classe final pública TensorShapeProto
Dimensions of a tensor.
tensorflow.TensorShapeProto
type tensorflow.TensorShapeProto
Classes aninhadas
aula | TensorShapeProto.Builder | Dimensions of a tensor. | |
aula | TensorShapeProto.Dim | One dimension of the tensor. | |
interface | TensorShapeProto.DimOrBuilder |
Constantes
int | DIM_FIELD_NUMBER | |
int | UNKNOWN_RANK_FIELD_NUMBER |
Métodos Públicos
boleano | igual a (objeto obj) |
TensorShapeProto estático | |
TensorShapeProto | |
final static com.google.protobuf.Descriptors.Descriptor | |
TensorShapeProto.Dim | |
int | getDimCount () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
List < 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. |
int | |
final com.google.protobuf.UnknownFieldSet | |
boleano | getUnknownRank () If true, the number of dimensions in the shape is unknown. |
int | hashCode () |
final booleano | |
static TensorShapeProto.Builder | newBuilder (protótipo TensorShapeProto ) |
static TensorShapeProto.Builder | newBuilder () |
TensorShapeProto.Builder | |
TensorShapeProto estático | parseDelimitedFrom (input InputStream) |
TensorShapeProto estático | parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (dados ByteBuffer) |
TensorShapeProto estático | parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (com.google.protobuf.CodedInputStream input) |
TensorShapeProto estático | parseFrom (byte [] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (com.google.protobuf.ByteString data) |
TensorShapeProto estático | parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto estático | parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático | analisador () |
TensorShapeProto.Builder | toBuilder () |
vazio | writeTo (saída com.google.protobuf.CodedOutputStream) |
Métodos herdados
Constantes
public static final int DIM_FIELD_NUMBER
Valor constante: 2
public static final int UNKNOWN_RANK_FIELD_NUMBER
Valor Constante: 3
Métodos Públicos
public boolean equals (Object obj)
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
public TensorShapeProto.Dim getDim (int index)
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;
public List < 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 interno )
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 ()
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)
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public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static TensorShapeProto parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input)
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public static TensorShapeProto parseFrom (byte [] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static TensorShapeProto parseFrom (com.google.protobuf.ByteString data)
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InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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IOException |
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public static TensorShapeProto parseFrom (com.google.protobuf.ByteString data, 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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