TensorProto.Builder

TensorProto.Builder kelas akhir statis publik

 Protocol buffer representing a tensor.
Protobuf tipe tensorflow.TensorProto

Metode Publik

TensorProto.Builder
addAllBoolVal (Nilai Iterable<? extends Boolean>)
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
TensorProto.Builder
addAllDcomplexVal (Nilai Iterable<? extends Double>)
 DT_COMPLEX128.
TensorProto.Builder
addAllDoubleVal (Nilai Iterable<? extends Double>)
 DT_DOUBLE.
TensorProto.Builder
addAllFloatVal (nilai Iterable<? extends Float>)
 DT_FLOAT.
TensorProto.Builder
addAllHalfVal (Nilai Iterable<? extends Integer>)
 DT_HALF, DT_BFLOAT16.
TensorProto.Builder
addAllInt64Val (nilai Iterable<? extends Long>)
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
TensorProto.Builder
addAllIntVal (Nilai Iterable<? extends Integer>)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
TensorProto.Builder
addAllResourceHandleVal (Nilai Iterable<? extends ResourceHandleProto >)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
addAllScomplexVal (nilai Iterable<? extends Float>)
 DT_COMPLEX64.
TensorProto.Builder
addAllStringVal (nilai Iterable<? extends ByteString>)
 DT_STRING
repeated bytes string_val = 8;
TensorProto.Builder
addAllUint32Val (nilai Iterable<? extends Integer>)
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
TensorProto.Builder
addAllUint64Val (nilai Iterable<? extends Long>)
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
TensorProto.Builder
addAllVariantVal (Nilai Iterable<? extends VariantTensorDataProto >)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
addBoolVal (nilai boolean)
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
TensorProto.Builder
addDcomplexVal (nilai ganda)
 DT_COMPLEX128.
TensorProto.Builder
addDoubleVal (nilai ganda)
 DT_DOUBLE.
TensorProto.Builder
addFloatVal (nilai mengambang)
 DT_FLOAT.
TensorProto.Builder
addHalfVal (nilai int)
 DT_HALF, DT_BFLOAT16.
TensorProto.Builder
addInt64Val (nilai panjang)
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
TensorProto.Builder
addIntVal (nilai int)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
TensorProto.Builder
addRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)
TensorProto.Builder
addResourceHandleVal (indeks int, ResourceHandleProto.Builder builderForValue)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
addResourceHandleVal (indeks int, nilai ResourceHandleProto )
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
addResourceHandleVal (nilai ResourceHandleProto )
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
addResourceHandleVal ( ResourceHandleProto.Pembuat pembangunForValue)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProto.Builder
addResourceHandleValBuilder (indeks int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProto.Builder
addResourceHandleValBuilder ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
addScomplexVal (nilai mengambang)
 DT_COMPLEX64.
TensorProto.Builder
addStringVal (nilai com.google.protobuf.ByteString)
 DT_STRING
repeated bytes string_val = 8;
TensorProto.Builder
addUint32Val (nilai int)
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
TensorProto.Builder
addUint64Val (nilai panjang)
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
TensorProto.Builder
addVariantVal (nilai VariantTensorDataProto )
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
addVariantVal (indeks int, VariantTensorDataProto.Builder builderForValue)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
addVariantVal (indeks int, nilai VariantTensorDataProto )
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
addVariantVal ( VariantTensorDataProto.Pembuat pembangunForValue)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProto.Builder
addVariantValBuilder (indeks int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProto.Builder
tambahkanVariantValBuilder ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto
membangun ()
TensorProto
membangunPartial ()
TensorProto.Builder
jernih ()
TensorProto.Builder
jelasBoolVal ()
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
TensorProto.Builder
jelasDcomplexVal ()
 DT_COMPLEX128.
TensorProto.Builder
jelasDoubleVal ()
 DT_DOUBLE.
TensorProto.Builder
hapusDtype ()
.tensorflow.DataType dtype = 1;
TensorProto.Builder
clearField (bidang com.google.protobuf.Descriptors.FieldDescriptor)
TensorProto.Builder
jelasFloatVal ()
 DT_FLOAT.
TensorProto.Builder
jelasHalfVal ()
 DT_HALF, DT_BFLOAT16.
TensorProto.Builder
jelasInt64Val ()
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
TensorProto.Builder
jelasIntVal ()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
TensorProto.Builder
clearOneof (com.google.protobuf.Descriptors.OneofDescriptor salah satu)
TensorProto.Builder
jelasResourceHandleVal ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
jelasScomplexVal ()
 DT_COMPLEX64.
TensorProto.Builder
hapusStringVal ()
 DT_STRING
repeated bytes string_val = 8;
TensorProto.Builder
hapus Konten Tensor ()
 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
TensorProto.Builder
jelasTensorBentuk ()
 Shape of the tensor.
TensorProto.Builder
hapusUint32Val ()
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
TensorProto.Builder
hapusUint64Val ()
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
TensorProto.Builder
hapusVariantVal ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
hapusVersionNumber ()
 Version number.
TensorProto.Builder
klon ()
boolean
getBoolVal (indeks int)
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
ke dalam
dapatkanBoolValCount ()
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
Daftar<Boolean>
dapatkanBoolValList ()
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
dobel
getDcomplexVal (indeks int)
 DT_COMPLEX128.
ke dalam
dapatkanDcomplexValCount ()
 DT_COMPLEX128.
Daftar<Ganda>
dapatkanDcomplexValList ()
 DT_COMPLEX128.
TensorProto
dapatkanDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor statis terakhir
dapatkanDescriptor ()
com.google.protobuf.Descriptors.Descriptor
dapatkanDescriptorForType ()
dobel
getDoubleVal (indeks int)
 DT_DOUBLE.
ke dalam
dapatkanDoubleValCount ()
 DT_DOUBLE.
Daftar<Ganda>
dapatkanDoubleValList ()
 DT_DOUBLE.
Tipe data
dapatkan tipe D ()
.tensorflow.DataType dtype = 1;
ke dalam
dapatkanDtypeValue ()
.tensorflow.DataType dtype = 1;
mengambang
getFloatVal (indeks int)
 DT_FLOAT.
ke dalam
dapatkanFloatValCount ()
 DT_FLOAT.
Daftar<Mengambang>
dapatkanFloatValList ()
 DT_FLOAT.
ke dalam
getHalfVal (indeks int)
 DT_HALF, DT_BFLOAT16.
ke dalam
dapatkanHalfValCount ()
 DT_HALF, DT_BFLOAT16.
Daftar<Bilangan Bulat>
dapatkanHalfValList ()
 DT_HALF, DT_BFLOAT16.
panjang
getInt64Val (indeks int)
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
ke dalam
dapatkanInt64ValCount ()
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
Daftar<Panjang>
dapatkanInt64ValList ()
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
ke dalam
getIntVal (indeks int)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
ke dalam
dapatkanIntValCount ()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
Daftar<Bilangan Bulat>
dapatkanIntValList ()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
ResourceHandleProto
getResourceHandleVal (indeks int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProto.Builder
getResourceHandleValBuilder (indeks int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
Daftar< ResourceHandleProto.Builder >
getResourceHandleValBuilderList ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ke dalam
dapatkanResourceHandleValCount ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
Daftar< ResourceHandleProto >
dapatkanResourceHandleValList ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProtoOrBuilder
getResourceHandleValOrBuilder (indeks int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
Daftar<? memperluas ResourceHandleProtoOrBuilder >
getResourceHandleValOrBuilderList ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
mengambang
getScomplexVal (indeks int)
 DT_COMPLEX64.
ke dalam
dapatkanScomplexValCount ()
 DT_COMPLEX64.
Daftar<Mengambang>
dapatkanScomplexValList ()
 DT_COMPLEX64.
com.google.protobuf.ByteString
getStringVal (indeks int)
 DT_STRING
repeated bytes string_val = 8;
ke dalam
dapatkanStringValCount ()
 DT_STRING
repeated bytes string_val = 8;
Daftar<ByteString>
dapatkanStringValList ()
 DT_STRING
repeated bytes string_val = 8;
com.google.protobuf.ByteString
dapatkanTensorContent ()
 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
TensorBentukProto
dapatkanTensorBentuk ()
 Shape of the tensor.
TensorShapeProto.Builder
dapatkanTensorShapeBuilder ()
 Shape of the tensor.
TensorShapeProtoOrBuilder
dapatkanTensorShapeOrBuilder ()
 Shape of the tensor.
ke dalam
getUint32Val (indeks int)
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
ke dalam
dapatkanUint32ValCount ()
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
Daftar<Bilangan Bulat>
dapatkanUint32ValList ()
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
panjang
getUint64Val (indeks int)
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
ke dalam
dapatkanUint64ValCount ()
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
Daftar<Panjang>
dapatkanUint64ValList ()
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
VarianTensorDataProto
getVariantVal (indeks int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProto.Builder
getVariantValBuilder (indeks int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Daftar< VariantTensorDataProto.Builder >
dapatkanVariantValBuilderList ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
ke dalam
dapatkanVariantValCount ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Daftar< VariantTensorDataProto >
dapatkanVariantValList ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProtoOrBuilder
getVariantValOrBuilder (indeks int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Daftar<? memperluas VariantTensorDataProtoOrBuilder >
dapatkanVariantValOrBuilderList ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
ke dalam
dapatkanVersionNumber ()
 Version number.
boolean
hasTensorShape ()
 Shape of the tensor.
boolean terakhir
diinisialisasi ()
TensorProto.Builder
mergeFrom (com.google.protobuf.Pesan lainnya)
TensorProto.Builder
mergeFrom (com.google.protobuf.CodedInputStream masukan, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
TensorProto.Builder
mergeTensorShape (nilai TensorShapeProto )
 Shape of the tensor.
TensorProto.Builder terakhir
mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
TensorProto.Builder
hapusResourceHandleVal (indeks int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
hapusVariantVal (indeks int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
setBoolVal (indeks int, nilai boolean)
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
TensorProto.Builder
setDcomplexVal (indeks int, nilai ganda)
 DT_COMPLEX128.
TensorProto.Builder
setDoubleVal (indeks int, nilai ganda)
 DT_DOUBLE.
TensorProto.Builder
setDtype (nilai Tipe Data )
.tensorflow.DataType dtype = 1;
TensorProto.Builder
setDtypeValue (nilai int)
.tensorflow.DataType dtype = 1;
TensorProto.Builder
setField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)
TensorProto.Builder
setFloatVal (indeks int, nilai float)
 DT_FLOAT.
TensorProto.Builder
setHalfVal (indeks int, nilai int)
 DT_HALF, DT_BFLOAT16.
TensorProto.Builder
setInt64Val (indeks int, nilai panjang)
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
TensorProto.Builder
setIntVal (indeks int, nilai int)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
TensorProto.Builder
setRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, indeks int, Nilai objek)
TensorProto.Builder
setResourceHandleVal (indeks int, ResourceHandleProto.Builder builderForValue)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
setResourceHandleVal (indeks int, nilai ResourceHandleProto )
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
TensorProto.Builder
setScomplexVal (indeks int, nilai float)
 DT_COMPLEX64.
TensorProto.Builder
setStringVal (indeks int, nilai com.google.protobuf.ByteString)
 DT_STRING
repeated bytes string_val = 8;
TensorProto.Builder
setTensorContent (nilai com.google.protobuf.ByteString)
 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
TensorProto.Builder
setTensorShape (nilai TensorShapeProto )
 Shape of the tensor.
TensorProto.Builder
setTensorShape ( TensorShapeProto.Pembuat pembangunForValue)
 Shape of the tensor.
TensorProto.Builder
setUint32Val (indeks int, nilai int)
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
TensorProto.Builder
setUint64Val (indeks int, nilai panjang)
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
TensorProto.Builder terakhir
setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
TensorProto.Builder
setVariantVal (indeks int, nilai VariantTensorDataProto )
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
setVariantVal (indeks int, VariantTensorDataProto.Builder builderForValue)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
TensorProto.Builder
setVersionNumber (nilai int)
 Version number.

Metode Warisan

Metode Publik

public TensorProto.Builder addAllBoolVal (nilai Iterable<? extends Boolean>) 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

public TensorProto.Builder addAllDcomplexVal (nilai Iterable<? extends Double>) 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

public TensorProto.Builder addAllDoubleVal (nilai Iterable<? extends Double>) 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

public TensorProto.Builder addAllFloatVal (nilai Iterable<? extends Float>) 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

public TensorProto.Builder addAllHalfVal (nilai Iterable<? extends Integer>) 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

public TensorProto.Builder addAllInt64Val (nilai Iterable<? extends Long>) 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

public TensorProto.Builder addAllIntVal (nilai Iterable<? extends Integer>) 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

public TensorProto.Builder addAllResourceHandleVal (Nilai Iterable<? extends ResourceHandleProto >) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public TensorProto.Builder addAllScomplexVal (nilai Iterable<? extends Float>) 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

public TensorProto.Builder addAllStringVal (nilai Iterable<? extends ByteString>) 

 DT_STRING
repeated bytes string_val = 8;

public TensorProto.Builder addAllUint32Val (nilai Iterable<? extends Integer>) 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

public TensorProto.Builder addAllUint64Val (nilai Iterable<? extends Long>) 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

public TensorProto.Builder addAllVariantVal (Nilai Iterable<? extends VariantTensorDataProto >) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder addBoolVal publik (nilai boolean) 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

public TensorProto.Builder addDcomplexVal (nilai ganda) 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

public TensorProto.Builder addDoubleVal (nilai ganda) 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

TensorProto.Builder addFloatVal publik (nilai float) 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

TensorProto.Builder publik addHalfVal (nilai int) 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

public TensorProto.Builder addInt64Val (nilai panjang) 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

TensorProto.Builder addIntVal publik (nilai int) 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

public TensorProto.Builder addRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)

TensorProto.Builder addResourceHandleVal publik (int indeks, ResourceHandleProto.Builder builderForValue) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik addResourceHandleVal (indeks int, nilai ResourceHandleProto ) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik addResourceHandleVal (nilai ResourceHandleProto ) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder addResourceHandleVal publik ( ResourceHandleProto.Builder builderForValue) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

ResourceHandleProto.Builder publik addResourceHandleValBuilder (int indeks) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

ResourceHandleProto.Builder publik addResourceHandleValBuilder () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik addScomplexVal (nilai float) 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

TensorProto.Builder addStringVal publik (nilai com.google.protobuf.ByteString) 

 DT_STRING
repeated bytes string_val = 8;

TensorProto.Builder addUint32Val publik (nilai int) 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

public TensorProto.Builder addUint64Val (nilai panjang) 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

TensorProto.Builder addVariantVal publik (nilai VariantTensorDataProto ) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder addVariantVal publik (indeks int, VariantTensorDataProto.Builder builderForValue) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder addVariantVal publik (indeks int, nilai VariantTensorDataProto ) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder addVariantVal publik ( VariantTensorDataProto.Builder builderForValue) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

VariantTensorDataProto.Builder publik addVariantValBuilder (int indeks) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

VariantTensorDataProto.Builder publik addVariantValBuilder () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

pembuatan TensorProto publik ()

Tensor publikProto buildPartial ()

TensorProto.Builder publik jelas ()

TensorProto.Builder publik clearBoolVal () 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

TensorProto.Builder publik clearDcomplexVal () 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

TensorProto.Builder publik clearDoubleVal () 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

TensorProto.Builder publik clearDtype ()

.tensorflow.DataType dtype = 1;

TensorProto.Builder clearField publik (bidang com.google.protobuf.Descriptors.FieldDescriptor)

TensorProto.Builder publik clearFloatVal () 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

TensorProto.Builder publik clearHalfVal () 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

TensorProto.Builder publik clearInt64Val () 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

TensorProto.Builder publik clearIntVal () 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

TensorProto.Builder publik clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

TensorProto.Builder publik clearResourceHandleVal () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik clearScomplexVal () 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

TensorProto.Builder publik clearStringVal () 

 DT_STRING
repeated bytes string_val = 8;

TensorProto.Builder publik clearTensorContent () 

 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
 can be used for all tensor types. The purpose of this representation is to
 reduce serialization overhead during RPC call by avoiding serialization of
 many repeated small items.
bytes tensor_content = 4;

TensorProto.Builder publik clearTensorShape () 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorProto.Builder publik clearUint32Val () 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

TensorProto.Builder publik clearUint64Val () 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

TensorProto.Builder publik clearVariantVal () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder publik clearVersionNumber () 

 Version number.
 In version 0, if the "repeated xxx" representations contain only one
 element, that element is repeated to fill the shape.  This makes it easy
 to represent a constant Tensor with a single value.
int32 version_number = 3;

klon TensorProto.Builder publik ()

getBoolVal boolean publik (indeks int) 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

int publik getBoolValCount () 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

Daftar publik<Boolean> getBoolValList () 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

getDcomplexVal ganda publik (indeks int) 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

int publik getDcomplexValCount () 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

Daftar publik<Double> getDcomplexValList () 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

TensorProto publik getDefaultInstanceForType ()

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

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

getDoubleVal ganda publik (indeks int) 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

int publik getDoubleValCount () 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

Daftar publik<Double> getDoubleValList () 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

Tipe Data publik getDtype ()

.tensorflow.DataType dtype = 1;

int publik getDtypeValue ()

.tensorflow.DataType dtype = 1;

getFloatVal float publik (indeks int) 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

int publik getFloatValCount () 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

Daftar publik<Float> getFloatValList () 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

publik int getHalfVal (indeks int) 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

int publik getHalfValCount () 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

Daftar publik<Bilangan Bulat> getHalfValList () 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

getInt64Val panjang publik (indeks int) 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

int publik getInt64ValCount () 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

Daftar publik<Panjang> getInt64ValList () 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

publik int getIntVal (indeks int) 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

int publik getIntValCount () 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

Daftar publik<Bilangan Bulat> getIntValList () 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

ResourceHandleProto publik getResourceHandleVal (int indeks) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

ResourceHandleProto.Builder publik getResourceHandleValBuilder (int indeks) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

Daftar publik< ResourceHandleProto.Builder > getResourceHandleValBuilderList () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

int publik getResourceHandleValCount () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

Daftar publik< ResourceHandleProto > getResourceHandleValList () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

ResourceHandleProtoOrBuilder publik getResourceHandleValOrBuilder (int indeks) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

Daftar Publik<? memperluas ResourceHandleProtoOrBuilder > getResourceHandleValOrBuilderList () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public float getScomplexVal (indeks int) 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

int publik getScomplexValCount () 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

Daftar publik<Float> getScomplexValList () 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

com.google.protobuf.ByteString getStringVal publik (indeks int) 

 DT_STRING
repeated bytes string_val = 8;

int publik getStringValCount () 

 DT_STRING
repeated bytes string_val = 8;

Daftar publik<ByteString> getStringValList () 

 DT_STRING
repeated bytes string_val = 8;

com.google.protobuf.ByteString publik getTensorContent () 

 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
 can be used for all tensor types. The purpose of this representation is to
 reduce serialization overhead during RPC call by avoiding serialization of
 many repeated small items.
bytes tensor_content = 4;

TensorShapeProto publik untuk mendapatkanTensorShape () 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorShapeProto.Builder publik getTensorShapeBuilder () 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorShapeProtoOrBuilder publik getTensorShapeOrBuilder () 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

publik int getUint32Val (indeks int) 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

int publik getUint32ValCount () 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

Daftar publik<Bilangan Bulat> getUint32ValList () 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

getUint64Val panjang publik (indeks int) 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

publik int getUint64ValCount () 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

Daftar publik<Panjang> getUint64ValList () 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

VariantTensorDataProto getVariantVal publik (indeks int) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

VariantTensorDataProto.Builder publik getVariantValBuilder (indeks int) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

daftar publik< VariantTensorDataProto.Builder > getVariantValBuilderList () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

int publik getVariantValCount () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

Daftar publik< VariantTensorDataProto > getVariantValList () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

VariantTensorDataProtoOrBuilder publik getVariantValOrBuilder (int indeks) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

Daftar Publik<? memperluas VariantTensorDataProtoOrBuilder > getVariantValOrBuilderList () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

int publik getVersionNumber () 

 Version number.
 In version 0, if the "repeated xxx" representations contain only one
 element, that element is repeated to fill the shape.  This makes it easy
 to represent a constant Tensor with a single value.
int32 version_number = 3;

boolean publik hasTensorShape () 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

boolean akhir publik diinisialisasi ()

TensorProto.Builder mergeFrom publik (com.google.protobuf.Pesan lainnya)

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

Melempar
Pengecualian IO

TensorProto.Builder mergeTensorShape publik (nilai TensorShapeProto ) 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorProto.Builder final publik menggabungkanUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)

TensorProto.Builder publik deleteResourceHandleVal (int indeks) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik menghapusVariantVal (int indeks) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder setBoolVal publik (indeks int, nilai boolean) 

 DT_BOOL
repeated bool bool_val = 11 [packed = true];

TensorProto.Builder setDcomplexVal publik (indeks int, nilai ganda) 

 DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
 and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];

TensorProto.Builder setDoubleVal publik (indeks int, nilai ganda) 

 DT_DOUBLE.
repeated double double_val = 6 [packed = true];

TensorProto.Builder setDtype publik (nilai Tipe Data )

.tensorflow.DataType dtype = 1;

TensorProto.Builder setDtypeValue publik (nilai int)

.tensorflow.DataType dtype = 1;

public TensorProto.Builder setField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)

TensorProto.Builder setFloatVal publik (indeks int, nilai float) 

 DT_FLOAT.
repeated float float_val = 5 [packed = true];

TensorProto.Builder setHalfVal publik (indeks int, nilai int) 

 DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
 have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];

public TensorProto.Builder setInt64Val (indeks int, nilai panjang) 

 DT_INT64
repeated int64 int64_val = 10 [packed = true];

TensorProto.Builder publik setIntVal (indeks int, nilai int) 

 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];

public TensorProto.Builder setRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, indeks int, Nilai objek)

TensorProto.Builder setResourceHandleVal publik (indeks int, ResourceHandleProto.Builder builderForValue) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder publik setResourceHandleVal (indeks int, nilai ResourceHandleProto ) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

TensorProto.Builder setScomplexVal publik (indeks int, nilai float) 

 DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
 and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];

TensorProto.Builder setStringVal publik (indeks int, nilai com.google.protobuf.ByteString) 

 DT_STRING
repeated bytes string_val = 8;

TensorProto.Builder setTensorContent publik (nilai com.google.protobuf.ByteString) 

 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
 can be used for all tensor types. The purpose of this representation is to
 reduce serialization overhead during RPC call by avoiding serialization of
 many repeated small items.
bytes tensor_content = 4;

TensorProto.Builder setTensorShape publik (nilai TensorShapeProto ) 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorProto.Builder setTensorShape publik ( TensorShapeProto.Builder builderForValue) 

 Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;

TensorProto.Builder publik setUint32Val (indeks int, nilai int) 

 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];

public TensorProto.Builder setUint64Val (indeks int, nilai panjang) 

 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];

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

TensorProto.Builder setVariantVal publik (indeks int, nilai VariantTensorDataProto ) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder setVariantVal publik (indeks int, VariantTensorDataProto.Builder builderForValue) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

TensorProto.Builder setVersionNumber publik (nilai int) 

 Version number.
 In version 0, if the "repeated xxx" representations contain only one
 element, that element is repeated to fill the shape.  This makes it easy
 to represent a constant Tensor with a single value.
int32 version_number = 3;