TensorShapeProto.Builder

classe finale statique publique TensorShapeProto.Builder

 Dimensions of a tensor.
tensorflow.TensorShapeProto de type Protobuf.TensorShapeProto

Méthodes publiques

TensorShapeProto.Builder
addAllDim (Iterable<? extends TensorShapeProto.Dim > valeurs)
 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 (index 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 (index int, valeur TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (valeur TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
addDimBuilder ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
addDimBuilder (index int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)
TensorShapeProto
construire ()
TensorShapeProto
buildPartial ()
TensorShapeProto.Builder
clair ()
TensorShapeProto.Builder
clairDim ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
clearField (champ 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
cloner ()
TensorShapeProto
getDefaultInstanceForType ()
final statique com.google.protobuf.Descriptors.Descriptor
getDescripteur ()
com.google.protobuf.Descriptors.Descriptor
getDescriptorForType ()
TensorShapeProto.Dim
getDim (index entier)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
getDimBuilder (index entier)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Liste< 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.
Liste< TensorShapeProto.Dim >
getDimList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.DimOrBuilder
getDimOrBuilder (index int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
Liste<? étend TensorShapeProto.DimOrBuilder >
getDimOrBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
booléen
getUnknownRank ()
 If true, the number of dimensions in the shape is unknown.
booléen final
estInitialisé ()
TensorShapeProto.Builder
mergeFrom (entrée com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
TensorShapeProto.Builder
mergeFrom (com.google.protobuf.Message autre)
TensorShapeProto.Builder final
mergeUnknownFields (com.google.protobuf.UnknownFieldSet inconnuFields)
TensorShapeProto.Builder
RemoveDim (index int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (index int, valeur TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (index 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 (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)
TensorShapeProto.Builder
setRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, index int, valeur de l'objet)
TensorShapeProto.Builder final
setUnknownFields (com.google.protobuf.UnknownFieldSet inconnuFields)
TensorShapeProto.Builder
setUnknownRank (valeur booléenne)
 If true, the number of dimensions in the shape is unknown.

Méthodes héritées

Méthodes publiques

public TensorShapeProto.Builder addAllDim (Iterable<? étend TensorShapeProto.Dim > valeurs) 

 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 (index 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 (index int, valeur 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 (valeur 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 (index 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 (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)

build public TensorShapeProto ()

public TensorShapeProto buildPartial ()

public TensorShapeProto.Builder clear ()

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 (champ 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 public TensorShapeProto.Builder ()

public TensorShapeProto getDefaultInstanceForType ()

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

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

public TensorShapeProto.Dim getDim (index 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 (index 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;

Liste publique < 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;

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;

liste publique < 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 (index 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;

Liste publique <? étend 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;

public booléen 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 booléen isInitialized ()

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

Jetés
IOException

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

public final TensorShapeProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)

public TensorShapeProto.Builder removeDim (index 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 (index int, valeur 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 (index 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 (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)

public TensorShapeProto.Builder setRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, index int, valeur de l'objet)

public final TensorShapeProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)

public TensorShapeProto.Builder setUnknownRank (valeur booléenne) 

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