общедоступный интерфейс TensorShapeProtoOrBuilder
| Известные косвенные подклассы |
Публичные методы
| абстрактный TensorShapeProto.Dim | getDim (целочисленный индекс)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| абстрактный int | получитьДимКаунт ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| абстрактный список < TensorShapeProto.Dim > | получитьDimList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| абстрактный TensorShapeProto.DimOrBuilder | getDimOrBuilder (индекс целого числа)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| абстрактный список<? расширяет TensorShapeProto.DimOrBuilder > | getDimOrBuilderList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| абстрактное логическое значение | getUnknownRank () If true, the number of dimensions in the shape is unknown. |
Публичные методы
публичный абстрактный TensorShapeProto.Dim getDim (индекс int)
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; публичный абстрактный 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; общедоступный абстрактный список < 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; публичный абстрактный TensorShapeProto.DimOrBuilder getDimOrBuilder (индекс int)
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; публичный абстрактный список<? расширяет 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; общедоступное абстрактное логическое значение getUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;