public static final class TensorNamespace.TensorProto.Builder extends org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder> implements TensorNamespace.TensorProtoOrBuilder
Tensors A serialized tensor value.Protobuf type
org.nd4j.ir.TensorProto| Modifier and Type | Method and Description |
|---|---|
TensorNamespace.TensorProto.Builder |
addAllBoolVal(Iterable<? extends Boolean> values)
boolean values
|
TensorNamespace.TensorProto.Builder |
addAllDims(Iterable<? extends Long> values)
The shape of the tensor.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addAllExternalData(Iterable<? extends TensorNamespace.StringStringEntryProto> values)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addAllHalfVal(Iterable<? extends Integer> values)
For half values (tensorflow compatibility)
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addAllInt64Data(Iterable<? extends Long> values)
For int64.
|
TensorNamespace.TensorProto.Builder |
addAllStringData(Iterable<? extends org.nd4j.shade.protobuf.ByteString> values)
For strings.
|
TensorNamespace.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
|
TensorNamespace.TensorProto.Builder |
addBoolVal(boolean value)
boolean values
|
TensorNamespace.TensorProto.Builder |
addDims(long value)
The shape of the tensor.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addExternalData(int index,
TensorNamespace.StringStringEntryProto.Builder builderForValue)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
addExternalData(int index,
TensorNamespace.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
addExternalData(TensorNamespace.StringStringEntryProto.Builder builderForValue)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
addExternalData(TensorNamespace.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.StringStringEntryProto.Builder |
addExternalDataBuilder()
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.StringStringEntryProto.Builder |
addExternalDataBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addHalfVal(int value)
For half values (tensorflow compatibility)
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
addInt64Data(long value)
For int64.
|
TensorNamespace.TensorProto.Builder |
addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
Object value) |
TensorNamespace.TensorProto.Builder |
addStringData(org.nd4j.shade.protobuf.ByteString value)
For strings.
|
TensorNamespace.TensorProto.Builder |
addUint64Data(long value)
For uint64 and uint32 values
When this field is present, the data_type field MUST be
UINT32 or UINT64
|
TensorNamespace.TensorProto |
build() |
TensorNamespace.TensorProto |
buildPartial() |
TensorNamespace.TensorProto.Builder |
clear() |
TensorNamespace.TensorProto.Builder |
clearBoolVal()
boolean values
|
TensorNamespace.TensorProto.Builder |
clearDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
|
TensorNamespace.TensorProto.Builder |
clearDataType()
The data type of the tensor.
|
TensorNamespace.TensorProto.Builder |
clearDims()
The shape of the tensor.
|
TensorNamespace.TensorProto.Builder |
clearDocString()
A human-readable documentation for this tensor.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
clearExternalData()
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) |
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
clearHalfVal()
For half values (tensorflow compatibility)
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
clearInt64Data()
For int64.
|
TensorNamespace.TensorProto.Builder |
clearName()
Optionally, a name for the tensor.
|
TensorNamespace.TensorProto.Builder |
clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) |
TensorNamespace.TensorProto.Builder |
clearRawData()
Serializations can either use one of the fields above, or use this
raw bytes field.
|
TensorNamespace.TensorProto.Builder |
clearSegment()
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.Builder |
clearStringData()
For strings.
|
TensorNamespace.TensorProto.Builder |
clearUint64Data()
For uint64 and uint32 values
When this field is present, the data_type field MUST be
UINT32 or UINT64
|
TensorNamespace.TensorProto.Builder |
clone() |
boolean |
getBoolVal(int index)
boolean values
|
int |
getBoolValCount()
boolean values
|
List<Boolean> |
getBoolValList()
boolean values
|
TensorNamespace.TensorProto.DataLocation |
getDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
|
int |
getDataLocationValue()
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.
|
TensorNamespace.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
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.
|
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.
|
TensorNamespace.StringStringEntryProto |
getExternalData(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.StringStringEntryProto.Builder |
getExternalDataBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
List<TensorNamespace.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.
|
List<TensorNamespace.StringStringEntryProto> |
getExternalDataList()
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.StringStringEntryProtoOrBuilder |
getExternalDataOrBuilder(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
List<? extends TensorNamespace.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.
|
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.
|
int |
getHalfVal(int index)
For half values (tensorflow compatibility)
|
int |
getHalfValCount()
For half values (tensorflow compatibility)
|
List<Integer> |
getHalfValList()
For half values (tensorflow compatibility)
|
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.
|
TensorNamespace.TensorProto.Segment |
getSegment()
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.Segment.Builder |
getSegmentBuilder()
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.SegmentOrBuilder |
getSegmentOrBuilder()
.org.nd4j.ir.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()
.org.nd4j.ir.TensorProto.Segment segment = 3; |
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable |
internalGetFieldAccessorTable() |
boolean |
isInitialized() |
TensorNamespace.TensorProto.Builder |
mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorNamespace.TensorProto.Builder |
mergeFrom(org.nd4j.shade.protobuf.Message other) |
TensorNamespace.TensorProto.Builder |
mergeFrom(TensorNamespace.TensorProto other) |
TensorNamespace.TensorProto.Builder |
mergeSegment(TensorNamespace.TensorProto.Segment value)
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.Builder |
mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) |
TensorNamespace.TensorProto.Builder |
removeExternalData(int index)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
setBoolVal(int index,
boolean value)
boolean values
|
TensorNamespace.TensorProto.Builder |
setDataLocation(TensorNamespace.TensorProto.DataLocation value)
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
|
TensorNamespace.TensorProto.Builder |
setDataLocationValue(int value)
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
|
TensorNamespace.TensorProto.Builder |
setDataType(int value)
The data type of the tensor.
|
TensorNamespace.TensorProto.Builder |
setDims(int index,
long value)
The shape of the tensor.
|
TensorNamespace.TensorProto.Builder |
setDocString(String value)
A human-readable documentation for this tensor.
|
TensorNamespace.TensorProto.Builder |
setDocStringBytes(org.nd4j.shade.protobuf.ByteString value)
A human-readable documentation for this tensor.
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
setExternalData(int index,
TensorNamespace.StringStringEntryProto.Builder builderForValue)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
setExternalData(int index,
TensorNamespace.StringStringEntryProto value)
Data can be stored inside the protobuf file using type-specific fields or raw_data.
|
TensorNamespace.TensorProto.Builder |
setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
Object value) |
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
setHalfVal(int index,
int value)
For half values (tensorflow compatibility)
|
TensorNamespace.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.
|
TensorNamespace.TensorProto.Builder |
setInt64Data(int index,
long value)
For int64.
|
TensorNamespace.TensorProto.Builder |
setName(String value)
Optionally, a name for the tensor.
|
TensorNamespace.TensorProto.Builder |
setNameBytes(org.nd4j.shade.protobuf.ByteString value)
Optionally, a name for the tensor.
|
TensorNamespace.TensorProto.Builder |
setRawData(org.nd4j.shade.protobuf.ByteString value)
Serializations can either use one of the fields above, or use this
raw bytes field.
|
TensorNamespace.TensorProto.Builder |
setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
int index,
Object value) |
TensorNamespace.TensorProto.Builder |
setSegment(TensorNamespace.TensorProto.Segment.Builder builderForValue)
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.Builder |
setSegment(TensorNamespace.TensorProto.Segment value)
.org.nd4j.ir.TensorProto.Segment segment = 3; |
TensorNamespace.TensorProto.Builder |
setStringData(int index,
org.nd4j.shade.protobuf.ByteString value)
For strings.
|
TensorNamespace.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
|
TensorNamespace.TensorProto.Builder |
setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) |
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder clear()
clear in interface org.nd4j.shade.protobuf.Message.Builderclear in interface org.nd4j.shade.protobuf.MessageLite.Builderclear in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface org.nd4j.shade.protobuf.Message.BuildergetDescriptorForType in interface org.nd4j.shade.protobuf.MessageOrBuildergetDescriptorForType in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto getDefaultInstanceForType()
getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageOrBuilderpublic TensorNamespace.TensorProto build()
build in interface org.nd4j.shade.protobuf.Message.Builderbuild in interface org.nd4j.shade.protobuf.MessageLite.Builderpublic TensorNamespace.TensorProto buildPartial()
buildPartial in interface org.nd4j.shade.protobuf.Message.BuilderbuildPartial in interface org.nd4j.shade.protobuf.MessageLite.Builderpublic TensorNamespace.TensorProto.Builder clone()
clone in interface org.nd4j.shade.protobuf.Message.Builderclone in interface org.nd4j.shade.protobuf.MessageLite.Builderclone in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface org.nd4j.shade.protobuf.Message.BuildersetField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
clearField in interface org.nd4j.shade.protobuf.Message.BuilderclearField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface org.nd4j.shade.protobuf.Message.BuilderclearOneof in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface org.nd4j.shade.protobuf.Message.BuildersetRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface org.nd4j.shade.protobuf.Message.BuilderaddRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.Message other)
mergeFrom in interface org.nd4j.shade.protobuf.Message.BuildermergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder mergeFrom(TensorNamespace.TensorProto other)
public final boolean isInitialized()
isInitialized in interface org.nd4j.shade.protobuf.MessageLiteOrBuilderisInitialized in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public TensorNamespace.TensorProto.Builder mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface org.nd4j.shade.protobuf.Message.BuildermergeFrom in interface org.nd4j.shade.protobuf.MessageLite.BuildermergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<TensorNamespace.TensorProto.Builder>IOExceptionpublic List<Long> getDimsList()
The shape of the tensor.
repeated int64 dims = 1;getDimsList in interface TensorNamespace.TensorProtoOrBuilderpublic int getDimsCount()
The shape of the tensor.
repeated int64 dims = 1;getDimsCount in interface TensorNamespace.TensorProtoOrBuilderpublic long getDims(int index)
The shape of the tensor.
repeated int64 dims = 1;getDims in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setDims(int index, long value)
The shape of the tensor.
repeated int64 dims = 1;public TensorNamespace.TensorProto.Builder addDims(long value)
The shape of the tensor.
repeated int64 dims = 1;public TensorNamespace.TensorProto.Builder addAllDims(Iterable<? extends Long> values)
The shape of the tensor.
repeated int64 dims = 1;public TensorNamespace.TensorProto.Builder clearDims()
The shape of the tensor.
repeated int64 dims = 1;public int getDataType()
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;getDataType in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setDataType(int value)
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;public TensorNamespace.TensorProto.Builder clearDataType()
The data type of the tensor. This field MUST have a valid TensorProto.DataType value
int32 data_type = 2;public boolean hasSegment()
.org.nd4j.ir.TensorProto.Segment segment = 3;hasSegment in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Segment getSegment()
.org.nd4j.ir.TensorProto.Segment segment = 3;getSegment in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setSegment(TensorNamespace.TensorProto.Segment value)
.org.nd4j.ir.TensorProto.Segment segment = 3;public TensorNamespace.TensorProto.Builder setSegment(TensorNamespace.TensorProto.Segment.Builder builderForValue)
.org.nd4j.ir.TensorProto.Segment segment = 3;public TensorNamespace.TensorProto.Builder mergeSegment(TensorNamespace.TensorProto.Segment value)
.org.nd4j.ir.TensorProto.Segment segment = 3;public TensorNamespace.TensorProto.Builder clearSegment()
.org.nd4j.ir.TensorProto.Segment segment = 3;public TensorNamespace.TensorProto.Segment.Builder getSegmentBuilder()
.org.nd4j.ir.TensorProto.Segment segment = 3;public TensorNamespace.TensorProto.SegmentOrBuilder getSegmentOrBuilder()
.org.nd4j.ir.TensorProto.Segment segment = 3;getSegmentOrBuilder in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getFloatDataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getFloatDataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getFloatData in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];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];getInt32DataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getInt32DataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getInt32Data in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];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;getStringDataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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;getStringDataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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;getStringData in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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;public TensorNamespace.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;public TensorNamespace.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;public TensorNamespace.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;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];getInt64DataList in interface TensorNamespace.TensorProtoOrBuilderpublic int getInt64DataCount()
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];getInt64DataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getInt64Data in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.TensorProto.Builder clearInt64Data()
For int64. When this field is present, the data_type field MUST be INT64
repeated int64 int64_data = 7 [packed = true];public String getName()
Optionally, a name for the tensor.
string name = 8;getName in interface TensorNamespace.TensorProtoOrBuilderpublic org.nd4j.shade.protobuf.ByteString getNameBytes()
Optionally, a name for the tensor.
string name = 8;getNameBytes in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setName(String value)
Optionally, a name for the tensor.
string name = 8;public TensorNamespace.TensorProto.Builder clearName()
Optionally, a name for the tensor.
string name = 8;public TensorNamespace.TensorProto.Builder setNameBytes(org.nd4j.shade.protobuf.ByteString value)
Optionally, a name for the tensor.
string name = 8;public String getDocString()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;getDocString in interface TensorNamespace.TensorProtoOrBuilderpublic org.nd4j.shade.protobuf.ByteString getDocStringBytes()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;getDocStringBytes in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setDocString(String value)
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;public TensorNamespace.TensorProto.Builder clearDocString()
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;public TensorNamespace.TensorProto.Builder setDocStringBytes(org.nd4j.shade.protobuf.ByteString value)
A human-readable documentation for this tensor. Markdown is allowed.
string doc_string = 12;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;getRawData in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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;public TensorNamespace.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;public List<TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;getExternalDataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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 .org.nd4j.ir.StringStringEntryProto external_data = 13;getExternalDataCount in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;getExternalData in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setExternalData(int index, TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder setExternalData(int index, TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder addExternalData(TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder addExternalData(int index, TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder addExternalData(TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder addExternalData(int index, TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.TensorProto.Builder addAllExternalData(Iterable<? extends TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;getExternalDataOrBuilder in interface TensorNamespace.TensorProtoOrBuilderpublic List<? extends TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;getExternalDataOrBuilderList in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public List<TensorNamespace.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 .org.nd4j.ir.StringStringEntryProto external_data = 13;public int getDataLocationValue()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.org.nd4j.ir.TensorProto.DataLocation data_location = 14;getDataLocationValue in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setDataLocationValue(int value)
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.org.nd4j.ir.TensorProto.DataLocation data_location = 14;public TensorNamespace.TensorProto.DataLocation getDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.org.nd4j.ir.TensorProto.DataLocation data_location = 14;getDataLocation in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setDataLocation(TensorNamespace.TensorProto.DataLocation value)
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.org.nd4j.ir.TensorProto.DataLocation data_location = 14;public TensorNamespace.TensorProto.Builder clearDataLocation()
If value not set, data is stored in raw_data (if set) otherwise in type-specified field.
.org.nd4j.ir.TensorProto.DataLocation data_location = 14;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];getDoubleDataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getDoubleDataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getDoubleData in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];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];getUint64DataList in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getUint64DataCount in interface TensorNamespace.TensorProtoOrBuilderpublic 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];getUint64Data in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public TensorNamespace.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];public List<Integer> getHalfValList()
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];getHalfValList in interface TensorNamespace.TensorProtoOrBuilderpublic int getHalfValCount()
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];getHalfValCount in interface TensorNamespace.TensorProtoOrBuilderpublic int getHalfVal(int index)
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];getHalfVal in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setHalfVal(int index, int value)
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];public TensorNamespace.TensorProto.Builder addHalfVal(int value)
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];public TensorNamespace.TensorProto.Builder addAllHalfVal(Iterable<? extends Integer> values)
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];public TensorNamespace.TensorProto.Builder clearHalfVal()
For half values (tensorflow compatibility)
repeated int32 half_val = 15 [packed = true];public List<Boolean> getBoolValList()
boolean values
repeated bool bool_val = 16 [packed = true];getBoolValList in interface TensorNamespace.TensorProtoOrBuilderpublic int getBoolValCount()
boolean values
repeated bool bool_val = 16 [packed = true];getBoolValCount in interface TensorNamespace.TensorProtoOrBuilderpublic boolean getBoolVal(int index)
boolean values
repeated bool bool_val = 16 [packed = true];getBoolVal in interface TensorNamespace.TensorProtoOrBuilderpublic TensorNamespace.TensorProto.Builder setBoolVal(int index, boolean value)
boolean values
repeated bool bool_val = 16 [packed = true];public TensorNamespace.TensorProto.Builder addBoolVal(boolean value)
boolean values
repeated bool bool_val = 16 [packed = true];public TensorNamespace.TensorProto.Builder addAllBoolVal(Iterable<? extends Boolean> values)
boolean values
repeated bool bool_val = 16 [packed = true];public TensorNamespace.TensorProto.Builder clearBoolVal()
boolean values
repeated bool bool_val = 16 [packed = true];public final TensorNamespace.TensorProto.Builder setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface org.nd4j.shade.protobuf.Message.BuildersetUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>public final TensorNamespace.TensorProto.Builder mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface org.nd4j.shade.protobuf.Message.BuildermergeUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorNamespace.TensorProto.Builder>Copyright © 2021. All rights reserved.