TensorShapeProto.Builder

คลาสสุดท้ายแบบคงที่สาธารณะ TensorShapeProto.Builder

 Dimensions of a tensor.
Protobuf ประเภท tensorflow.TensorShapeProto

วิธีการสาธารณะ

TensorShapeProto.Builder
addAllDim (Iterable<? ขยาย TensorShapeProto.Dim > ค่า)
 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 (ดัชนี 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 (ดัชนี int, ค่า TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addDim (ค่า 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 (ดัชนี int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ช่อง ค่าอ็อบเจ็กต์)
เทนเซอร์รูปร่างโปรโต
สร้าง ()
เทนเซอร์รูปร่างโปรโต
สร้างบางส่วน ()
TensorShapeProto.Builder
ชัดเจน ()
TensorShapeProto.Builder
เคลียร์ดิม ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
clearField (ฟิลด์ 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
โคลน ()
เทนเซอร์รูปร่างโปรโต
getDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor แบบคงที่ขั้นสุดท้าย
รับคำอธิบาย ()
com.google.protobuf.Descriptors.Descriptor
getDescriptorForType ()
TensorShapeProto.Dim
getDim (ดัชนี int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Dim.Builder
getDimBuilder (ดัชนี int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
รายการ < TensorShapeProto.Dim.Builder >
getDimBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
ภายใน
รับDimCount ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
รายการ < TensorShapeProto.Dim >
getDimList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.DimOrBuilder
getDimOrBuilder (ดัชนี int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
รายการ<? ขยาย TensorShapeProto.DimOrBuilder >
getDimOrBuilderList ()
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
บูลีน
getUnknownRank ()
 If true, the number of dimensions in the shape is unknown.
บูลีนสุดท้าย
เป็นค่าเริ่มต้น ()
TensorShapeProto.Builder
mergeFrom (com.google.protobuf.CodedInputStream อินพุต com.google.protobuf.ExtensionRegistryLite extensionRegistry)
TensorShapeProto.Builder
mergeFrom (com.google.protobuf.ข้อความ อื่น ๆ )
TensorShapeProto.Builder สุดท้าย
mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
TensorShapeProto.Builder
RemoveDim (ดัชนี int)
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (ดัชนี int, ค่า TensorShapeProto.Dim )
 Dimensions of the tensor, such as {"input", 30}, {"output", 40}
 for a 30 x 40 2D tensor.
TensorShapeProto.Builder
setDim (ดัชนี 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 (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor ค่าอ็อบเจ็กต์)
TensorShapeProto.Builder
setRepeatedField (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor, ดัชนี int, ค่าอ็อบเจ็กต์)
TensorShapeProto.Builder สุดท้าย
setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
TensorShapeProto.Builder
setUnknownRank (ค่าบูลีน)
 If true, the number of dimensions in the shape is unknown.

วิธีการสืบทอด

วิธีการสาธารณะ

สาธารณะ TensorShapeProto.Builder addAllDim (Iterable <? ขยาย TensorShapeProto.Dim > ค่า) 

 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;

สาธารณะ 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;

สาธารณะ TensorShapeProto.Builder addDim (ดัชนี 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;

สาธารณะ TensorShapeProto.Builder addDim (ดัชนี int, ค่า 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;

สาธารณะ TensorShapeProto.Builder addDim (ค่า 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;

สาธารณะ 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;

สาธารณะ TensorShapeProto.Dim.Builder addDimBuilder (ดัชนี 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;

สาธารณะ TensorShapeProto.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ฟิลด์ ค่าอ็อบเจ็กต์)

การสร้าง TensorShapeProto สาธารณะ ()

สาธารณะ TensorShapeProto buildPartial ()

สาธารณะ TensorShapeProto.Builder ชัดเจน ()

สาธารณะ 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;

สาธารณะ TensorShapeProto.Builder clearField (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor)

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

สาธารณะ 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;

โคลน TensorShapeProto.Builder สาธารณะ ()

TensorShapeProto สาธารณะ รับ DefaultInstanceForType ()

สาธารณะคงที่สุดท้าย com.google.protobuf.Descriptors.Descriptor getDescriptor ()

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

สาธารณะ TensorShapeProto.Dim getDim (ดัชนี 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;

สาธารณะ TensorShapeProto.Dim.Builder getDimBuilder (ดัชนี 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;

รายการสาธารณะ < 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;

สาธารณะ 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;

รายการสาธารณะ < 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;

สาธารณะ TensorShapeProto.DimOrBuilder getDimOrBuilder (ดัชนี 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;

รายการสาธารณะ<? ขยาย 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;

บูลีนสาธารณะ getUnknownRank () 

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

บูลีนสุดท้ายสาธารณะ isInitialized ()

TensorShapeProto.Builder สาธารณะ ผสานจาก (com.google.protobuf.CodedInputStream อินพุต com.google.protobuf.ExtensionRegistryLite extensionRegistry)

ขว้าง
IOข้อยกเว้น

สาธารณะ TensorShapeProto.Builder ผสานจาก (com.google.protobuf.Message อื่น ๆ )

TensorShapeProto.Builder สาธารณะขั้นสุดท้าย ผสาน UnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

สาธารณะ TensorShapeProto.Builder RemoveDim (ดัชนี 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;

สาธารณะ TensorShapeProto.Builder setDim (ดัชนี int, ค่า 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;

สาธารณะ TensorShapeProto.Builder setDim (ดัชนี 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;

สาธารณะ TensorShapeProto.Builder setField (com.google.protobuf.Descriptors.FieldDescriptor ฟิลด์ ค่าอ็อบเจ็กต์)

สาธารณะ TensorShapeProto.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ฟิลด์ ดัชนี int ค่าอ็อบเจ็กต์)

TensorShapeProto.Builder สุดท้ายสาธารณะ setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

สาธารณะ TensorShapeProto.Builder setUnknownRank (ค่าบูลีน) 

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