TensorShapeProto.Builder

الطبقة النهائية العامة الثابتة TensorShapeProto.Builder

 Dimensions of a tensor.
نوع Protobuf tensorflow.TensorShapeProto

الأساليب العامة

TensorShapeProto.Builder
addAllDim (Iterable<؟ يمتد TensorShapeProto.Dim > القيم)
 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 (مؤشر 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 (مؤشر int، قيمة TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (قيمة 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 (فهرس كثافة العمليات)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
TensorShapeProto
يبني ()
TensorShapeProto
بناء جزئي ()
TensorShapeProto.Builder
واضح ()
TensorShapeProto.Builder
كليرديم ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
ClearField (حقل 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
استنساخ ()
TensorShapeProto
getDefaultInstanceForType ()
النهائي الثابت com.google.protobuf.Descriptors.Descriptor
الحصول على واصف ()
com.google.protobuf.Descriptors.Descriptor
الحصول على DescriptorForType ()
TensorShapeProto.Dim
getDim (فهرس كثافة العمليات)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
getDimBuilder (فهرس كثافة العمليات)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
القائمة< TensorShapeProto.Dim.Builder >
الحصول علىDimBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
كثافة العمليات
الحصول علىDimCount ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
القائمة< TensorShapeProto.Dim >
الحصول علىDimList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.DimOrBuilder
getDimOrBuilder (فهرس كثافة العمليات)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
القائمة<؟ يمتد TensorShapeProto.DimOrBuilder >
الحصول علىDimOrBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
منطقية
الحصول على UnknownRank ()
 If true, the number of dimensions in the shape is unknown.
منطقية نهائية
تمت التهيئة ()
TensorShapeProto.Builder
دمج من (com.google.protobuf.CodedInputStream input، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
TensorShapeProto.Builder
دمج من (com.google.protobuf.Message أخرى)
TensorShapeProto.Builder النهائي
دمجUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
TensorShapeProto.Builder
إزالةديم (مؤشر كثافة العمليات)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (مؤشر int، قيمة TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (مؤشر 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 (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
TensorShapeProto.Builder
setRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، فهرس int، قيمة الكائن)
TensorShapeProto.Builder النهائي
setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
TensorShapeProto.Builder
setUnknownRank (قيمة منطقية)
 If true, the number of dimensions in the shape is unknown.

الطرق الموروثة

الأساليب العامة

TensorShapeProto.Builder addAllDim العام (Iterable<؟ يمتد TensorShapeProto.Dim > القيم) 

 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;

TensorShapeProto.Builder addDim العام ( 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;

TensorShapeProto.Builder addDim العام (مؤشر 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;

TensorShapeProto.Builder addDim العام (مؤشر int، قيمة 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;

TensorShapeProto.Builder addDim العام (قيمة 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;

TensorShapeProto.Dim.Builder العام 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;

TensorShapeProto.Dim.Builder العام addDimBuilder (مؤشر 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;

TensorShapeProto.Builder addRepeatedField العام (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)

بناء TensorShapeProto العام ()

TensorShapeProto buildPartial () العام

TensorShapeProto.Builder العام واضح ()

TensorShapeProto.Builder العام 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;

TensorShapeProto.Builder ClearField العام (حقل com.google.protobuf.Descriptors.FieldDescriptor)

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

TensorShapeProto.Builder العام ClearUnknownRank () 

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

استنساخ TensorShapeProto.Builder العام ()

TensorShapeProto getDefaultInstanceForType () العام

النهائي العام الثابت com.google.protobuf.Descriptors.Descriptor getDescriptor ()

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

TensorShapeProto.Dim getDim العام (مؤشر 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;

TensorShapeProto.Dim.Builder public getDimBuilder (مؤشر 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;

القائمة العامة< 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;

int public 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;

القائمة العامة< 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;

TensorShapeProto.DimOrBuilder العام getDimOrBuilder (مؤشر كثافة العمليات) 

 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;

القائمة العامة <؟ يمتد 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;

getUnknownRank () المنطقية العامة 

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

تمت تهيئة القيمة المنطقية النهائية العامة ()

TensorShapeProto.Builder mergeFrom العام (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
IOEException

TensorShapeProto.Builder mergeFrom العام (com.google.protobuf.Messageother)

TensorShapeProto.Builder النهائي العام mergeUnknownFields (com.google.protobuf.UnknownFieldSetUnknownFields)

TensorShapeProto.Builder العام RemoveDim (مؤشر 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;

TensorShapeProto.Builder setDim العام (مؤشر int، قيمة 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;

TensorShapeProto.Builder setDim العام (مؤشر 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;

TensorShapeProto.Builder setField العام (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)

TensorShapeProto.Builder setRepeatedField العام (com.google.protobuf.Descriptors.FieldDescriptor، حقل int، قيمة الكائن)

TensorShapeProto.Builder النهائي العام setUnknownFields (com.google.protobuf.UnknownFieldSetUnknownFields)

TensorShapeProto.Builder العام setUnknownRank (قيمة منطقية) 

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