org.tensorflow.framework.TensorProtoOrBuilder Maven / Gradle / Ivy
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/framework/tensor.proto
package org.tensorflow.framework;
public interface TensorProtoOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.TensorProto)
com.github.os72.protobuf351.MessageOrBuilder {
/**
* .tensorflow.DataType dtype = 1;
*/
int getDtypeValue();
/**
* .tensorflow.DataType dtype = 1;
*/
org.tensorflow.framework.DataType getDtype();
/**
*
* Shape of the tensor. TODO(touts): sort out the 0-rank issues.
*
*
* .tensorflow.TensorShapeProto tensor_shape = 2;
*/
boolean hasTensorShape();
/**
*
* Shape of the tensor. TODO(touts): sort out the 0-rank issues.
*
*
* .tensorflow.TensorShapeProto tensor_shape = 2;
*/
org.tensorflow.framework.TensorShapeProto getTensorShape();
/**
*
* Shape of the tensor. TODO(touts): sort out the 0-rank issues.
*
*
* .tensorflow.TensorShapeProto tensor_shape = 2;
*/
org.tensorflow.framework.TensorShapeProtoOrBuilder getTensorShapeOrBuilder();
/**
*
* 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;
*/
int getVersionNumber();
/**
*
* 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;
*/
com.github.os72.protobuf351.ByteString getTensorContent();
/**
*
* 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];
*/
java.util.List 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];
*/
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];
*/
int getHalfVal(int index);
/**
*
* DT_FLOAT.
*
*
* repeated float float_val = 5 [packed = true];
*/
java.util.List getFloatValList();
/**
*
* DT_FLOAT.
*
*
* repeated float float_val = 5 [packed = true];
*/
int getFloatValCount();
/**
*
* DT_FLOAT.
*
*
* repeated float float_val = 5 [packed = true];
*/
float getFloatVal(int index);
/**
*
* DT_DOUBLE.
*
*
* repeated double double_val = 6 [packed = true];
*/
java.util.List getDoubleValList();
/**
*
* DT_DOUBLE.
*
*
* repeated double double_val = 6 [packed = true];
*/
int getDoubleValCount();
/**
*
* DT_DOUBLE.
*
*
* repeated double double_val = 6 [packed = true];
*/
double getDoubleVal(int index);
/**
*
* DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
*
*
* repeated int32 int_val = 7 [packed = true];
*/
java.util.List getIntValList();
/**
*
* DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
*
*
* repeated int32 int_val = 7 [packed = true];
*/
int getIntValCount();
/**
*
* DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
*
*
* repeated int32 int_val = 7 [packed = true];
*/
int getIntVal(int index);
/**
*
* DT_STRING
*
*
* repeated bytes string_val = 8;
*/
java.util.List getStringValList();
/**
*
* DT_STRING
*
*
* repeated bytes string_val = 8;
*/
int getStringValCount();
/**
*
* DT_STRING
*
*
* repeated bytes string_val = 8;
*/
com.github.os72.protobuf351.ByteString getStringVal(int index);
/**
*
* 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];
*/
java.util.List 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];
*/
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];
*/
float getScomplexVal(int index);
/**
*
* DT_INT64
*
*
* repeated int64 int64_val = 10 [packed = true];
*/
java.util.List getInt64ValList();
/**
*
* DT_INT64
*
*
* repeated int64 int64_val = 10 [packed = true];
*/
int getInt64ValCount();
/**
*
* DT_INT64
*
*
* repeated int64 int64_val = 10 [packed = true];
*/
long getInt64Val(int index);
/**
*
* DT_BOOL
*
*
* repeated bool bool_val = 11 [packed = true];
*/
java.util.List getBoolValList();
/**
*
* DT_BOOL
*
*
* repeated bool bool_val = 11 [packed = true];
*/
int getBoolValCount();
/**
*
* DT_BOOL
*
*
* repeated bool bool_val = 11 [packed = true];
*/
boolean getBoolVal(int index);
/**
*
* 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];
*/
java.util.List 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];
*/
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];
*/
double getDcomplexVal(int index);
/**
*
* DT_RESOURCE
*
*
* repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
*/
java.util.List
getResourceHandleValList();
/**
*
* DT_RESOURCE
*
*
* repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
*/
org.tensorflow.framework.ResourceHandleProto getResourceHandleVal(int index);
/**
*
* DT_RESOURCE
*
*
* repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
*/
int getResourceHandleValCount();
/**
*
* DT_RESOURCE
*
*
* repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
*/
java.util.List
getResourceHandleValOrBuilderList();
/**
*
* DT_RESOURCE
*
*
* repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
*/
org.tensorflow.framework.ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder(
int index);
/**
*
* DT_VARIANT
*
*
* repeated .tensorflow.VariantTensorDataProto variant_val = 15;
*/
java.util.List
getVariantValList();
/**
*
* DT_VARIANT
*
*
* repeated .tensorflow.VariantTensorDataProto variant_val = 15;
*/
org.tensorflow.framework.VariantTensorDataProto getVariantVal(int index);
/**
*
* DT_VARIANT
*
*
* repeated .tensorflow.VariantTensorDataProto variant_val = 15;
*/
int getVariantValCount();
/**
*
* DT_VARIANT
*
*
* repeated .tensorflow.VariantTensorDataProto variant_val = 15;
*/
java.util.List
getVariantValOrBuilderList();
/**
*
* DT_VARIANT
*
*
* repeated .tensorflow.VariantTensorDataProto variant_val = 15;
*/
org.tensorflow.framework.VariantTensorDataProtoOrBuilder getVariantValOrBuilder(
int index);
/**
*
* DT_UINT32
*
*
* repeated uint32 uint32_val = 16 [packed = true];
*/
java.util.List getUint32ValList();
/**
*
* DT_UINT32
*
*
* repeated uint32 uint32_val = 16 [packed = true];
*/
int getUint32ValCount();
/**
*
* DT_UINT32
*
*
* repeated uint32 uint32_val = 16 [packed = true];
*/
int getUint32Val(int index);
/**
*
* DT_UINT64
*
*
* repeated uint64 uint64_val = 17 [packed = true];
*/
java.util.List getUint64ValList();
/**
*
* DT_UINT64
*
*
* repeated uint64 uint64_val = 17 [packed = true];
*/
int getUint64ValCount();
/**
*
* DT_UINT64
*
*
* repeated uint64 uint64_val = 17 [packed = true];
*/
long getUint64Val(int index);
}