OnnxMl.TensorProto.Builder

java.lang.Object
- com.google.protobuf.AbstractMessageLite.Builder
- - com.google.protobuf.AbstractMessage.Builder<BuilderType>
  - - com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
    - - ai.onnx.proto.OnnxMl.TensorProto.Builder

All Implemented Interfaces:

OnnxMl.TensorProtoOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, java.lang.Cloneable

Enclosing class:

OnnxMl.TensorProto
```
public static final class OnnxMl.TensorProto.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>
implements OnnxMl.TensorProtoOrBuilder
```
```
 Tensors
 A serialized tensor value.
 
```
Protobuf type onnx.TensorProto

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`OnnxMl.TensorProto.Builder`	`addAllDims(java.lang.Iterable<? extends java.lang.Long> values)` The shape of the tensor.
`OnnxMl.TensorProto.Builder`	`addAllDoubleData(java.lang.Iterable<? extends java.lang.Double> values)` For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`addAllExternalData(java.lang.Iterable<? extends OnnxMl.StringStringEntryProto> values)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`addAllFloatData(java.lang.Iterable<? extends java.lang.Float> values)` For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`addAllInt32Data(java.lang.Iterable<? extends java.lang.Integer> values)` For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
`OnnxMl.TensorProto.Builder`	`addAllInt64Data(java.lang.Iterable<? extends java.lang.Long> values)` For int64.
`OnnxMl.TensorProto.Builder`	`addAllStringData(java.lang.Iterable<? extends com.google.protobuf.ByteString> values)` For strings.
`OnnxMl.TensorProto.Builder`	`addAllUint64Data(java.lang.Iterable<? extends java.lang.Long> values)` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`OnnxMl.TensorProto.Builder`	`addDims(long value)` The shape of the tensor.
`OnnxMl.TensorProto.Builder`	`addDoubleData(double value)` For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`addExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`addExternalData(int index, OnnxMl.StringStringEntryProto value)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`addExternalData(OnnxMl.StringStringEntryProto.Builder builderForValue)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`addExternalData(OnnxMl.StringStringEntryProto value)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.StringStringEntryProto.Builder`	`addExternalDataBuilder()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.StringStringEntryProto.Builder`	`addExternalDataBuilder(int index)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`addFloatData(float value)` For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`addInt32Data(int value)` For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
`OnnxMl.TensorProto.Builder`	`addInt64Data(long value)` For int64.
`OnnxMl.TensorProto.Builder`	`addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)`
`OnnxMl.TensorProto.Builder`	`addStringData(com.google.protobuf.ByteString value)` For strings.
`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
`OnnxMl.TensorProto`	`build()`
`OnnxMl.TensorProto`	`buildPartial()`
`OnnxMl.TensorProto.Builder`	`clear()`
`OnnxMl.TensorProto.Builder`	`clearDataLocation()` If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
`OnnxMl.TensorProto.Builder`	`clearDataType()` The data type of the tensor.
`OnnxMl.TensorProto.Builder`	`clearDims()` The shape of the tensor.
`OnnxMl.TensorProto.Builder`	`clearDocString()` A human-readable documentation for this tensor.
`OnnxMl.TensorProto.Builder`	`clearDoubleData()` For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`clearExternalData()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`clearField(com.google.protobuf.Descriptors.FieldDescriptor field)`
`OnnxMl.TensorProto.Builder`	`clearFloatData()` For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`clearInt32Data()` For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
`OnnxMl.TensorProto.Builder`	`clearInt64Data()` For int64.
`OnnxMl.TensorProto.Builder`	`clearName()` Optionally, a name for the tensor.
`OnnxMl.TensorProto.Builder`	`clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)`
`OnnxMl.TensorProto.Builder`	`clearRawData()` Serializations can either use one of the fields above, or use this raw bytes field.
`OnnxMl.TensorProto.Builder`	`clearSegment()` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.Builder`	`clearStringData()` For strings.
`OnnxMl.TensorProto.Builder`	`clearUint64Data()` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`OnnxMl.TensorProto.Builder`	`clone()`
`OnnxMl.TensorProto.DataLocation`	`getDataLocation()` If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
`int`	`getDataType()` The data type of the tensor.
`OnnxMl.TensorProto`	`getDefaultInstanceForType()`
`static com.google.protobuf.Descriptors.Descriptor`	`getDescriptor()`
`com.google.protobuf.Descriptors.Descriptor`	`getDescriptorForType()`
`long`	`getDims(int index)` The shape of the tensor.
`int`	`getDimsCount()` The shape of the tensor.
`java.util.List<java.lang.Long>`	`getDimsList()` The shape of the tensor.
`java.lang.String`	`getDocString()` A human-readable documentation for this tensor.
`com.google.protobuf.ByteString`	`getDocStringBytes()` A human-readable documentation for this tensor.
`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.
`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.
`java.util.List<java.lang.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.StringStringEntryProto`	`getExternalData(int index)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.StringStringEntryProto.Builder`	`getExternalDataBuilder(int index)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`java.util.List<OnnxMl.StringStringEntryProto.Builder>`	`getExternalDataBuilderList()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`int`	`getExternalDataCount()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`java.util.List<OnnxMl.StringStringEntryProto>`	`getExternalDataList()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.StringStringEntryProtoOrBuilder`	`getExternalDataOrBuilder(int index)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`java.util.List<? extends OnnxMl.StringStringEntryProtoOrBuilder>`	`getExternalDataOrBuilderList()` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`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.
`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.
`java.util.List<java.lang.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.
`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.
`java.util.List<java.lang.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.
`java.util.List<java.lang.Long>`	`getInt64DataList()` For int64.
`java.lang.String`	`getName()` Optionally, a name for the tensor.
`com.google.protobuf.ByteString`	`getNameBytes()` Optionally, a name for the tensor.
`com.google.protobuf.ByteString`	`getRawData()` Serializations can either use one of the fields above, or use this raw bytes field.
`OnnxMl.TensorProto.Segment`	`getSegment()` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.Segment.Builder`	`getSegmentBuilder()` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.SegmentOrBuilder`	`getSegmentOrBuilder()` `optional .onnx.TensorProto.Segment segment = 3;`
`com.google.protobuf.ByteString`	`getStringData(int index)` For strings.
`int`	`getStringDataCount()` For strings.
`java.util.List<com.google.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
`java.util.List<java.lang.Long>`	`getUint64DataList()` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`boolean`	`hasDataLocation()` If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
`boolean`	`hasDataType()` The data type of the tensor.
`boolean`	`hasDocString()` A human-readable documentation for this tensor.
`boolean`	`hasName()` Optionally, a name for the tensor.
`boolean`	`hasRawData()` Serializations can either use one of the fields above, or use this raw bytes field.
`boolean`	`hasSegment()` `optional .onnx.TensorProto.Segment segment = 3;`
`protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable`	`internalGetFieldAccessorTable()`
`boolean`	`isInitialized()`
`OnnxMl.TensorProto.Builder`	`mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`OnnxMl.TensorProto.Builder`	`mergeFrom(com.google.protobuf.Message other)`
`OnnxMl.TensorProto.Builder`	`mergeFrom(OnnxMl.TensorProto other)`
`OnnxMl.TensorProto.Builder`	`mergeSegment(OnnxMl.TensorProto.Segment value)` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.Builder`	`mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)`
`OnnxMl.TensorProto.Builder`	`removeExternalData(int index)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`setDataLocation(OnnxMl.TensorProto.DataLocation value)` If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
`OnnxMl.TensorProto.Builder`	`setDataType(int value)` The data type of the tensor.
`OnnxMl.TensorProto.Builder`	`setDims(int index, long value)` The shape of the tensor.
`OnnxMl.TensorProto.Builder`	`setDocString(java.lang.String value)` A human-readable documentation for this tensor.
`OnnxMl.TensorProto.Builder`	`setDocStringBytes(com.google.protobuf.ByteString value)` A human-readable documentation for this tensor.
`OnnxMl.TensorProto.Builder`	`setDoubleData(int index, double value)` For double Complex128 tensors are encoded as a single array of doubles, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`setExternalData(int index, OnnxMl.StringStringEntryProto.Builder builderForValue)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`setExternalData(int index, OnnxMl.StringStringEntryProto value)` Data can be stored inside the protobuf file using type-specific fields or raw_data.
`OnnxMl.TensorProto.Builder`	`setField(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)`
`OnnxMl.TensorProto.Builder`	`setFloatData(int index, float value)` For float and complex64 values Complex64 tensors are encoded as a single array of floats, with the real components appearing in odd numbered positions, and the corresponding imaginary component appearing in the subsequent even numbered position.
`OnnxMl.TensorProto.Builder`	`setInt32Data(int index, int value)` For int32, uint8, int8, uint16, int16, bool, and float16 values float16 values must be bit-wise converted to an uint16_t prior to writing to the buffer.
`OnnxMl.TensorProto.Builder`	`setInt64Data(int index, long value)` For int64.
`OnnxMl.TensorProto.Builder`	`setName(java.lang.String value)` Optionally, a name for the tensor.
`OnnxMl.TensorProto.Builder`	`setNameBytes(com.google.protobuf.ByteString value)` Optionally, a name for the tensor.
`OnnxMl.TensorProto.Builder`	`setRawData(com.google.protobuf.ByteString value)` Serializations can either use one of the fields above, or use this raw bytes field.
`OnnxMl.TensorProto.Builder`	`setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value)`
`OnnxMl.TensorProto.Builder`	`setSegment(OnnxMl.TensorProto.Segment.Builder builderForValue)` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.Builder`	`setSegment(OnnxMl.TensorProto.Segment value)` `optional .onnx.TensorProto.Segment segment = 3;`
`OnnxMl.TensorProto.Builder`	`setStringData(int index, com.google.protobuf.ByteString value)` For strings.
`OnnxMl.TensorProto.Builder`	`setUint64Data(int index, long value)` For uint64 and uint32 values When this field is present, the data_type field MUST be UINT32 or UINT64
`OnnxMl.TensorProto.Builder`	`setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)`

Methods inherited from class com.google.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 com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.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 com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFrom

Method Detail

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable
```
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
```
Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

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

clear in interface com.google.protobuf.Message.Builder

Specified by:

clear in interface com.google.protobuf.MessageLite.Builder

Overrides:

clear in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

getDescriptorForType
```
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
```
Specified by:

getDescriptorForType in interface com.google.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface com.google.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

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

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

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

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

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

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

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

clone in interface com.google.protobuf.Message.Builder

Specified by:

clone in interface com.google.protobuf.MessageLite.Builder

Overrides:

clone in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

setField
```
public OnnxMl.TensorProto.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                           java.lang.Object value)
```
Specified by:

setField in interface com.google.protobuf.Message.Builder

Overrides:

setField in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

clearField
```
public OnnxMl.TensorProto.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
```
Specified by:

clearField in interface com.google.protobuf.Message.Builder

Overrides:

clearField in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

clearOneof
```
public OnnxMl.TensorProto.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
```
Specified by:

clearOneof in interface com.google.protobuf.Message.Builder

Overrides:

clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

setRepeatedField

public OnnxMl.TensorProto.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   int index,
                                                   java.lang.Object value)

Specified by:: setRepeatedField in interface com.google.protobuf.Message.Builder
Overrides:: setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

addRepeatedField
```
public OnnxMl.TensorProto.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   java.lang.Object value)
```
Specified by:

addRepeatedField in interface com.google.protobuf.Message.Builder

Overrides:

addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

mergeFrom
```
public OnnxMl.TensorProto.Builder mergeFrom(com.google.protobuf.Message other)
```
Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<OnnxMl.TensorProto.Builder>

mergeFrom

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

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

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<OnnxMl.TensorProto.Builder>

mergeFrom
```
public OnnxMl.TensorProto.Builder mergeFrom(com.google.protobuf.CodedInputStream input,
                                            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                     throws java.io.IOException
```
Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Specified by:

mergeFrom in interface com.google.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<OnnxMl.TensorProto.Builder>

Throws:

java.io.IOException

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

getDimsList in interface OnnxMl.TensorProtoOrBuilder

Returns:

A list containing the dims.

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

getDimsCount in interface OnnxMl.TensorProtoOrBuilder

Returns:

The count of dims.

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

getDims in interface OnnxMl.TensorProtoOrBuilder

Parameters:

index - The index of the element to return.

Returns:

The dims at the given index.

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.

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.

addAllDims

public OnnxMl.TensorProto.Builder addAllDims(java.lang.Iterable<? extends java.lang.Long> values)

 The shape of the tensor.

repeated int64 dims = 1;

Parameters:: values - The dims to add.
Returns:: This builder for chaining.

clearDims

public OnnxMl.TensorProto.Builder clearDims()

 The shape of the tensor.

repeated int64 dims = 1;

Returns:: This builder for chaining.

hasDataType
```
public boolean hasDataType()
```
```
 The data type of the tensor.
 This field MUST have a valid TensorProto.DataType value
 
```
optional int32 data_type = 2;
Specified by:

hasDataType in interface OnnxMl.TensorProtoOrBuilder

Returns:

Whether the dataType field is set.

getDataType
```
public int getDataType()
```
```
 The data type of the tensor.
 This field MUST have a valid TensorProto.DataType value
 
```
optional int32 data_type = 2;
Specified by:

getDataType in interface OnnxMl.TensorProtoOrBuilder

Returns:

The dataType.

setDataType

public OnnxMl.TensorProto.Builder setDataType(int value)

 The data type of the tensor.
 This field MUST have a valid TensorProto.DataType value

optional int32 data_type = 2;

Parameters:: value - The dataType to set.
Returns:: This builder for chaining.

clearDataType

public OnnxMl.TensorProto.Builder clearDataType()

 The data type of the tensor.
 This field MUST have a valid TensorProto.DataType value

optional int32 data_type = 2;

Returns:: This builder for chaining.

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

Specified by:

hasSegment in interface OnnxMl.TensorProtoOrBuilder

Returns:

Whether the segment field is set.

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

Specified by:

getSegment in interface OnnxMl.TensorProtoOrBuilder

Returns:

The segment.

setSegment

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

optional .onnx.TensorProto.Segment segment = 3;

setSegment

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

optional .onnx.TensorProto.Segment segment = 3;

mergeSegment

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

optional .onnx.TensorProto.Segment segment = 3;

clearSegment
```
public OnnxMl.TensorProto.Builder clearSegment()
```
optional .onnx.TensorProto.Segment segment = 3;

getSegmentBuilder

public OnnxMl.TensorProto.Segment.Builder getSegmentBuilder()

optional .onnx.TensorProto.Segment segment = 3;

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

Specified by:

getSegmentOrBuilder in interface OnnxMl.TensorProtoOrBuilder

getFloatDataList

public java.util.List<java.lang.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:: getFloatDataList in interface OnnxMl.TensorProtoOrBuilder
Returns:: A list containing the floatData.

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:: getFloatDataCount in interface OnnxMl.TensorProtoOrBuilder
Returns:: The count of floatData.

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:: getFloatData in interface OnnxMl.TensorProtoOrBuilder
Parameters:: index - The index of the element to return.
Returns:: The floatData at the given index.

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.

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.

addAllFloatData

public OnnxMl.TensorProto.Builder addAllFloatData(java.lang.Iterable<? extends java.lang.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.

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.

getInt32DataList

public java.util.List<java.lang.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:: getInt32DataList in interface OnnxMl.TensorProtoOrBuilder
Returns:: A list containing the int32Data.

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:: getInt32DataCount in interface OnnxMl.TensorProtoOrBuilder
Returns:: The count of int32Data.

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:: getInt32Data in interface OnnxMl.TensorProtoOrBuilder
Parameters:: index - The index of the element to return.
Returns:: The int32Data at the given index.

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.

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.

addAllInt32Data

public OnnxMl.TensorProto.Builder addAllInt32Data(java.lang.Iterable<? extends java.lang.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.

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.

getStringDataList

public java.util.List<com.google.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 OnnxMl.TensorProtoOrBuilder
Returns:: A list containing the stringData.

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 OnnxMl.TensorProtoOrBuilder
Returns:: The count of stringData.

getStringData

public com.google.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 OnnxMl.TensorProtoOrBuilder
Parameters:: index - The index of the element to return.
Returns:: The stringData at the given index.

setStringData

public OnnxMl.TensorProto.Builder setStringData(int index,
                                                com.google.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.

addStringData

public OnnxMl.TensorProto.Builder addStringData(com.google.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.

addAllStringData

public OnnxMl.TensorProto.Builder addAllStringData(java.lang.Iterable<? extends com.google.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.

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.

getInt64DataList
```
public java.util.List<java.lang.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 OnnxMl.TensorProtoOrBuilder

Returns:

A list containing the int64Data.

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 OnnxMl.TensorProtoOrBuilder

Returns:

The count of int64Data.

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 OnnxMl.TensorProtoOrBuilder

Parameters:

index - The index of the element to return.

Returns:

The int64Data at the given index.

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.

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.

addAllInt64Data

public OnnxMl.TensorProto.Builder addAllInt64Data(java.lang.Iterable<? extends java.lang.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.

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.

hasName
```
public boolean hasName()
```
```
 Optionally, a name for the tensor.
 
```
optional string name = 8;
Specified by:

hasName in interface OnnxMl.TensorProtoOrBuilder

Returns:

Whether the name field is set.

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

getName in interface OnnxMl.TensorProtoOrBuilder

Returns:

The name.

getNameBytes
```
public com.google.protobuf.ByteString getNameBytes()
```
```
 Optionally, a name for the tensor.
 
```
optional string name = 8;
Specified by:

getNameBytes in interface OnnxMl.TensorProtoOrBuilder

Returns:

The bytes for name.

setName

public OnnxMl.TensorProto.Builder setName(java.lang.String value)

 Optionally, a name for the tensor.

optional string name = 8;

Parameters:: value - The name to set.
Returns:: This builder for chaining.

clearName

public OnnxMl.TensorProto.Builder clearName()

 Optionally, a name for the tensor.

optional string name = 8;

Returns:: This builder for chaining.

setNameBytes

public OnnxMl.TensorProto.Builder setNameBytes(com.google.protobuf.ByteString value)

 Optionally, a name for the tensor.

optional string name = 8;

Parameters:: value - The bytes for name to set.
Returns:: This builder for chaining.

hasDocString
```
public boolean hasDocString()
```
```
 A human-readable documentation for this tensor. Markdown is allowed.
 
```
optional string doc_string = 12;
Specified by:

hasDocString in interface OnnxMl.TensorProtoOrBuilder

Returns:

Whether the docString field is set.

getDocString
```
public java.lang.String getDocString()
```
```
 A human-readable documentation for this tensor. Markdown is allowed.
 
```
optional string doc_string = 12;
Specified by:

getDocString in interface OnnxMl.TensorProtoOrBuilder

Returns:

The docString.

getDocStringBytes
```
public com.google.protobuf.ByteString getDocStringBytes()
```
```
 A human-readable documentation for this tensor. Markdown is allowed.
 
```
optional string doc_string = 12;
Specified by:

getDocStringBytes in interface OnnxMl.TensorProtoOrBuilder

Returns:

The bytes for docString.

setDocString

public OnnxMl.TensorProto.Builder setDocString(java.lang.String value)

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

optional string doc_string = 12;

Parameters:: value - The docString to set.
Returns:: This builder for chaining.

clearDocString

public OnnxMl.TensorProto.Builder clearDocString()

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

optional string doc_string = 12;

Returns:: This builder for chaining.

setDocStringBytes

public OnnxMl.TensorProto.Builder setDocStringBytes(com.google.protobuf.ByteString value)

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

optional string doc_string = 12;

Parameters:: value - The bytes for docString to set.
Returns:: This builder for chaining.

hasRawData

public boolean hasRawData()

 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

optional bytes raw_data = 9;

Specified by:: hasRawData in interface OnnxMl.TensorProtoOrBuilder
Returns:: Whether the rawData field is set.

getRawData

public com.google.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

optional bytes raw_data = 9;

Specified by:: getRawData in interface OnnxMl.TensorProtoOrBuilder
Returns:: The rawData.

setRawData

public OnnxMl.TensorProto.Builder setRawData(com.google.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

optional bytes raw_data = 9;

Parameters:: value - The rawData to set.
Returns:: This builder for chaining.

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

optional bytes raw_data = 9;

Returns:: This builder for chaining.