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