NamedTensorProtoOrBuilder

общедоступный интерфейс NamedTensorProtoOrBuilder
Известные косвенные подклассы

Публичные методы

абстрактная строка
получитьИмя ()
 Name of the tensor.
абстрактный com.google.protobuf.ByteString
getNameBytes ()
 Name of the tensor.
абстрактный TensorProto
получитьТензор ()
 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.
абстрактный TensorProtoOrBuilder
getTensorOrBuilder ()
 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.
абстрактное логическое значение
имеетТензор ()
 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.

Публичные методы

общедоступная абстрактная строка getName ()

 Name of the tensor.
 
string name = 1;

общедоступный абстрактный com.google.protobuf.ByteString getNameBytes ()

 Name of the tensor.
 
string name = 1;

публичный абстрактный TensorProto getTensor ()

 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.
 The client specifies whether the returned tensor values should be
 filled tensor fields (float_val, int_val, etc.) or encoded in a
 compact form in tensor.tensor_content.
 
.tensorflow.TensorProto tensor = 2;

публичный абстрактный TensorProtoOrBuilder getTensorOrBuilder ()

 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.
 The client specifies whether the returned tensor values should be
 filled tensor fields (float_val, int_val, etc.) or encoded in a
 compact form in tensor.tensor_content.
 
.tensorflow.TensorProto tensor = 2;

общедоступное абстрактное логическое значение hasTensor ()

 The client can populate a TensorProto using a tensorflow::Tensor`, or
 directly using the protobuf field accessors.
 The client specifies whether the returned tensor values should be
 filled tensor fields (float_val, int_val, etc.) or encoded in a
 compact form in tensor.tensor_content.
 
.tensorflow.TensorProto tensor = 2;