final case class TensorShapeProto(dim: Seq[Dim] = _root_.scala.Seq.empty, unknownRank: Boolean = false, unknownFields: UnknownFieldSet = ...) extends GeneratedMessage 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.
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        TensorShapeProto(dim: Seq[Dim] = _root_.scala.Seq.empty, unknownRank: Boolean = false, unknownFields: UnknownFieldSet = ...)
      
      
      
- 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.
 
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 -  def addAllDim(__vs: Iterable[Dim]): TensorShapeProto
 -  def addDim(__vs: Dim*): TensorShapeProto
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 -  def clearDim: TensorShapeProto
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        companion: TensorShapeProto.type
      
      
      
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 - TensorShapeProto → GeneratedMessage
 
 -  val dim: Seq[Dim]
 -  def discardUnknownFields: TensorShapeProto
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 -  val unknownFields: UnknownFieldSet
 -  val unknownRank: Boolean
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        update(ms: (Lens[TensorShapeProto, TensorShapeProto]) ⇒ Mutation[TensorShapeProto]*): TensorShapeProto
      
      
      
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 -  def withDim(__v: Seq[Dim]): TensorShapeProto
 -  def withUnknownFields(__v: UnknownFieldSet): TensorShapeProto
 -  def withUnknownRank(__v: Boolean): TensorShapeProto
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