final case class SparseTensorProto(values: Option[TensorProto] = _root_.scala.None, indices: Option[TensorProto] = _root_.scala.None, dims: Seq[Long] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = ...) extends GeneratedMessage with Updatable[SparseTensorProto] with Product with Serializable
A serialized sparse-tensor value
- values
The sequence of non-default values are encoded as a tensor of shape [NNZ]. The default-value is zero for numeric tensors, and empty-string for string tensors. values must have a non-empty name present which serves as a name for SparseTensorProto when used in sparse_initializer list.
- indices
The indices of the non-default values, which may be stored in one of two formats. (a) Indices can be a tensor of shape [NNZ, rank] with the [i,j]-th value corresponding to the j-th index of the i-th value (in the values tensor). (b) Indices can be a tensor of shape [NNZ], in which case the i-th value must be the linearized-index of the i-th value (in the values tensor). The linearized-index can be converted into an index tuple (k_1,...,k_rank) using the shape provided below. The indices must appear in ascending order without duplication. In the first format, the ordering is lexicographic-ordering: e.g., index-value [1,4] must appear before [2,1]
- dims
The shape of the underlying dense-tensor: [dim_1, dim_2, ... dim_rank]
- Annotations
- @SerialVersionUID()
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- SparseTensorProto
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Instance Constructors
-
new
SparseTensorProto(values: Option[TensorProto] = _root_.scala.None, indices: Option[TensorProto] = _root_.scala.None, dims: Seq[Long] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = ...)
- values
The sequence of non-default values are encoded as a tensor of shape [NNZ]. The default-value is zero for numeric tensors, and empty-string for string tensors. values must have a non-empty name present which serves as a name for SparseTensorProto when used in sparse_initializer list.
- indices
The indices of the non-default values, which may be stored in one of two formats. (a) Indices can be a tensor of shape [NNZ, rank] with the [i,j]-th value corresponding to the j-th index of the i-th value (in the values tensor). (b) Indices can be a tensor of shape [NNZ], in which case the i-th value must be the linearized-index of the i-th value (in the values tensor). The linearized-index can be converted into an index tuple (k_1,...,k_rank) using the shape provided below. The indices must appear in ascending order without duplication. In the first format, the ordering is lexicographic-ordering: e.g., index-value [1,4] must appear before [2,1]
- dims
The shape of the underlying dense-tensor: [dim_1, dim_2, ... dim_rank]
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def addAllDims(__vs: Iterable[Long]): SparseTensorProto
- def addDims(__vs: Long*): SparseTensorProto
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clearDims: SparseTensorProto
- def clearIndices: SparseTensorProto
- def clearValues: SparseTensorProto
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native() @HotSpotIntrinsicCandidate()
-
def
companion: SparseTensorProto.type
- Definition Classes
- SparseTensorProto → GeneratedMessage
- val dims: Seq[Long]
- def discardUnknownFields: SparseTensorProto
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
-
def
getField(__field: FieldDescriptor): PValue
- Definition Classes
- SparseTensorProto → GeneratedMessage
-
def
getFieldByNumber(__fieldNumber: Int): Any
- Definition Classes
- SparseTensorProto → GeneratedMessage
- def getIndices: TensorProto
- def getValues: TensorProto
- val indices: Option[TensorProto]
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
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final
def
notify(): Unit
- Definition Classes
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- @native() @HotSpotIntrinsicCandidate()
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final
def
notifyAll(): Unit
- Definition Classes
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- Annotations
- @native() @HotSpotIntrinsicCandidate()
-
def
serializedSize: Int
- Definition Classes
- SparseTensorProto → GeneratedMessage
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
final
def
toByteArray: Array[Byte]
- Definition Classes
- GeneratedMessage
-
final
def
toByteString: ByteString
- Definition Classes
- GeneratedMessage
-
final
def
toPMessage: PMessage
- Definition Classes
- GeneratedMessage
-
def
toProtoString: String
- Definition Classes
- SparseTensorProto → GeneratedMessage
- val unknownFields: UnknownFieldSet
-
def
update(ms: (Lens[SparseTensorProto, SparseTensorProto]) ⇒ Mutation[SparseTensorProto]*): SparseTensorProto
- Definition Classes
- Updatable
- val values: Option[TensorProto]
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
- def withDims(__v: Seq[Long]): SparseTensorProto
- def withIndices(__v: TensorProto): SparseTensorProto
- def withUnknownFields(__v: UnknownFieldSet): SparseTensorProto
- def withValues(__v: TensorProto): SparseTensorProto
-
final
def
writeDelimitedTo(output: OutputStream): Unit
- Definition Classes
- GeneratedMessage
-
def
writeTo(_output__: CodedOutputStream): Unit
- Definition Classes
- SparseTensorProto → GeneratedMessage
-
final
def
writeTo(output: OutputStream): Unit
- Definition Classes
- GeneratedMessage
Deprecated Value Members
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
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- Annotations
- @throws( classOf[java.lang.Throwable] ) @Deprecated
- Deprecated