الواجهة العامة TensorShapeProtoOrBuilder
| الفئات الفرعية غير المباشرة المعروفة |
الأساليب العامة
| مجردة TensorShapeProto.Dim | getDim (فهرس كثافة العمليات)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| كثافة العمليات مجردة | الحصول علىDimCount ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| قائمة مجردة< TensorShapeProto.Dim > | الحصول علىDimList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| مجردة TensorShapeProto.DimOrBuilder | getDimOrBuilder (فهرس كثافة العمليات)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| قائمة مجردة <؟ يمتد TensorShapeProto.DimOrBuilder > | الحصول علىDimOrBuilderList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. |
| منطقية مجردة | الحصول على UnknownRank () If true, the number of dimensions in the shape is unknown. |
الأساليب العامة
الملخص العام TensorShapeProto.Dim getDim (مؤشر 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; الملخص العام 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; قائمة مجردة عامة< 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; الملخص العام TensorShapeProto.DimOrBuilder getDimOrBuilder (فهرس كثافة العمليات)
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; قائمة الملخصات العامة<؟ يمتد 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; الملخص المنطقي العام getUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;