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 | UNKNOWN_RANK_FIELD_NUMBER |
Métodos públicos
booleano | es igual a (Objeto obj) |
estático TensorShapeProto | |
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 | 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 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 | |
final com.google.protobuf.UnknownFieldSet | |
booleano | getUnknownRank () If true, the number of dimensions in the shape is unknown. |
En t | hashCode () |
booleano final | |
estático TensorShapeProto.Builder | newBuilder (prototipo de TensorShapeProto ) |
estático TensorShapeProto.Builder | newBuilder () |
TensorShapeProto.Builder | |
estático TensorShapeProto | parseDelimitedFrom (entrada InputStream) |
estático TensorShapeProto | parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático TensorShapeProto | parseFrom (datos ByteBuffer) |
estático TensorShapeProto | parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático TensorShapeProto | parseFrom (datos ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático TensorShapeProto | parseFrom (entrada com.google.protobuf.CodedInputStream) |
estático TensorShapeProto | parseFrom (byte [] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático TensorShapeProto | parseFrom (datos com.google.protobuf.ByteString) |
estático TensorShapeProto | parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático TensorShapeProto | parseFrom (datos com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático | analizador () |
TensorShapeProto.Builder | toBuilder () |
vacío | writeTo (salida de com.google.protobuf.CodedOutputStream) |
Métodos heredados
Constantes
public static final int DIM_FIELD_NUMBER
Valor constante: 2
público estático final int UNKNOWN_RANK_FIELD_NUMBER
Valor constante: 3
Métodos públicos
public boolean es igual a (Object obj)
público estático final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
public 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;
public 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;
public 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 ()
public int getSerializedSize ()
public final com.google.protobuf.UnknownFieldSet getUnknownFields ()
public boolean getUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
public int hashCode ()
public final boolean isInitialized ()
public static TensorShapeProto parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Lanza
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public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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IOException |
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public static TensorShapeProto parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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InvalidProtocolBufferException |
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público estático TensorShapeProto parseFrom (entrada com.google.protobuf.CodedInputStream)
Lanza
IOException |
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public static TensorShapeProto parseFrom (byte [] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Lanza
InvalidProtocolBufferException |
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público estático TensorShapeProto parseFrom (com.google.protobuf.ByteString data)
Lanza
InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Lanza
IOException |
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public static TensorShapeProto parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Lanza
InvalidProtocolBufferException |
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público estático analizador ()
public void writeTo (salida de com.google.protobuf.CodedOutputStream)
Lanza
IOException |
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