clase final pública TensorShapeProto
Dimensions of a tensor.Protobuf tipo
tensorflow.TensorShapeProto
Clases anidadas
clase | TensorShapeProto.Builder | Dimensions of a tensor. | |
clase | TensorShapeProto.Dim | One dimension of the tensor. | |
interfaz | TensorShapeProto.DimOrBuilder |
Constantes
En t | DIM_FIELD_NUMBER | |
En t | DESCONOCIDO_RANK_FIELD_NUMBER |
Métodos públicos
booleano | es igual (Objeto obj) |
TensorShapeProto estático | |
TensorShapeProto | |
com.google.protobuf.Descriptors.Descriptor estático final | |
TensorShapeProto.Dim | getDim (índice int) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
En t | obtenerDimCount () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
Lista< TensorShapeProto.Dim > | obtenerListaDim () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.DimOrBuilder | getDimOrBuilder (índice int) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
Lista<? extiende TensorShapeProto.DimOrBuilder > | getDimOrBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
En t | |
com.google.protobuf.UnknownFieldSet final | |
booleano | obtener rango desconocido () If true, the number of dimensions in the shape is unknown. |
En t | código hash () |
booleano final | |
TensorShapeProto.Builder estático | newBuilder (prototipo TensorShapeProto ) |
TensorShapeProto.Builder estático | |
TensorShapeProto.Builder | |
TensorShapeProto estático | parseDelimitedFrom (entrada de InputStream) |
TensorShapeProto estático | parseDelimitedFrom (entrada de InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (datos de ByteBuffer) |
TensorShapeProto estático | parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensiónRegistry) |
TensorShapeProto estático | parseFrom (datos de ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (entrada com.google.protobuf.CodedInputStream) |
TensorShapeProto estático | parseFrom (byte[] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (datos com.google.protobuf.ByteString) |
TensorShapeProto estático | parseFrom (entrada de InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (com.google.protobuf.ByteString datos, com.google.protobuf.ExtensionRegistryLite extensiónRegistry) |
estático | analizador () |
TensorShapeProto.Builder | |
vacío | writeTo (salida de com.google.protobuf.CodedOutputStream) |
Métodos heredados
Constantes
int final estático público DIM_FIELD_NUMBER
Valor constante: 2
int final estático público UNKNOWN_RANK_FIELD_NUMBER
Valor constante: 3
Métodos públicos
público booleano es igual (Objeto obj)
público estático final 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<? extiende 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 ()
público final com.google.protobuf.UnknownFieldSet getUnknownFields ()
getUnknownRank público booleano ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
código hash int público ()
público final booleano isInitialized ()
TensorShapeProto estático público parseDelimitedFrom (entrada de InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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público estático TensorShapeProto parseFrom (datos ByteBuffer)
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parseFrom público estático de TensorShapeProto (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensiónRegistry)
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público estático TensorShapeProto parseFrom (datos ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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parseFrom público estático de TensorShapeProto (entrada com.google.protobuf.CodedInputStream)
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público estático TensorShapeProto parseFrom (byte[] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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Excepción de buffer de protocolo no válido |
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público estático TensorShapeProto parseFrom (datos com.google.protobuf.ByteString)
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Excepción de buffer de protocolo no válido |
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público estático TensorShapeProto parseFrom (entrada de InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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IOExcepción |
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público estático TensorShapeProto parseFrom (datos com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Lanza
Excepción de buffer de protocolo no válido |
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estática pública analizador ()
escritura vacía pública (salida de com.google.protobuf.CodedOutputStream)
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