Interface TensorShapeProtoOrBuilder

All Superinterfaces:
MessageLiteOrBuilder, MessageOrBuilder
All Known Implementing Classes:
TensorShapeProto, TensorShapeProto.Builder
public interface TensorShapeProtoOrBuilder extends MessageOrBuilder

  • Method Details

    • getDimList

      List<TensorShapeProto.Dim> getDimList()
      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.
      repeated .tensorflow.TensorShapeProto.Dim dim = 2;

    • getDim

      TensorShapeProto.Dim getDim(int index)
      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.
      repeated .tensorflow.TensorShapeProto.Dim dim = 2;

    • getDimCount

      int getDimCount()
      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.
      repeated .tensorflow.TensorShapeProto.Dim dim = 2;

    • getDimOrBuilderList

      List<? extends TensorShapeProto.DimOrBuilder> getDimOrBuilderList()
      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.
      repeated .tensorflow.TensorShapeProto.Dim dim = 2;

    • getDimOrBuilder

      TensorShapeProto.DimOrBuilder getDimOrBuilder(int index)
      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.
      repeated .tensorflow.TensorShapeProto.Dim dim = 2;

    • getUnknownRank

      boolean getUnknownRank()
      If true, the number of dimensions in the shape is unknown.
If true, "dim.size()" must be 0.
      bool unknown_rank = 3;
      Returns:
      The unknownRank.