public interface NamedTensorProtoOrBuilder
extends org.nd4j.shade.protobuf.MessageOrBuilder
Modifier and Type | Method and Description |
---|---|
String |
getName()
Name of the tensor.
|
org.nd4j.shade.protobuf.ByteString |
getNameBytes()
Name of the tensor.
|
TensorProto |
getTensor()
The client can populate a TensorProto using a tensorflow::Tensor`, or
directly using the protobuf field accessors.
|
TensorProtoOrBuilder |
getTensorOrBuilder()
The client can populate a TensorProto using a tensorflow::Tensor`, or
directly using the protobuf field accessors.
|
boolean |
hasTensor()
The client can populate a TensorProto using a tensorflow::Tensor`, or
directly using the protobuf field accessors.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
String getName()
Name of the tensor.
string name = 1;
org.nd4j.shade.protobuf.ByteString getNameBytes()
Name of the tensor.
string name = 1;
boolean 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;
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;
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;
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