TensorShapeProto.Builder

classe finale statica pubblica TensorShapeProto.Builder

 Dimensions of a tensor.
Tipo protobuf tensorflow.TensorShapeProto

Metodi pubblici

TensorShapeProto.Builder
addAllDim (Iterable<? estende i valori TensorShapeProto.Dim >)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim ( TensorShapeProto.Dim.Builder builderForValue)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (indice int, TensorShapeProto.Dim.Builder builderForValue)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (indice int, valore TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (valore TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
aggiungiDimBuilder ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
addDimBuilder (indice int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)
TensorShapeProto
costruire ()
TensorShapeProto
buildPartial ()
TensorShapeProto.Builder
chiaro ()
TensorShapeProto.Builder
chiaraDim ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
clearField (campo com.google.protobuf.Descriptors.FieldDescriptor)
TensorShapeProto.Builder
clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
TensorShapeProto.Builder
clearUnknownRank ()
 If true, the number of dimensions in the shape is unknown.
TensorShapeProto.Builder
clone ()
TensorShapeProto
getDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor statico finale
getDescrittore ()
com.google.protobuf.Descriptors.Descriptor
getDescriptorForType ()
TensorShapeProto.Dim
getDim (indice int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
getDimBuilder (indice int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Elenco< TensorShapeProto.Dim.Builder >
getDimBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
int
getDimCount ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Elenco< TensorShapeProto.Dim >
getDimLista ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.DimOrBuilder
getDimOrBuilder (indice int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Elenco<? estende TensorShapeProto.DimOrBuilder >
getDimOrBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
booleano
getUnknownRank ()
 If true, the number of dimensions in the shape is unknown.
booleano finale
èinizializzato ()
TensorShapeProto.Builder
mergeFrom (input com.google.protobuf.CodedInputStream, estensione com.google.protobuf.ExtensionRegistryLiteRegistry)
TensorShapeProto.Builder
mergeFrom (com.google.protobuf.Message altro)
finale TensorShapeProto.Builder
mergeUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
TensorShapeProto.Builder
rimuoviDim (indice int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (indice int, valore TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (indice int, TensorShapeProto.Dim.Builder builderForValue)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)
TensorShapeProto.Builder
setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, indice int, valore oggetto)
finale TensorShapeProto.Builder
setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
TensorShapeProto.Builder
setUnknownRank (valore booleano)
 If true, the number of dimensions in the shape is unknown.

Metodi ereditati

Metodi pubblici

public TensorShapeProto.Builder addAllDim (Iterable<? estende i valori TensorShapeProto.Dim >) 

 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.Builder addDim ( TensorShapeProto.Dim.Builder builderForValue) 

 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.Builder addDim (indice int, TensorShapeProto.Dim.Builder builderForValue) 

 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.Builder addDim (indice int, valore TensorShapeProto.Dim ) 

 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.Builder addDim (valore TensorShapeProto.Dim ) 

 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.Dim.Builder addDimBuilder () 

 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.Dim.Builder addDimBuilder (indice 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 TensorShapeProto.Builder addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)

build pubblica di TensorShapeProto ()

public TensorShapeProto buildPartial ()

pubblico TensorShapeProto.Builder chiaro ()

public TensorShapeProto.Builder clearDim () 

 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.Builder clearField (campo com.google.protobuf.Descriptors.FieldDescriptor)

public TensorShapeProto.Builder clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

public TensorShapeProto.Builder clearUnknownRank () 

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

clone pubblico di TensorShapeProto.Builder ()

public TensorShapeProto getDefaultInstanceForType ()

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()

pubblico com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()

public TensorShapeProto.Dim getDim (indice 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 TensorShapeProto.Dim.Builder getDimBuilder (indice 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;

Elenco pubblico< TensorShapeProto.Dim.Builder > getDimBuilderList () 

 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;

pubblico 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;

Elenco pubblico< 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 (indice 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;

Elenco pubblico<? 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;

booleano pubblico getUnknownRank () 

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

public final booleano isInitialized ()

public TensorShapeProto.Builder mergeFrom (input com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia
IOException

public TensorShapeProto.Builder mergeFrom (com.google.protobuf.Message altro)

pubblico finale TensorShapeProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)

public TensorShapeProto.Builder rimuoviDim (indice 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 TensorShapeProto.Builder setDim (indice int, valore TensorShapeProto.Dim ) 

 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.Builder setDim (indice int, TensorShapeProto.Dim.Builder builderForValue) 

 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.Builder setField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)

public TensorShapeProto.Builder setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, indice int, valore oggetto)

pubblico finale TensorShapeProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)

public TensorShapeProto.Builder setUnknownRank (valore booleano) 

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