classe final pública TensorShapeProto
Dimensions of a tensor.Protobuf tipo
tensorflow.TensorShapeProto
Classes aninhadas
aula | TensorShapeProto.Builder | Dimensions of a tensor. | |
aula | TensorShapeProto.Dim | One dimension of the tensor. | |
interface | TensorShapeProto.DimOrBuilder |
Constantes
interno | DIM_FIELD_NUMBER | |
interno | UNKNOWN_RANK_FIELD_NUMBER |
Métodos Públicos
boleano | é igual (objeto obj) |
TensorShapeProto estático | |
TensorShapeProto | |
final estático com.google.protobuf.Descriptors.Descriptor | |
TensorShapeProto.Dim | getDim (índice interno) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
interno | getDimCount () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
Lista< TensorShapeProto.Dim > | getDimList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.DimOrBuilder | getDimOrBuilder (índice interno) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
Lista<? estende TensorShapeProto.DimOrBuilder > | getDimOrBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
interno | |
final com.google.protobuf.UnknownFieldSet | |
boleano | getUnknownRank () If true, the number of dimensions in the shape is unknown. |
interno | código hash () |
booleano final | |
TensorShapeProto.Builder estático | newBuilder (protótipo TensorShapeProto ) |
TensorShapeProto.Builder estático | |
TensorShapeProto.Builder | |
TensorShapeProto estático | parseDelimitedFrom (entrada InputStream) |
TensorShapeProto estático | parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (dados de ByteBuffer) |
TensorShapeProto estático | parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (dados de ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (entrada com.google.protobuf.CodedInputStream) |
TensorShapeProto estático | parseFrom (byte[] dados, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (dados com.google.protobuf.ByteString) |
TensorShapeProto estático | parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (dados com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático | analisador () |
TensorShapeProto.Builder | |
vazio | writeTo (saída com.google.protobuf.CodedOutputStream) |
Métodos herdados
Constantes
int final estático público DIM_FIELD_NUMBER
Valor Constante: 2
público estático final int UNKNOWN_RANK_FIELD_NUMBER
Valor Constante: 3
Métodos Públicos
booleano público é igual (Object obj)
final estático público com.google.protobuf.Descriptors.Descriptor getDescriptor ()
público TensorShapeProto.Dim getDim (índice 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;
público 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;
Lista pública< 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;
público TensorShapeProto.DimOrBuilder getDimOrBuilder (índice 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;
Lista pública<? estende 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;
público getParserForType ()
público int getSerializedSize ()
final público com.google.protobuf.UnknownFieldSet getUnknownFields ()
getUnknownRank booleano público ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
hashCode int público ()
público final booleano isInitialized ()
public static TensorShapeProto parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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público estático TensorShapeProto parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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público estático TensorShapeProto parseFrom (dados ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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InvalidProtocolBufferException |
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público estático TensorShapeProto parseFrom (entrada com.google.protobuf.CodedInputStream)
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público estático TensorShapeProto parseFrom (byte[] dados, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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TensorShapeProto estático público parseFrom (dados com.google.protobuf.ByteString)
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InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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público estático TensorShapeProto parseFrom (dados com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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InvalidProtocolBufferException |
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estática pública analisador ()
public void writeTo (saída com.google.protobuf.CodedOutputStream)
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