TensorShapeProtoOrBuilder

giao diện công cộng TensorShapeProtoOrBuilder
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Phương pháp công cộng

trừu tượng TensorShapeProto.Dim
getDim (chỉ số int) 
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
int trừu tượng
getDimCount () 
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Danh sách trừu tượng< TensorShapeProto.Dim >
getDimList () 
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
trừu tượng TensorShapeProto.DimOrBuilder
getDimOrBuilder (chỉ mục int) 
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Danh sách trừu tượng<? mở rộng TensorShapeProto.DimOrBuilder >
getDimOrBuilderList () 
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
trừu tượng boolean
getUnknownRank () 
 If true, the number of dimensions in the shape is unknown.

Phương pháp công cộng

tóm tắt công khai TensorShapeProto.Dim getDim (chỉ mục 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;

tóm tắt công khai 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;

Danh sách tóm tắt công khai< 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;

tóm tắt công khai TensorShapeProto.DimOrBuilder getDimOrBuilder (chỉ mục 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;

Danh sách tóm tắt công khai<? mở rộng 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;

boolean trừu tượng công khai getUnknownRank () 

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