Class/Object

io.hydrosphere.serving.tensorflow.tensor

TensorProto

Related Docs: object TensorProto | package tensor

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final case class TensorProto(dtype: DataType = ..., tensorShape: Option[TensorShapeProto] = None, versionNumber: Int = 0, tensorContent: ByteString = ..., halfVal: Seq[Int] = _root_.scala.collection.Seq.empty, floatVal: Seq[Float] = _root_.scala.collection.Seq.empty, doubleVal: Seq[Double] = _root_.scala.collection.Seq.empty, intVal: Seq[Int] = _root_.scala.collection.Seq.empty, stringVal: Seq[ByteString] = _root_.scala.collection.Seq.empty, scomplexVal: Seq[Float] = _root_.scala.collection.Seq.empty, int64Val: Seq[Long] = _root_.scala.collection.Seq.empty, boolVal: Seq[Boolean] = _root_.scala.collection.Seq.empty, dcomplexVal: Seq[Double] = _root_.scala.collection.Seq.empty, variantVal: Seq[VariantTensorDataProto] = _root_.scala.collection.Seq.empty, uint32Val: Seq[Int] = _root_.scala.collection.Seq.empty, uint64Val: Seq[Long] = _root_.scala.collection.Seq.empty, mapVal: Seq[MapTensorData] = _root_.scala.collection.Seq.empty) extends GeneratedMessage with Message[TensorProto] with Updatable[TensorProto] with Product with Serializable

Protocol buffer representing a tensor.

tensorShape

Shape of the tensor.

versionNumber

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.

tensorContent

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.

halfVal

DT_HALF. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.

floatVal

DT_FLOAT.

doubleVal

DT_DOUBLE.

intVal

DT_INT32, DT_INT16, DT_INT8, DT_UINT8.

stringVal

DT_STRING

scomplexVal

DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.

int64Val

DT_INT64

boolVal

DT_BOOL

dcomplexVal

DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.

variantVal

DT_VARIANT

uint32Val

DT_UINT32

uint64Val

DT_UINT64

mapVal

Hydroserving

Annotations
@SerialVersionUID()
Linear Supertypes
Product, Equals, Updatable[TensorProto], Message[TensorProto], GeneratedMessage, Serializable, Serializable, AnyRef, Any
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Inherited
  1. TensorProto
  2. Product
  3. Equals
  4. Updatable
  5. Message
  6. GeneratedMessage
  7. Serializable
  8. Serializable
  9. AnyRef
  10. Any
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Visibility
  1. Public
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Instance Constructors

  1. new TensorProto(dtype: DataType = ..., tensorShape: Option[TensorShapeProto] = None, versionNumber: Int = 0, tensorContent: ByteString = ..., halfVal: Seq[Int] = _root_.scala.collection.Seq.empty, floatVal: Seq[Float] = _root_.scala.collection.Seq.empty, doubleVal: Seq[Double] = _root_.scala.collection.Seq.empty, intVal: Seq[Int] = _root_.scala.collection.Seq.empty, stringVal: Seq[ByteString] = _root_.scala.collection.Seq.empty, scomplexVal: Seq[Float] = _root_.scala.collection.Seq.empty, int64Val: Seq[Long] = _root_.scala.collection.Seq.empty, boolVal: Seq[Boolean] = _root_.scala.collection.Seq.empty, dcomplexVal: Seq[Double] = _root_.scala.collection.Seq.empty, variantVal: Seq[VariantTensorDataProto] = _root_.scala.collection.Seq.empty, uint32Val: Seq[Int] = _root_.scala.collection.Seq.empty, uint64Val: Seq[Long] = _root_.scala.collection.Seq.empty, mapVal: Seq[MapTensorData] = _root_.scala.collection.Seq.empty)

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    tensorShape

    Shape of the tensor.

    versionNumber

    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.

    tensorContent

    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.

    halfVal

    DT_HALF. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.

    floatVal

    DT_FLOAT.

    doubleVal

    DT_DOUBLE.

    intVal

    DT_INT32, DT_INT16, DT_INT8, DT_UINT8.

    stringVal

    DT_STRING

    scomplexVal

    DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.

    int64Val

    DT_INT64

    boolVal

    DT_BOOL

    dcomplexVal

    DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.

    variantVal

    DT_VARIANT

    uint32Val

    DT_UINT32

    uint64Val

    DT_UINT64

    mapVal

    Hydroserving

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. def addAllBoolVal(__vs: TraversableOnce[Boolean]): TensorProto

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  5. def addAllDcomplexVal(__vs: TraversableOnce[Double]): TensorProto

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  6. def addAllDoubleVal(__vs: TraversableOnce[Double]): TensorProto

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  7. def addAllFloatVal(__vs: TraversableOnce[Float]): TensorProto

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  8. def addAllHalfVal(__vs: TraversableOnce[Int]): TensorProto

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  9. def addAllInt64Val(__vs: TraversableOnce[Long]): TensorProto

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  10. def addAllIntVal(__vs: TraversableOnce[Int]): TensorProto

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  11. def addAllMapVal(__vs: TraversableOnce[MapTensorData]): TensorProto

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  12. def addAllScomplexVal(__vs: TraversableOnce[Float]): TensorProto

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  13. def addAllStringVal(__vs: TraversableOnce[ByteString]): TensorProto

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  14. def addAllUint32Val(__vs: TraversableOnce[Int]): TensorProto

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  15. def addAllUint64Val(__vs: TraversableOnce[Long]): TensorProto

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  16. def addAllVariantVal(__vs: TraversableOnce[VariantTensorDataProto]): TensorProto

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  17. def addBoolVal(__vs: Boolean*): TensorProto

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  18. def addDcomplexVal(__vs: Double*): TensorProto

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  19. def addDoubleVal(__vs: Double*): TensorProto

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  20. def addFloatVal(__vs: Float*): TensorProto

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  21. def addHalfVal(__vs: Int*): TensorProto

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  22. def addInt64Val(__vs: Long*): TensorProto

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  23. def addIntVal(__vs: Int*): TensorProto

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  24. def addMapVal(__vs: MapTensorData*): TensorProto

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  25. def addScomplexVal(__vs: Float*): TensorProto

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  26. def addStringVal(__vs: ByteString*): TensorProto

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  27. def addUint32Val(__vs: Int*): TensorProto

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  28. def addUint64Val(__vs: Long*): TensorProto

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  29. def addVariantVal(__vs: VariantTensorDataProto*): TensorProto

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  30. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  31. val boolVal: Seq[Boolean]

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    DT_BOOL

  32. def clearBoolVal: TensorProto

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  33. def clearDcomplexVal: TensorProto

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  34. def clearDoubleVal: TensorProto

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  35. def clearFloatVal: TensorProto

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  36. def clearHalfVal: TensorProto

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  37. def clearInt64Val: TensorProto

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  38. def clearIntVal: TensorProto

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  39. def clearMapVal: TensorProto

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  40. def clearScomplexVal: TensorProto

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  41. def clearStringVal: TensorProto

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  42. def clearTensorShape: TensorProto

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  43. def clearUint32Val: TensorProto

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  44. def clearUint64Val: TensorProto

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  45. def clearVariantVal: TensorProto

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  46. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  47. def companion: TensorProto.type

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    Definition Classes
    TensorProto → GeneratedMessage

  48. val dcomplexVal: Seq[Double]

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    DT_COMPLEX128.

    DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.

  49. val doubleVal: Seq[Double]

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    DT_DOUBLE.

  50. val dtype: DataType

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  51. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  52. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  53. val floatVal: Seq[Float]

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    DT_FLOAT.

  54. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  55. def getField(__field: FieldDescriptor): PValue

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    Definition Classes
    TensorProto → GeneratedMessage

  56. def getFieldByNumber(__fieldNumber: Int): Any

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    Definition Classes
    TensorProto → GeneratedMessage

  57. def getTensorShape: TensorShapeProto

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  58. val halfVal: Seq[Int]

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    DT_HALF.

    DT_HALF. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.

  59. val int64Val: Seq[Long]

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    DT_INT64

  60. val intVal: Seq[Int]

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    DT_INT32, DT_INT16, DT_INT8, DT_UINT8.

  61. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  62. val mapVal: Seq[MapTensorData]

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    Hydroserving

  63. def mergeFrom(_input__: CodedInputStream): TensorProto

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    Definition Classes
    TensorProto → Message

  64. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  65. final def notify(): Unit

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    Definition Classes
    AnyRef

  66. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  67. val scomplexVal: Seq[Float]

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    DT_COMPLEX64.

    DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.

  68. final def serializedSize: Int

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    Definition Classes
    TensorProto → GeneratedMessage

  69. val stringVal: Seq[ByteString]

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    DT_STRING

  70. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  71. val tensorContent: ByteString

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    Serialized raw tensor content from either Tensor::AsProtoTensorContent or memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.

    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.

  72. val tensorShape: Option[TensorShapeProto]

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    Shape of the tensor.

  73. def toByteArray: Array[Byte]

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    Definition Classes
    GeneratedMessage

  74. def toByteString: ByteString

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    Definition Classes
    GeneratedMessage

  75. def toPMessage: PMessage

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    Definition Classes
    GeneratedMessage

  76. def toProtoString: String

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    Definition Classes
    TensorProto → GeneratedMessage

  77. val uint32Val: Seq[Int]

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    DT_UINT32

  78. val uint64Val: Seq[Long]

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    DT_UINT64

  79. def update(ms: (Lens[TensorProto, TensorProto]) ⇒ Mutation[TensorProto]*): TensorProto

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    Definition Classes
    Updatable

  80. val variantVal: Seq[VariantTensorDataProto]

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    DT_VARIANT

  81. val versionNumber: Int

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    Version number.

    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.

  82. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  83. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  84. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  85. def withBoolVal(__v: Seq[Boolean]): TensorProto

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  86. def withDcomplexVal(__v: Seq[Double]): TensorProto

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  87. def withDoubleVal(__v: Seq[Double]): TensorProto

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  88. def withDtype(__v: DataType): TensorProto

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  89. def withFloatVal(__v: Seq[Float]): TensorProto

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  90. def withHalfVal(__v: Seq[Int]): TensorProto

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  91. def withInt64Val(__v: Seq[Long]): TensorProto

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  92. def withIntVal(__v: Seq[Int]): TensorProto

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  93. def withMapVal(__v: Seq[MapTensorData]): TensorProto

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  94. def withScomplexVal(__v: Seq[Float]): TensorProto

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  95. def withStringVal(__v: Seq[ByteString]): TensorProto

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  96. def withTensorContent(__v: ByteString): TensorProto

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  97. def withTensorShape(__v: TensorShapeProto): TensorProto

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  98. def withUint32Val(__v: Seq[Int]): TensorProto

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  99. def withUint64Val(__v: Seq[Long]): TensorProto

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  100. def withVariantVal(__v: Seq[VariantTensorDataProto]): TensorProto

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  101. def withVersionNumber(__v: Int): TensorProto

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  102. def writeDelimitedTo(output: OutputStream): Unit

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    Definition Classes
    GeneratedMessage

  103. def writeTo(_output__: CodedOutputStream): Unit

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    Definition Classes
    TensorProto → GeneratedMessage

  104. def writeTo(output: OutputStream): Unit

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    Definition Classes
    GeneratedMessage

Deprecated Value Members

  1. def getAllFields: Map[FieldDescriptor, Any]

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    Definition Classes
    GeneratedMessage
    Annotations
    @deprecated
    Deprecated

    (Since version 0.6.0) Use toPMessage

  2. def getField(field: FieldDescriptor): Any

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    Definition Classes
    GeneratedMessage
    Annotations
    @deprecated
    Deprecated

    (Since version 0.6.0) Use getField that accepts a ScalaPB descriptor and returns PValue

Inherited from Product

Inherited from Equals

Inherited from Updatable[TensorProto]

Inherited from Message[TensorProto]

Inherited from GeneratedMessage

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped