Onnx.TensorProto.Builder (nd4j-api 1.0.0-beta6 API)

java.lang.Object
- org.nd4j.shade.protobuf.AbstractMessageLite.Builder
- - org.nd4j.shade.protobuf.AbstractMessage.Builder<BuilderType>
  - - org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>
    - - onnx.Onnx.TensorProto.Builder

All Implemented Interfaces:

Cloneable, Onnx.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:

Onnx.TensorProto
```
public static final class Onnx.TensorProto.Builder
extends org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>
implements Onnx.TensorProtoOrBuilder
```
```
 A message defined to store a tensor in its serialized format.
 
```
Protobuf type onnx.TensorProto

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Onnx.TensorProto.Builder`	`addAllDims(Iterable<? extends Long> values)` The shape of the tensor.
`Onnx.TensorProto.Builder`	`addAllDoubleData(Iterable<? extends Double> values)` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`Onnx.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 apparing in the subsequent even numbered position.
`Onnx.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.
`Onnx.TensorProto.Builder`	`addAllInt64Data(Iterable<? extends Long> values)` For int64.
`Onnx.TensorProto.Builder`	`addAllStringData(Iterable<? extends org.nd4j.shade.protobuf.ByteString> values)` For strings.
`Onnx.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
`Onnx.TensorProto.Builder`	`addDims(long value)` The shape of the tensor.
`Onnx.TensorProto.Builder`	`addDoubleData(double value)` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`Onnx.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 apparing in the subsequent even numbered position.
`Onnx.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.
`Onnx.TensorProto.Builder`	`addInt64Data(long value)` For int64.
`Onnx.TensorProto.Builder`	`addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)`
`Onnx.TensorProto.Builder`	`addStringData(org.nd4j.shade.protobuf.ByteString value)` For strings.
`Onnx.TensorProto.Builder`	`addUint64Data(long value)` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`Onnx.TensorProto`	`build()`
`Onnx.TensorProto`	`buildPartial()`
`Onnx.TensorProto.Builder`	`clear()`
`Onnx.TensorProto.Builder`	`clearDataType()` The data type of the tensor.
`Onnx.TensorProto.Builder`	`clearDims()` The shape of the tensor.
`Onnx.TensorProto.Builder`	`clearDocString()` A human-readable documentation for this tensor.
`Onnx.TensorProto.Builder`	`clearDoubleData()` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`Onnx.TensorProto.Builder`	`clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)`
`Onnx.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 apparing in the subsequent even numbered position.
`Onnx.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.
`Onnx.TensorProto.Builder`	`clearInt64Data()` For int64.
`Onnx.TensorProto.Builder`	`clearName()` Optionally, a name for the tensor.
`Onnx.TensorProto.Builder`	`clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)`
`Onnx.TensorProto.Builder`	`clearRawData()` Serializations can either use one of the fields above, or use this raw bytes field.
`Onnx.TensorProto.Builder`	`clearSegment()` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.Builder`	`clearStringData()` For strings.
`Onnx.TensorProto.Builder`	`clearUint64Data()` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`Onnx.TensorProto.Builder`	`clone()`
`Onnx.TensorProto.DataType`	`getDataType()` The data type of the tensor.
`int`	`getDataTypeValue()` The data type of the tensor.
`Onnx.TensorProto`	`getDefaultInstanceForType()`
`static org.nd4j.shade.protobuf.Descriptors.Descriptor`	`getDescriptor()`
`org.nd4j.shade.protobuf.Descriptors.Descriptor`	`getDescriptorForType()`
`long`	`getDims(int index)` The shape of the tensor.
`int`	`getDimsCount()` The shape of the tensor.
`List<Long>`	`getDimsList()` The shape of the tensor.
`String`	`getDocString()` A human-readable documentation for this tensor.
`org.nd4j.shade.protobuf.ByteString`	`getDocStringBytes()` A human-readable documentation for this tensor.
`double`	`getDoubleData(int index)` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`int`	`getDoubleDataCount()` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`List<Double>`	`getDoubleDataList()` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`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 apparing in the subsequent even numbered position.
`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 apparing 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 apparing in the subsequent even numbered position.
`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.
`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.
`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.
`long`	`getInt64Data(int index)` For int64.
`int`	`getInt64DataCount()` For int64.
`List<Long>`	`getInt64DataList()` For int64.
`String`	`getName()` Optionally, a name for the tensor.
`org.nd4j.shade.protobuf.ByteString`	`getNameBytes()` Optionally, a name for the tensor.
`org.nd4j.shade.protobuf.ByteString`	`getRawData()` Serializations can either use one of the fields above, or use this raw bytes field.
`Onnx.TensorProto.Segment`	`getSegment()` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.Segment.Builder`	`getSegmentBuilder()` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.SegmentOrBuilder`	`getSegmentOrBuilder()` `.onnx.TensorProto.Segment segment = 3;`
`org.nd4j.shade.protobuf.ByteString`	`getStringData(int index)` For strings.
`int`	`getStringDataCount()` For strings.
`List<org.nd4j.shade.protobuf.ByteString>`	`getStringDataList()` For strings.
`long`	`getUint64Data(int index)` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`int`	`getUint64DataCount()` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`List<Long>`	`getUint64DataList()` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`boolean`	`hasSegment()` `.onnx.TensorProto.Segment segment = 3;`
`protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable`	`internalGetFieldAccessorTable()`
`boolean`	`isInitialized()`
`Onnx.TensorProto.Builder`	`mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)`
`Onnx.TensorProto.Builder`	`mergeFrom(org.nd4j.shade.protobuf.Message other)`
`Onnx.TensorProto.Builder`	`mergeFrom(Onnx.TensorProto other)`
`Onnx.TensorProto.Builder`	`mergeSegment(Onnx.TensorProto.Segment value)` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.Builder`	`mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)`
`Onnx.TensorProto.Builder`	`setDataType(Onnx.TensorProto.DataType value)` The data type of the tensor.
`Onnx.TensorProto.Builder`	`setDataTypeValue(int value)` The data type of the tensor.
`Onnx.TensorProto.Builder`	`setDims(int index, long value)` The shape of the tensor.
`Onnx.TensorProto.Builder`	`setDocString(String value)` A human-readable documentation for this tensor.
`Onnx.TensorProto.Builder`	`setDocStringBytes(org.nd4j.shade.protobuf.ByteString value)` A human-readable documentation for this tensor.
`Onnx.TensorProto.Builder`	`setDoubleData(int index, double value)` For double Complex64 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component apparing in the subsequent even numbered position.
`Onnx.TensorProto.Builder`	`setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)`
`Onnx.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 apparing in the subsequent even numbered position.
`Onnx.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.
`Onnx.TensorProto.Builder`	`setInt64Data(int index, long value)` For int64.
`Onnx.TensorProto.Builder`	`setName(String value)` Optionally, a name for the tensor.
`Onnx.TensorProto.Builder`	`setNameBytes(org.nd4j.shade.protobuf.ByteString value)` Optionally, a name for the tensor.
`Onnx.TensorProto.Builder`	`setRawData(org.nd4j.shade.protobuf.ByteString value)` Serializations can either use one of the fields above, or use this raw bytes field.
`Onnx.TensorProto.Builder`	`setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)`
`Onnx.TensorProto.Builder`	`setSegment(Onnx.TensorProto.Segment.Builder builderForValue)` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.Builder`	`setSegment(Onnx.TensorProto.Segment value)` `.onnx.TensorProto.Segment segment = 3;`
`Onnx.TensorProto.Builder`	`setStringData(int index, org.nd4j.shade.protobuf.ByteString value)` For strings.
`Onnx.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
`Onnx.TensorProto.Builder`	`setUnknownFields(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

Methods inherited from class org.nd4j.shade.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class org.nd4j.shade.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.nd4j.shade.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface org.nd4j.shade.protobuf.MessageLite.Builder
mergeFrom

Method Detail

getDescriptor

public static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable
```
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
```
Specified by:

internalGetFieldAccessorTable in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

clear
```
public Onnx.TensorProto.Builder clear()
```
Specified by:

clear in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

clear in interface org.nd4j.shade.protobuf.MessageLite.Builder

Overrides:

clear in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

getDescriptorForType
```
public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
```
Specified by:

getDescriptorForType in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface org.nd4j.shade.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

getDefaultInstanceForType
```
public Onnx.TensorProto getDefaultInstanceForType()
```
Specified by:

getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageOrBuilder

build
```
public Onnx.TensorProto build()
```
Specified by:

build in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

build in interface org.nd4j.shade.protobuf.MessageLite.Builder

buildPartial
```
public Onnx.TensorProto buildPartial()
```
Specified by:

buildPartial in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

buildPartial in interface org.nd4j.shade.protobuf.MessageLite.Builder

clone
```
public Onnx.TensorProto.Builder clone()
```
Specified by:

clone in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

clone in interface org.nd4j.shade.protobuf.MessageLite.Builder

Overrides:

clone in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

setField

public Onnx.TensorProto.Builder setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                         Object value)

Specified by:: setField in interface org.nd4j.shade.protobuf.Message.Builder
Overrides:: setField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

clearField
```
public Onnx.TensorProto.Builder clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
```
Specified by:

clearField in interface org.nd4j.shade.protobuf.Message.Builder

Overrides:

clearField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

clearOneof
```
public Onnx.TensorProto.Builder clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
```
Specified by:

clearOneof in interface org.nd4j.shade.protobuf.Message.Builder

Overrides:

clearOneof in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

setRepeatedField

public Onnx.TensorProto.Builder setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                                 int index,
                                                 Object value)

Specified by:: setRepeatedField in interface org.nd4j.shade.protobuf.Message.Builder
Overrides:: setRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

addRepeatedField

public Onnx.TensorProto.Builder addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                                 Object value)

Specified by:: addRepeatedField in interface org.nd4j.shade.protobuf.Message.Builder
Overrides:: addRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

mergeFrom
```
public Onnx.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.Message other)
```
Specified by:

mergeFrom in interface org.nd4j.shade.protobuf.Message.Builder

Overrides:

mergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<Onnx.TensorProto.Builder>

mergeFrom

public Onnx.TensorProto.Builder mergeFrom(Onnx.TensorProto other)

isInitialized
```
public final boolean isInitialized()
```
Specified by:

isInitialized in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<Onnx.TensorProto.Builder>

mergeFrom
```
public Onnx.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input,
                                          org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
                                   throws IOException
```
Specified by:

mergeFrom in interface org.nd4j.shade.protobuf.Message.Builder

Specified by:

mergeFrom in interface org.nd4j.shade.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<Onnx.TensorProto.Builder>

Throws:

IOException

getDimsList
```
public List<Long> getDimsList()
```
```
 The shape of the tensor.
 
```
repeated int64 dims = 1;
Specified by:

getDimsList in interface Onnx.TensorProtoOrBuilder

getDimsCount
```
public int getDimsCount()
```
```
 The shape of the tensor.
 
```
repeated int64 dims = 1;
Specified by:

getDimsCount in interface Onnx.TensorProtoOrBuilder

getDims
```
public long getDims(int index)
```
```
 The shape of the tensor.
 
```
repeated int64 dims = 1;
Specified by:

getDims in interface Onnx.TensorProtoOrBuilder

setDims

public Onnx.TensorProto.Builder setDims(int index,
                                        long value)

 The shape of the tensor.

repeated int64 dims = 1;

addDims

public Onnx.TensorProto.Builder addDims(long value)

 The shape of the tensor.

repeated int64 dims = 1;

addAllDims

public Onnx.TensorProto.Builder addAllDims(Iterable<? extends Long> values)

 The shape of the tensor.

repeated int64 dims = 1;

clearDims

public Onnx.TensorProto.Builder clearDims()

 The shape of the tensor.

repeated int64 dims = 1;

getDataTypeValue
```
public int getDataTypeValue()
```
```
 The data type of the tensor.
 
```
.onnx.TensorProto.DataType data_type = 2;
Specified by:

getDataTypeValue in interface Onnx.TensorProtoOrBuilder

setDataTypeValue

public Onnx.TensorProto.Builder setDataTypeValue(int value)

 The data type of the tensor.

.onnx.TensorProto.DataType data_type = 2;

getDataType
```
public Onnx.TensorProto.DataType getDataType()
```
```
 The data type of the tensor.
 
```
.onnx.TensorProto.DataType data_type = 2;
Specified by:

getDataType in interface Onnx.TensorProtoOrBuilder

setDataType

public Onnx.TensorProto.Builder setDataType(Onnx.TensorProto.DataType value)

 The data type of the tensor.

.onnx.TensorProto.DataType data_type = 2;

clearDataType

public Onnx.TensorProto.Builder clearDataType()

 The data type of the tensor.

.onnx.TensorProto.DataType data_type = 2;

hasSegment
```
public boolean hasSegment()
```
.onnx.TensorProto.Segment segment = 3;

Specified by:

hasSegment in interface Onnx.TensorProtoOrBuilder

getSegment
```
public Onnx.TensorProto.Segment getSegment()
```
.onnx.TensorProto.Segment segment = 3;

Specified by:

getSegment in interface Onnx.TensorProtoOrBuilder

setSegment

public Onnx.TensorProto.Builder setSegment(Onnx.TensorProto.Segment value)

.onnx.TensorProto.Segment segment = 3;

setSegment

public Onnx.TensorProto.Builder setSegment(Onnx.TensorProto.Segment.Builder builderForValue)

.onnx.TensorProto.Segment segment = 3;

mergeSegment

public Onnx.TensorProto.Builder mergeSegment(Onnx.TensorProto.Segment value)

.onnx.TensorProto.Segment segment = 3;

clearSegment

public Onnx.TensorProto.Builder clearSegment()

.onnx.TensorProto.Segment segment = 3;

getSegmentBuilder

public Onnx.TensorProto.Segment.Builder getSegmentBuilder()

.onnx.TensorProto.Segment segment = 3;

getSegmentOrBuilder
```
public Onnx.TensorProto.SegmentOrBuilder getSegmentOrBuilder()
```
.onnx.TensorProto.Segment segment = 3;

Specified by:

getSegmentOrBuilder in interface Onnx.TensorProtoOrBuilder

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 apparing 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:: getFloatDataList in interface Onnx.TensorProtoOrBuilder

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 apparing 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:: getFloatDataCount in interface Onnx.TensorProtoOrBuilder

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 apparing 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:: getFloatData in interface Onnx.TensorProtoOrBuilder

setFloatData

public Onnx.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 apparing 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];

addFloatData

public Onnx.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 apparing 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];

addAllFloatData

public Onnx.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 apparing 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];

clearFloatData

public Onnx.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 apparing 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];

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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

Specified by:: getInt32DataList in interface Onnx.TensorProtoOrBuilder

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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

Specified by:: getInt32DataCount in interface Onnx.TensorProtoOrBuilder

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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

Specified by:: getInt32Data in interface Onnx.TensorProtoOrBuilder

setInt32Data

public Onnx.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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

addInt32Data

public Onnx.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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

addAllInt32Data

public Onnx.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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

clearInt32Data

public Onnx.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, INT8, BOOL, or FLOAT32

repeated int32 int32_data = 5 [packed = true];

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:: getStringDataList in interface Onnx.TensorProtoOrBuilder

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:: getStringDataCount in interface Onnx.TensorProtoOrBuilder

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:: getStringData in interface Onnx.TensorProtoOrBuilder

setStringData

public Onnx.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;

addStringData

public Onnx.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;

addAllStringData

public Onnx.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;

clearStringData

public Onnx.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;

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:

getInt64DataList in interface Onnx.TensorProtoOrBuilder

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:

getInt64DataCount in interface Onnx.TensorProtoOrBuilder

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:

getInt64Data in interface Onnx.TensorProtoOrBuilder

setInt64Data

public Onnx.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];

addInt64Data

public Onnx.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];

addAllInt64Data

public Onnx.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];

clearInt64Data

public Onnx.TensorProto.Builder clearInt64Data()

 For int64.
 When this field is present, the data_type field MUST be INT64

repeated int64 int64_data = 7 [packed = true];

getName
```
public String getName()
```
```
 Optionally, a name for the tensor.
 
```
string name = 8;
Specified by:

getName in interface Onnx.TensorProtoOrBuilder

getNameBytes

public org.nd4j.shade.protobuf.ByteString getNameBytes()

 Optionally, a name for the tensor.

string name = 8;

Specified by:: getNameBytes in interface Onnx.TensorProtoOrBuilder

setName

public Onnx.TensorProto.Builder setName(String value)

 Optionally, a name for the tensor.

string name = 8;

clearName

public Onnx.TensorProto.Builder clearName()

 Optionally, a name for the tensor.

string name = 8;

setNameBytes

public Onnx.TensorProto.Builder setNameBytes(org.nd4j.shade.protobuf.ByteString value)

 Optionally, a name for the tensor.

string name = 8;

getDocString

public String getDocString()

 A human-readable documentation for this tensor. Markdown is allowed.

string doc_string = 12;

Specified by:: getDocString in interface Onnx.TensorProtoOrBuilder

getDocStringBytes

public org.nd4j.shade.protobuf.ByteString getDocStringBytes()

 A human-readable documentation for this tensor. Markdown is allowed.

string doc_string = 12;

Specified by:: getDocStringBytes in interface Onnx.TensorProtoOrBuilder

setDocString

public Onnx.TensorProto.Builder setDocString(String value)

 A human-readable documentation for this tensor. Markdown is allowed.

string doc_string = 12;

clearDocString

public Onnx.TensorProto.Builder clearDocString()

 A human-readable documentation for this tensor. Markdown is allowed.

string doc_string = 12;

setDocStringBytes

public Onnx.TensorProto.Builder setDocStringBytes(org.nd4j.shade.protobuf.ByteString value)

 A human-readable documentation for this tensor. Markdown is allowed.

string doc_string = 12;

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:: getRawData in interface Onnx.TensorProtoOrBuilder

setRawData

public Onnx.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;

clearRawData

public Onnx.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;

getDoubleDataList

public List<Double> getDoubleDataList()

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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:: getDoubleDataList in interface Onnx.TensorProtoOrBuilder

getDoubleDataCount

public int getDoubleDataCount()

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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:: getDoubleDataCount in interface Onnx.TensorProtoOrBuilder

getDoubleData

public double getDoubleData(int index)

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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:: getDoubleData in interface Onnx.TensorProtoOrBuilder

setDoubleData

public Onnx.TensorProto.Builder setDoubleData(int index,
                                              double value)

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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];

addDoubleData

public Onnx.TensorProto.Builder addDoubleData(double value)

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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];

addAllDoubleData

public Onnx.TensorProto.Builder addAllDoubleData(Iterable<? extends Double> values)

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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];

clearDoubleData

public Onnx.TensorProto.Builder clearDoubleData()

 For double
 Complex64 tensors are encoded as a single array of doubles,
 with the real components appearing in odd numbered positions,
 and the corresponding imaginary component apparing 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];