TensorProto

public final class TensorProto

 Protocol buffer representing a tensor.
 
Protobuf type tensorflow.TensorProto

Nested Classes

class TensorProto.Builder
 Protocol buffer representing a tensor. 

Constants

int BOOL_VAL_FIELD_NUMBER
int DCOMPLEX_VAL_FIELD_NUMBER
int DOUBLE_VAL_FIELD_NUMBER
int DTYPE_FIELD_NUMBER
int FLOAT_VAL_FIELD_NUMBER
int HALF_VAL_FIELD_NUMBER
int INT64_VAL_FIELD_NUMBER
int INT_VAL_FIELD_NUMBER
int RESOURCE_HANDLE_VAL_FIELD_NUMBER
int SCOMPLEX_VAL_FIELD_NUMBER
int STRING_VAL_FIELD_NUMBER
int TENSOR_CONTENT_FIELD_NUMBER
int TENSOR_SHAPE_FIELD_NUMBER
int UINT32_VAL_FIELD_NUMBER
int UINT64_VAL_FIELD_NUMBER
int VARIANT_VAL_FIELD_NUMBER
int VERSION_NUMBER_FIELD_NUMBER

Public Methods

boolean
equals(Object obj)
boolean
getBoolVal(int index)
 DT_BOOL
 
repeated bool bool_val = 11 [packed = true];
int
getBoolValCount()
 DT_BOOL
 
repeated bool bool_val = 11 [packed = true];
List<Boolean>
getBoolValList()
 DT_BOOL
 
repeated bool bool_val = 11 [packed = true];
double
getDcomplexVal(int index)
 DT_COMPLEX128.
int
getDcomplexValCount()
 DT_COMPLEX128.
List<Double>
getDcomplexValList()
 DT_COMPLEX128.
static TensorProto
TensorProto
final static com.google.protobuf.Descriptors.Descriptor
double
getDoubleVal(int index)
 DT_DOUBLE.
int
getDoubleValCount()
 DT_DOUBLE.
List<Double>
getDoubleValList()
 DT_DOUBLE.
DataType
getDtype()
.tensorflow.DataType dtype = 1;
int
getDtypeValue()
.tensorflow.DataType dtype = 1;
float
getFloatVal(int index)
 DT_FLOAT.
int
getFloatValCount()
 DT_FLOAT.
List<Float>
getFloatValList()
 DT_FLOAT.
int
getHalfVal(int index)
 DT_HALF, DT_BFLOAT16.
int
getHalfValCount()
 DT_HALF, DT_BFLOAT16.
List<Integer>
getHalfValList()
 DT_HALF, DT_BFLOAT16.
long
getInt64Val(int index)
 DT_INT64
 
repeated int64 int64_val = 10 [packed = true];
int
getInt64ValCount()
 DT_INT64
 
repeated int64 int64_val = 10 [packed = true];
List<Long>
getInt64ValList()
 DT_INT64
 
repeated int64 int64_val = 10 [packed = true];
int
getIntVal(int index)
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
int
getIntValCount()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
List<Integer>
getIntValList()
 DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
ResourceHandleProto
getResourceHandleVal(int index)
 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
int
getResourceHandleValCount()
 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
List<ResourceHandleProto>
getResourceHandleValList()
 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProtoOrBuilder
getResourceHandleValOrBuilder(int index)
 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
List<? extends ResourceHandleProtoOrBuilder>
getResourceHandleValOrBuilderList()
 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
float
getScomplexVal(int index)
 DT_COMPLEX64.
int
getScomplexValCount()
 DT_COMPLEX64.
List<Float>
getScomplexValList()
 DT_COMPLEX64.
int
com.google.protobuf.ByteString
getStringVal(int index)
 DT_STRING
 
repeated bytes string_val = 8;
int
getStringValCount()
 DT_STRING
 
repeated bytes string_val = 8;
List<ByteString>
getStringValList()
 DT_STRING
 
repeated bytes string_val = 8;
com.google.protobuf.ByteString
getTensorContent()
 Serialized raw tensor content from either Tensor::AsProtoTensorContent or
 memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
TensorShapeProto
getTensorShape()
 Shape of the tensor.
TensorShapeProtoOrBuilder
getTensorShapeOrBuilder()
 Shape of the tensor.
int
getUint32Val(int index)
 DT_UINT32
 
repeated uint32 uint32_val = 16 [packed = true];
int
getUint32ValCount()
 DT_UINT32
 
repeated uint32 uint32_val = 16 [packed = true];
List<Integer>
getUint32ValList()
 DT_UINT32
 
repeated uint32 uint32_val = 16 [packed = true];
long
getUint64Val(int index)
 DT_UINT64
 
repeated uint64 uint64_val = 17 [packed = true];
int
getUint64ValCount()
 DT_UINT64
 
repeated uint64 uint64_val = 17 [packed = true];
List<Long>
getUint64ValList()
 DT_UINT64
 
repeated uint64 uint64_val = 17 [packed = true];
final com.google.protobuf.UnknownFieldSet
VariantTensorDataProto
getVariantVal(int index)
 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
int
getVariantValCount()
 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
List<VariantTensorDataProto>
getVariantValList()
 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProtoOrBuilder
getVariantValOrBuilder(int index)
 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
List<? extends VariantTensorDataProtoOrBuilder>
getVariantValOrBuilderList()
 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
int
getVersionNumber()
 Version number.
boolean
hasTensorShape()
 Shape of the tensor.
int
final boolean
static TensorProto.Builder
static TensorProto.Builder
newBuilder(TensorProto prototype)
TensorProto.Builder
static TensorProto
parseDelimitedFrom(InputStream input)
static TensorProto
parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorProto
parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorProto
parseFrom(com.google.protobuf.CodedInputStream input)
static TensorProto
parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorProto
parseFrom(ByteBuffer data)
static TensorProto
parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorProto
parseFrom(com.google.protobuf.ByteString data)
static TensorProto
parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorProto
parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static
parser()
TensorProto.Builder
void
writeTo(com.google.protobuf.CodedOutputStream output)

Inherited Methods

Constants

public static final int BOOL_VAL_FIELD_NUMBER

Constant Value: 11

public static final int DCOMPLEX_VAL_FIELD_NUMBER

Constant Value: 12

public static final int DOUBLE_VAL_FIELD_NUMBER

Constant Value: 6

public static final int DTYPE_FIELD_NUMBER

Constant Value: 1

public static final int FLOAT_VAL_FIELD_NUMBER

Constant Value: 5

public static final int HALF_VAL_FIELD_NUMBER

Constant Value: 13

public static final int INT64_VAL_FIELD_NUMBER

Constant Value: 10

public static final int INT_VAL_FIELD_NUMBER

Constant Value: 7

public static final int RESOURCE_HANDLE_VAL_FIELD_NUMBER

Constant Value: 14

public static final int SCOMPLEX_VAL_FIELD_NUMBER

Constant Value: 9

public static final int STRING_VAL_FIELD_NUMBER

Constant Value: 8

public static final int TENSOR_CONTENT_FIELD_NUMBER

Constant Value: 4

public static final int TENSOR_SHAPE_FIELD_NUMBER

Constant Value: 2

public static final int UINT32_VAL_FIELD_NUMBER

Constant Value: 16

public static final int UINT64_VAL_FIELD_NUMBER

Constant Value: 17

public static final int VARIANT_VAL_FIELD_NUMBER

Constant Value: 15

public static final int VERSION_NUMBER_FIELD_NUMBER

Constant Value: 3

Public Methods

public boolean equals (Object obj)

public boolean getBoolVal (int index)

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

public int getBoolValCount ()

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

public List<Boolean> getBoolValList ()

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

public double getDcomplexVal (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];

public 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];

public List<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];

public static TensorProto getDefaultInstance ()

public TensorProto getDefaultInstanceForType ()

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

public double getDoubleVal (int index)

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

public int getDoubleValCount ()

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

public List<Double> getDoubleValList ()

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

public DataType getDtype ()

.tensorflow.DataType dtype = 1;

public int getDtypeValue ()

.tensorflow.DataType dtype = 1;

public float getFloatVal (int index)

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

public int getFloatValCount ()

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

public List<Float> getFloatValList ()

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

public int getHalfVal (int index)

 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 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];

public List<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];

public long getInt64Val (int index)

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

public int getInt64ValCount ()

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

public List<Long> getInt64ValList ()

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

public int getIntVal (int index)

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

public int getIntValCount ()

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

public List<Integer> getIntValList ()

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

public getParserForType ()

public ResourceHandleProto getResourceHandleVal (int index)

 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public int getResourceHandleValCount ()

 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public List<ResourceHandleProto> getResourceHandleValList ()

 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder (int index)

 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public List<? extends ResourceHandleProtoOrBuilder> getResourceHandleValOrBuilderList ()

 DT_RESOURCE
 
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;

public float getScomplexVal (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];

public 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];

public List<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];

public int getSerializedSize ()

public com.google.protobuf.ByteString getStringVal (int index)

 DT_STRING
 
repeated bytes string_val = 8;

public int getStringValCount ()

 DT_STRING
 
repeated bytes string_val = 8;

public List<ByteString> getStringValList ()

 DT_STRING
 
repeated bytes string_val = 8;

public 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;

public TensorShapeProto getTensorShape ()

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

public TensorShapeProtoOrBuilder getTensorShapeOrBuilder ()

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

public int getUint32Val (int index)

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

public int getUint32ValCount ()

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

public List<Integer> getUint32ValList ()

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

public long getUint64Val (int index)

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

public int getUint64ValCount ()

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

public List<Long> getUint64ValList ()

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

public final com.google.protobuf.UnknownFieldSet getUnknownFields ()

public VariantTensorDataProto getVariantVal (int index)

 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

public int getVariantValCount ()

 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

public List<VariantTensorDataProto> getVariantValList ()

 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

public VariantTensorDataProtoOrBuilder getVariantValOrBuilder (int index)

 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

public List<? extends VariantTensorDataProtoOrBuilder> getVariantValOrBuilderList ()

 DT_VARIANT
 
repeated .tensorflow.VariantTensorDataProto variant_val = 15;

public 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;

public boolean hasTensorShape ()

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

public int hashCode ()

public final boolean isInitialized ()

public static TensorProto.Builder newBuilder ()

public static TensorProto.Builder newBuilder (TensorProto prototype)

public TensorProto.Builder newBuilderForType ()

public static TensorProto parseDelimitedFrom (InputStream input)

Throws
IOException

public static TensorProto parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
IOException

public static TensorProto parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
InvalidProtocolBufferException

public static TensorProto parseFrom (com.google.protobuf.CodedInputStream input)

Throws
IOException

public static TensorProto parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
InvalidProtocolBufferException

public static TensorProto parseFrom (ByteBuffer data)

Throws
InvalidProtocolBufferException

public static TensorProto parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
IOException

public static TensorProto parseFrom (com.google.protobuf.ByteString data)

Throws
InvalidProtocolBufferException

public static TensorProto parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
IOException

public static TensorProto parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
InvalidProtocolBufferException

public static parser ()

public TensorProto.Builder toBuilder ()

public void writeTo (com.google.protobuf.CodedOutputStream output)

Throws
IOException