TensorShapeProto.Builder

публичный статический конечный класс TensorShapeProto.Builder

 Dimensions of a tensor.
 

Тип Protobuf tensorflow.TensorShapeProto

Публичные методы

TensorShapeProto.Builder	addAllDim (Iterable<? расширяет значения 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 (int index, TensorShapeProto.Dim.Builder builderForValue) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	addDim (индекс int, значение TensorShapeProto.Dim ) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	addDim (значение TensorShapeProto.Dim ) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder	добавитьДимБилдер () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder	addDimBuilder (индекс целого числа) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	addRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)
TensorShapeProto	строить ()
TensorShapeProto	построитьчастичный ()
TensorShapeProto.Builder	прозрачный ()
TensorShapeProto.Builder	очиститьDим () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	ClearField (поле com.google.protobuf.Descriptors.FieldDescriptor)
TensorShapeProto.Builder	ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
TensorShapeProto.Builder	очиститьUnknownRank () If true, the number of dimensions in the shape is unknown.
TensorShapeProto.Builder	клон ()
TensorShapeProto	getDefaultInstanceForType ()
окончательный статический com.google.protobuf.Descriptors.Descriptor	получитьдескриптор ()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType ()
TensorShapeProto.Dim	getDim (целочисленный индекс) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder	getDimBuilder (индекс целого числа) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
Список < TensorShapeProto.Dim.Builder >	getDimBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
интервал	получитьДимКаунт () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
Список < TensorShapeProto.Dim >	получитьDimList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.DimOrBuilder	getDimOrBuilder (индекс целого числа) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
Список<? расширяет TensorShapeProto.DimOrBuilder >	getDimOrBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
логическое значение	getUnknownRank () If true, the number of dimensions in the shape is unknown.
последнее логическое значение	isInitialized ()
TensorShapeProto.Builder	mergeFrom (ввод com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
TensorShapeProto.Builder	mergeFrom (com.google.protobuf.Message другое)
окончательный TensorShapeProto.Builder	mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
TensorShapeProto.Builder	удалитьDim (целочисленный индекс) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	setDim (индекс int, значение TensorShapeProto.Dim ) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	setDim (int index, TensorShapeProto.Dim.Builder builderForValue) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
TensorShapeProto.Builder	setField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)
TensorShapeProto.Builder	setRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, индекс int, значение объекта)
окончательный TensorShapeProto.Builder	setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
TensorShapeProto.Builder	setUnknownRank (логическое значение) If true, the number of dimensions in the shape is unknown.

Унаследованные методы

Из класса java.lang.Object

логическое значение	равно (Объект arg0)
последний класс<?>	получитьКласс ()
интервал	хэш-код ()
окончательная пустота	поставить в известность ()
окончательная пустота	уведомитьВсе ()
Нить	нанизывать ()
окончательная пустота	подождать (длинный arg0, int arg1)
окончательная пустота	подождите (длинный arg0)
окончательная пустота	ждать ()

Из интерфейса org.tensorflow.proto.framework.TensorShapeProtoOrBuilder

абстрактный TensorShapeProto.Dim	getDim (целочисленный индекс) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
абстрактный int	получитьДимКаунт () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
абстрактный список < TensorShapeProto.Dim >	получитьDimList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
абстрактный TensorShapeProto.DimOrBuilder	getDimOrBuilder (индекс целого числа) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
абстрактный список<? расширяет TensorShapeProto.DimOrBuilder >	getDimOrBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
абстрактное логическое значение	getUnknownRank () If true, the number of dimensions in the shape is unknown.

Публичные методы

public TensorShapeProto.Builder addAllDim (Iterable<? расширяет значения 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;

общедоступный 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 (индекс 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 (индекс int, значение 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 (значение 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;

общедоступный 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 (индекс 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 (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)

общедоступная сборка TensorShapeProto ()

общественный TensorShapeProto buildPartial ()

общедоступный TensorShapeProto.Builder очистить ()

общедоступный 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;

общедоступный TensorShapeProto.Builder ClearField (поле com.google.protobuf.Descriptors.FieldDescriptor)

общедоступный TensorShapeProto.Builder ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

общедоступный 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;

общедоступный клон TensorShapeProto.Builder ()

public TensorShapeProto getDefaultInstanceForType ()

общедоступный статический окончательный com.google.protobuf.Descriptors.Descriptor getDescriptor ()

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

public TensorShapeProto.Dim getDim (индекс 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 (индекс 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;

общедоступный список < 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;

общедоступный список < 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 (индекс 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;

общедоступный список<? расширяет 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;

общедоступное логическое значение getUnknownRank ()

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

bool unknown_rank = 3;

публичное финальное логическое значение isInitialized ()

общедоступный TensorShapeProto.Builder mergeFrom (вход com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Броски

Исключение IO

общедоступный TensorShapeProto.Builder mergeFrom (com.google.protobuf.Message другое)

публичный финальный TensorShapeProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public TensorShapeProto.Builder RemoveDim (индекс 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 (индекс int, значение 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 (индекс 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 (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)

public TensorShapeProto.Builder setRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, индекс int, значение объекта)

публичный финальный TensorShapeProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public TensorShapeProto.Builder setUnknownRank (логическое значение)

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

bool unknown_rank = 3;