true];- Returns:
- This builder for chaining.
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getInt32DataList
public List<Integer> getInt32DataList()
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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Specified by:
getInt32DataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the int32Data.
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getInt32DataCount
public int getInt32DataCount()
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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Specified by:
getInt32DataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of int32Data.
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getInt32Data
public int getInt32Data(int index)
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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Specified by:
getInt32Datain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The int32Data at the given index.
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setInt32Data
public 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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Parameters:
index- The index to set the value at.value- The int32Data to set.- Returns:
- This builder for chaining.
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addInt32Data
public 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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Parameters:
value- The int32Data to add.- Returns:
- This builder for chaining.
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addAllInt32Data
public 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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Parameters:
values- The int32Data to add.- Returns:
- This builder for chaining.
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clearInt32Data
public 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. When this field is present, the data_type field MUST be INT32, INT16, INT8, UINT16, UINT8, BOOL, or FLOAT16
repeated int32 int32_data = 5 [packed = true];- Returns:
- This builder for chaining.
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getStringDataList
public List<org.nd4j.shade.protobuf.ByteString> getStringDataList()
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Specified by:
getStringDataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the stringData.
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getStringDataCount
public int getStringDataCount()
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Specified by:
getStringDataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of stringData.
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getStringData
public org.nd4j.shade.protobuf.ByteString getStringData(int index)
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Specified by:
getStringDatain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The stringData at the given index.
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setStringData
public OnnxMl.TensorProto.Builder setStringData(int index, org.nd4j.shade.protobuf.ByteString value)
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Parameters:
index- The index to set the value at.value- The stringData to set.- Returns:
- This builder for chaining.
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addStringData
public OnnxMl.TensorProto.Builder addStringData(org.nd4j.shade.protobuf.ByteString value)
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Parameters:
value- The stringData to add.- Returns:
- This builder for chaining.
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addAllStringData
public OnnxMl.TensorProto.Builder addAllStringData(Iterable<? extends org.nd4j.shade.protobuf.ByteString> values)
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Parameters:
values- The stringData to add.- Returns:
- This builder for chaining.
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clearStringData
public OnnxMl.TensorProto.Builder clearStringData()
For strings. Each element of string_data is a UTF-8 encoded Unicode string. No trailing null, no leading BOM. The protobuf "string" scalar type is not used to match ML community conventions. When this field is present, the data_type field MUST be STRING
repeated bytes string_data = 6;- Returns:
- This builder for chaining.
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getInt64DataList
public List<Long> getInt64DataList()
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Specified by:
getInt64DataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the int64Data.
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getInt64DataCount
public int getInt64DataCount()
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Specified by:
getInt64DataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of int64Data.
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getInt64Data
public long getInt64Data(int index)
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Specified by:
getInt64Datain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The int64Data at the given index.
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setInt64Data
public OnnxMl.TensorProto.Builder setInt64Data(int index, long value)
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Parameters:
index- The index to set the value at.value- The int64Data to set.- Returns:
- This builder for chaining.
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addInt64Data
public OnnxMl.TensorProto.Builder addInt64Data(long value)
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Parameters:
value- The int64Data to add.- Returns:
- This builder for chaining.
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addAllInt64Data
public OnnxMl.TensorProto.Builder addAllInt64Data(Iterable<? extends Long> values)
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Parameters:
values- The int64Data to add.- Returns:
- This builder for chaining.
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clearInt64Data
public OnnxMl.TensorProto.Builder clearInt64Data()
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];- Returns:
- This builder for chaining.
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getName
public String getName()
Optionally, a name for the tensor.
string name = 8;- Specified by:
getNamein interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The name.
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getNameBytes
public org.nd4j.shade.protobuf.ByteString getNameBytes()
Optionally, a name for the tensor.
string name = 8;- Specified by:
getNameBytesin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The bytes for name.
-
setName
public OnnxMl.TensorProto.Builder setName(String value)
Optionally, a name for the tensor.
string name = 8;- Parameters:
value- The name to set.- Returns:
- This builder for chaining.
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clearName
public OnnxMl.TensorProto.Builder clearName()
Optionally, a name for the tensor.
string name = 8;- Returns:
- This builder for chaining.
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setNameBytes
public OnnxMl.TensorProto.Builder setNameBytes(org.nd4j.shade.protobuf.ByteString value)
Optionally, a name for the tensor.
string name = 8;- Parameters:
value- The bytes for name to set.- Returns:
- This builder for chaining.
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getDocString
public String getDocString()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;- Specified by:
getDocStringin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The docString.
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getDocStringBytes
public org.nd4j.shade.protobuf.ByteString getDocStringBytes()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;- Specified by:
getDocStringBytesin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The bytes for docString.
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setDocString
public OnnxMl.TensorProto.Builder setDocString(String value)
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;- Parameters:
value- The docString to set.- Returns:
- This builder for chaining.
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clearDocString
public OnnxMl.TensorProto.Builder clearDocString()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;- Returns:
- This builder for chaining.
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setDocStringBytes
public OnnxMl.TensorProto.Builder setDocStringBytes(org.nd4j.shade.protobuf.ByteString value)
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;- Parameters:
value- The bytes for docString to set.- Returns:
- This builder for chaining.
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getRawData
public org.nd4j.shade.protobuf.ByteString getRawData()
Serializations can either use one of the fields above, or use this raw bytes field. The only exception is the string case, where one is required to store the content in the repeated bytes string_data field. When this raw_data field is used to store tensor value, elements MUST be stored in as fixed-width, little-endian order. Floating-point data types MUST be stored in IEEE 754 format. Complex64 elements must be written as two consecutive FLOAT values, real component first. Complex128 elements must be written as two consecutive DOUBLE values, real component first. Boolean type MUST be written one byte per tensor element (00000001 for true, 00000000 for false). Note: the advantage of specific field rather than the raw_data field is that in some cases (e.g. int data), protobuf does a better packing via variable length storage, and may lead to smaller binary footprint. When this field is present, the data_type field MUST NOT be STRING or UNDEFINED
bytes raw_data = 9;- Specified by:
getRawDatain interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The rawData.
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setRawData
public OnnxMl.TensorProto.Builder setRawData(org.nd4j.shade.protobuf.ByteString value)
Serializations can either use one of the fields above, or use this raw bytes field. The only exception is the string case, where one is required to store the content in the repeated bytes string_data field. When this raw_data field is used to store tensor value, elements MUST be stored in as fixed-width, little-endian order. Floating-point data types MUST be stored in IEEE 754 format. Complex64 elements must be written as two consecutive FLOAT values, real component first. Complex128 elements must be written as two consecutive DOUBLE values, real component first. Boolean type MUST be written one byte per tensor element (00000001 for true, 00000000 for false). Note: the advantage of specific field rather than the raw_data field is that in some cases (e.g. int data), protobuf does a better packing via variable length storage, and may lead to smaller binary footprint. When this field is present, the data_type field MUST NOT be STRING or UNDEFINED
bytes raw_data = 9;- Parameters:
value- The rawData to set.- Returns:
- This builder for chaining.
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clearRawData
public OnnxMl.TensorProto.Builder clearRawData()
Serializations can either use one of the fields above, or use this raw bytes field. The only exception is the string case, where one is required to store the content in the repeated bytes string_data field. When this raw_data field is used to store tensor value, elements MUST be stored in as fixed-width, little-endian order. Floating-point data types MUST be stored in IEEE 754 format. Complex64 elements must be written as two consecutive FLOAT values, real component first. Complex128 elements must be written as two consecutive DOUBLE values, real component first. Boolean type MUST be written one byte per tensor element (00000001 for true, 00000000 for false). Note: the advantage of specific field rather than the raw_data field is that in some cases (e.g. int data), protobuf does a better packing via variable length storage, and may lead to smaller binary footprint. When this field is present, the data_type field MUST NOT be STRING or UNDEFINED
bytes raw_data = 9;- Returns:
- This builder for chaining.
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getExternalDataList
public List<OnnxMl.StringStringEntryProto> getExternalDataList()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;- Specified by:
getExternalDataListin interfaceOnnxMl.TensorProtoOrBuilder
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getExternalDataCount
public int getExternalDataCount()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;- Specified by:
getExternalDataCountin interfaceOnnxMl.TensorProtoOrBuilder
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getExternalData
public OnnxMl.StringStringEntryProto getExternalData(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;- Specified by:
getExternalDatain interfaceOnnxMl.TensorProtoOrBuilder
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setExternalData
public OnnxMl.TensorProto.Builder setExternalData(int index, OnnxMl.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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setExternalData
public 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. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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addExternalData
public OnnxMl.TensorProto.Builder addExternalData(OnnxMl.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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addExternalData
public OnnxMl.TensorProto.Builder addExternalData(int index, OnnxMl.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
-
addExternalData
public OnnxMl.TensorProto.Builder addExternalData(OnnxMl.StringStringEntryProto.Builder builderForValue)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
-
addExternalData
public 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. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
-
addAllExternalData
public OnnxMl.TensorProto.Builder addAllExternalData(Iterable<? extends OnnxMl.StringStringEntryProto> values)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
-
clearExternalData
public OnnxMl.TensorProto.Builder clearExternalData()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
-
removeExternalData
public OnnxMl.TensorProto.Builder removeExternalData(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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getExternalDataBuilder
public OnnxMl.StringStringEntryProto.Builder getExternalDataBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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getExternalDataOrBuilder
public OnnxMl.StringStringEntryProtoOrBuilder getExternalDataOrBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;- Specified by:
getExternalDataOrBuilderin interfaceOnnxMl.TensorProtoOrBuilder
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getExternalDataOrBuilderList
public List<? extends OnnxMl.StringStringEntryProtoOrBuilder> getExternalDataOrBuilderList()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;- Specified by:
getExternalDataOrBuilderListin interfaceOnnxMl.TensorProtoOrBuilder
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addExternalDataBuilder
public OnnxMl.StringStringEntryProto.Builder addExternalDataBuilder()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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addExternalDataBuilder
public OnnxMl.StringStringEntryProto.Builder addExternalDataBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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getExternalDataBuilderList
public List<OnnxMl.StringStringEntryProto.Builder> getExternalDataBuilderList()
Data can be stored inside the protobuf file using type-specific fields or raw_data. Alternatively, raw bytes data can be stored in an external file, using the external_data field. external_data stores key-value pairs describing data location. Recognized keys are: - "location" (required) - POSIX filesystem path relative to the directory where the ONNX protobuf model was stored - "offset" (optional) - position of byte at which stored data begins. Integer stored as string. Offset values SHOULD be multiples 4096 (page size) to enable mmap support. - "length" (optional) - number of bytes containing data. Integer stored as string. - "checksum" (optional) - SHA1 digest of file specified in under 'location' key.repeated .onnx.StringStringEntryProto external_data = 13;
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getDataLocationValue
public int getDataLocationValue()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.onnx.TensorProto.DataLocation data_location = 14;- Specified by:
getDataLocationValuein interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The enum numeric value on the wire for dataLocation.
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setDataLocationValue
public OnnxMl.TensorProto.Builder setDataLocationValue(int value)
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.onnx.TensorProto.DataLocation data_location = 14;- Parameters:
value- The enum numeric value on the wire for dataLocation to set.- Returns:
- This builder for chaining.
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getDataLocation
public OnnxMl.TensorProto.DataLocation getDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.onnx.TensorProto.DataLocation data_location = 14;- Specified by:
getDataLocationin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The dataLocation.
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setDataLocation
public 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.
.onnx.TensorProto.DataLocation data_location = 14;- Parameters:
value- The dataLocation to set.- Returns:
- This builder for chaining.
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clearDataLocation
public OnnxMl.TensorProto.Builder clearDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.onnx.TensorProto.DataLocation data_location = 14;- Returns:
- This builder for chaining.
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getDoubleDataList
public List<Double> getDoubleDataList()
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Specified by:
getDoubleDataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the doubleData.
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getDoubleDataCount
public int getDoubleDataCount()
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Specified by:
getDoubleDataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of doubleData.
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getDoubleData
public double getDoubleData(int index)
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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Specified by:
getDoubleDatain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The doubleData at the given index.
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setDoubleData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Parameters:
index- The index to set the value at.value- The doubleData to set.- Returns:
- This builder for chaining.
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addDoubleData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Parameters:
value- The doubleData to add.- Returns:
- This builder for chaining.
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addAllDoubleData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Parameters:
values- The doubleData to add.- Returns:
- This builder for chaining.
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clearDoubleData
public 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. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] is encoded as [1.0, 2.0 ,3.0 ,4.0] When this field is present, the data_type field MUST be DOUBLE or COMPLEX128
repeated double double_data = 10 [packed = true];- Returns:
- This builder for chaining.
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getUint64DataList
public List<Long> getUint64DataList()
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
repeated uint64 uint64_data = 11 [packed = true];- Specified by:
getUint64DataListin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- A list containing the uint64Data.
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getUint64DataCount
public int getUint64DataCount()
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
repeated uint64 uint64_data = 11 [packed = true];- Specified by:
getUint64DataCountin interfaceOnnxMl.TensorProtoOrBuilder- Returns:
- The count of uint64Data.
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getUint64Data
public long getUint64Data(int index)
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
repeated uint64 uint64_data = 11 [packed = true];- Specified by:
getUint64Datain interfaceOnnxMl.TensorProtoOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The uint64Data at the given index.
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setUint64Data
public 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 UINT64
repeated uint64 uint64_data = 11 [packed = true];- Parameters:
index- The index to set the value at.value- The uint64Data to set.- Returns:
- This builder for chaining.
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addUint64Data
public OnnxMl.TensorProto.Builder addUint64Data(long value)
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
repeated uint64 uint64_data = 11 [packed = true];- Parameters:
value- The uint64Data to add.- Returns:
- This builder for chaining.
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addAllUint64Data
public 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 UINT64
repeated uint64 uint64_data = 11 [packed = true];- Parameters:
values- The uint64Data to add.- Returns:
- This builder for chaining.
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clearUint64Data
public OnnxMl.TensorProto.Builder clearUint64Data()
For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
repeated uint64 uint64_data = 11 [packed = true];- Returns:
- This builder for chaining.
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setUnknownFields
public final OnnxMl.TensorProto.Builder setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
- Specified by:
setUnknownFieldsin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setUnknownFieldsin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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mergeUnknownFields
public final OnnxMl.TensorProto.Builder mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
- Specified by:
mergeUnknownFieldsin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
mergeUnknownFieldsin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
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