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;
*/
org.tensorflow.framework.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;
*/
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;
*/
java.util.List
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;
*/
org.tensorflow.framework.TensorShapeProto.DimOrBuilder getDimOrBuilder(
int index);
/**
*
* If true, the number of dimensions in the shape is unknown.
* If true, "dim.size()" must be 0.
*
*
* bool unknown_rank = 3;
*/
boolean getUnknownRank();
}
