TensorProtoOrBuilder

interfaz pública TensorProtoOrBuilder
Subclases indirectas conocidas

Métodos públicos

booleano abstracto
getBoolVal (índice int)
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
resumen entero
obtenerBoolValCount ()
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
Lista abstracta<Booleano>
obtenerBoolValList ()
 DT_BOOL
repeated bool bool_val = 11 [packed = true];
doble abstracto
getDcomplexVal (índice int)
 DT_COMPLEX128.
resumen entero
getDcomplexValCount ()
 DT_COMPLEX128.
Lista abstracta<Doble>
getDcomplexValList ()
 DT_COMPLEX128.
doble abstracto
getDoubleVal (índice int)
 DT_DOUBLE.
resumen entero
getDoubleValCount ()
 DT_DOUBLE.
Lista abstracta<Doble>
obtenerListaDobleVal ()
 DT_DOUBLE.
tipo de datos abstracto
obtener tipo D ()
.tensorflow.DataType dtype = 1;
resumen entero
getDtypeValue ()
.tensorflow.DataType dtype = 1;
flotador abstracto
getFloatVal (índice int)
 DT_FLOAT.
resumen entero
obtenerFloatValCount ()
 DT_FLOAT.
Lista abstracta<Flotante>
obtenerFloatValList ()
 DT_FLOAT.
resumen entero
getHalfVal (índice int)
 DT_HALF, DT_BFLOAT16.
resumen entero
obtenerHalfValCount ()
 DT_HALF, DT_BFLOAT16.
Lista abstracta<Entero>
obtenerHalfValList ()
 DT_HALF, DT_BFLOAT16.
abstracto largo
getInt64Val (índice int)
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
resumen entero
getInt64ValCount ()
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
Lista abstracta<Larga>
getInt64ValList ()
 DT_INT64
repeated int64 int64_val = 10 [packed = true];
resumen entero
getIntVal (índice int)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
resumen entero
obtenerIntValCount ()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
Lista abstracta<Entero>
obtenerListaIntVal ()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
resumen ResourceHandleProto
getResourceHandleVal (índice int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
resumen entero
getResourceHandleValCount ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
Lista abstracta < ResourceHandleProto >
getResourceHandleValList ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
resumen ResourceHandleProtoOrBuilder
getResourceHandleValOrBuilder (índice int)
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
Lista abstracta<? extiende ResourceHandleProtoOrBuilder >
getResourceHandleValOrBuilderList ()
 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
flotador abstracto
getScomplexVal (índice int)
 DT_COMPLEX64.
resumen entero
getScomplexValCount ()
 DT_COMPLEX64.
Lista abstracta<Flotante>
getScomplexValList ()
 DT_COMPLEX64.
resumen com.google.protobuf.ByteString
getStringVal (índice int)
 DT_STRING
repeated bytes string_val = 8;
resumen entero
getStringValCount ()
 DT_STRING
repeated bytes string_val = 8;
Lista abstracta<ByteString>
obtenerStringValList ()
 DT_STRING
repeated bytes string_val = 8;
resumen com.google.protobuf.ByteString
obtenerTensorContenido ()
 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
resumen TensorShapeProto
obtener forma tensor ()
 Shape of the tensor.
abstracto TensorShapeProtoOrBuilder
getTensorShapeOrBuilder ()
 Shape of the tensor.
resumen entero
getUint32Val (índice int)
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
resumen entero
getUint32ValCount ()
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
Lista abstracta<Entero>
getUint32ValList ()
 DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
abstracto largo
getUint64Val (índice int)
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
resumen entero
getUint64ValCount ()
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
Lista abstracta<Larga>
getUint64ValList ()
 DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
abstracto VariantTensorDataProto
getVariantVal (índice int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
resumen entero
getVariantValCount ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Lista abstracta <VariantTensorDataProto>
getVariantValList ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Variante abstractaTensorDataProtoOrBuilder
getVariantValOrBuilder (índice int)
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
Lista abstracta<? extiende VariantTensorDataProtoOrBuilder >
getVariantValOrBuilderList ()
 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
resumen entero
obtener número de versión ()
 Version number.
booleano abstracto
tieneTensorShape ()
 Shape of the tensor.

Métodos públicos

getBoolVal booleano abstracto público (índice int) 

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

resumen público int getBoolValCount () 

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

Lista abstracta pública<Boolean> getBoolValList () 

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

resumen público doble getDcomplexVal (índice 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];

resumen público int 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];

Lista abstracta pública <Doble> 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];

doble abstracto público getDoubleVal (índice int) 

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

resumen público int getDoubleValCount () 

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

Lista abstracta pública <Doble> getDoubleValList () 

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

Tipo de datos abstracto público getDtype ()

.tensorflow.DataType dtype = 1;

resumen público int getDtypeValue ()

.tensorflow.DataType dtype = 1;

flotante abstracto público getFloatVal (índice int) 

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

resumen público int getFloatValCount () 

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

Lista abstracta pública<Float> getFloatValList () 

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

resumen público int getHalfVal (índice 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];

resumen público int 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];

Lista abstracta pública<Integer> 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];

resumen público largo getInt64Val (índice int) 

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

resumen público int getInt64ValCount () 

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

Lista abstracta pública<Long> getInt64ValList () 

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

resumen público int getIntVal (índice int) 

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

resumen público int getIntValCount () 

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

Lista abstracta pública<Integer> getIntValList () 

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

resumen público ResourceHandleProto getResourceHandleVal (índice int) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

resumen público int getResourceHandleValCount () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

Lista abstracta pública < ResourceHandleProto > getResourceHandleValList () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

resumen público ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder (índice int) 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

Lista de resúmenes públicos <? extiende ResourceHandleProtoOrBuilder > getResourceHandleValOrBuilderList () 

 DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

flotante abstracto público getScomplexVal (índice 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];

resumen público int 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];

Lista abstracta pública<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];

resumen público com.google.protobuf.ByteString getStringVal (índice int) 

 DT_STRING
repeated bytes string_val = 8;

resumen público int getStringValCount () 

 DT_STRING
repeated bytes string_val = 8;

Lista abstracta pública <ByteString> getStringValList () 

 DT_STRING
repeated bytes string_val = 8;

resumen público com.google.protobuf.ByteString 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;

resumen público TensorShapeProto getTensorShape () 

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

resumen público TensorShapeProtoOrBuilder getTensorShapeOrBuilder () 

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

resumen público int getUint32Val (índice int) 

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

resumen público int getUint32ValCount () 

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

Lista abstracta pública <Integer> getUint32ValList () 

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

resumen público largo getUint64Val (índice int) 

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

resumen público int getUint64ValCount () 

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

Lista abstracta pública<Long> getUint64ValList () 

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

resumen público VariantTensorDataProto getVariantVal (índice int) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

resumen público int getVariantValCount () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

Lista abstracta pública< VariantTensorDataProto > getVariantValList () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

resumen público VariantTensorDataProtoOrBuilder getVariantValOrBuilder (índice int) 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

Lista de resúmenes públicos <? extiende VariantTensorDataProtoOrBuilder > getVariantValOrBuilderList () 

 DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

resumen público int 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;

hasTensorShape booleano abstracto público () 

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