Class/Object

io.hydrosphere.serving.tensorflow.tensor_shape

TensorShapeProto

Related Docs: object TensorShapeProto | package tensor_shape

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final case class TensorShapeProto(dim: Seq[Dim] = _root_.scala.collection.Seq.empty, unknownRank: Boolean = false) extends GeneratedMessage with Message[TensorShapeProto] with Updatable[TensorShapeProto] with Product with Serializable

Dimensions of a tensor.

dim

Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.

unknownRank

If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.

Annotations
@SerialVersionUID()
Linear Supertypes
Product, Equals, Updatable[TensorShapeProto], Message[TensorShapeProto], GeneratedMessage, Serializable, Serializable, AnyRef, Any
Ordering
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  2. By Inheritance
Inherited
  1. TensorShapeProto
  2. Product
  3. Equals
  4. Updatable
  5. Message
  6. GeneratedMessage
  7. Serializable
  8. Serializable
  9. AnyRef
  10. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TensorShapeProto(dim: Seq[Dim] = _root_.scala.collection.Seq.empty, unknownRank: Boolean = false)

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    dim

    Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.

    unknownRank

    If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. def addAllDim(__vs: TraversableOnce[Dim]): TensorShapeProto

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  5. def addDim(__vs: Dim*): TensorShapeProto

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  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def clearDim: TensorShapeProto

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  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  9. def companion: TensorShapeProto.type

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  10. val dim: Seq[Dim]

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    Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.

    Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.

  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  12. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  13. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  14. def getField(__field: FieldDescriptor): PValue

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  15. def getFieldByNumber(__fieldNumber: Int): Any

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  17. def mergeFrom(_input__: CodedInputStream): TensorShapeProto

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    Definition Classes
    TensorShapeProto → Message

  18. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  19. final def notify(): Unit

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    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  21. final def serializedSize: Int

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  22. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  23. def toByteArray: Array[Byte]

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    Definition Classes
    GeneratedMessage

  24. def toByteString: ByteString

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    Definition Classes
    GeneratedMessage

  25. def toPMessage: PMessage

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    Definition Classes
    GeneratedMessage

  26. def toProtoString: String

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  27. val unknownRank: Boolean

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    If true, the number of dimensions in the shape is unknown.

    If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.

  28. def update(ms: (Lens[TensorShapeProto, TensorShapeProto]) ⇒ Mutation[TensorShapeProto]*): TensorShapeProto

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    Definition Classes
    Updatable

  29. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  30. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  31. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  32. def withDim(__v: Seq[Dim]): TensorShapeProto

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  33. def withUnknownRank(__v: Boolean): TensorShapeProto

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  34. def writeDelimitedTo(output: OutputStream): Unit

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    Definition Classes
    GeneratedMessage

  35. def writeTo(_output__: CodedOutputStream): Unit

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    Definition Classes
    TensorShapeProto → GeneratedMessage

  36. def writeTo(output: OutputStream): Unit

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    Definition Classes
    GeneratedMessage

Deprecated Value Members

  1. def getAllFields: Map[FieldDescriptor, Any]

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    Definition Classes
    GeneratedMessage
    Annotations
    @deprecated
    Deprecated

    (Since version 0.6.0) Use toPMessage

  2. def getField(field: FieldDescriptor): Any

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    Definition Classes
    GeneratedMessage
    Annotations
    @deprecated
    Deprecated

    (Since version 0.6.0) Use getField that accepts a ScalaPB descriptor and returns PValue

Inherited from Product

Inherited from Equals

Inherited from Updatable[TensorShapeProto]

Inherited from Message[TensorShapeProto]

Inherited from GeneratedMessage

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped