final case class GraphProto(node: Seq[NodeProto] = _root_.scala.Seq.empty, name: Option[String] = _root_.scala.None, initializer: Seq[TensorProto] = _root_.scala.Seq.empty, sparseInitializer: Seq[SparseTensorProto] = _root_.scala.Seq.empty, docString: Option[String] = _root_.scala.None, input: Seq[ValueInfoProto] = _root_.scala.Seq.empty, output: Seq[ValueInfoProto] = _root_.scala.Seq.empty, valueInfo: Seq[ValueInfoProto] = _root_.scala.Seq.empty, quantizationAnnotation: Seq[TensorAnnotation] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = ...) extends GeneratedMessage with Updatable[GraphProto] with Product with Serializable
Graphs
A graph defines the computational logic of a model and is comprised of a parameterized list of nodes that form a directed acyclic graph based on their inputs and outputs. This is the equivalent of the "network" or "graph" in many deep learning frameworks.
- node
The nodes in the graph, sorted topologically.
- name
The name of the graph. namespace Graph
- initializer
A list of named tensor values, used to specify constant inputs of the graph. Each initializer (both TensorProto as well SparseTensorProto) MUST have a name. The name MUST be unique across both initializer and sparse_initializer, but the name MAY also appear in the input list.
- sparseInitializer
Initializers (see above) stored in sparse format.
- docString
A human-readable documentation for this graph. Markdown is allowed.
- input
The inputs and outputs of the graph.
- valueInfo
Information for the values in the graph. The ValueInfoProto.name's must be distinct. It is optional for a value to appear in value_info list.
- quantizationAnnotation
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors. For example: For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated, which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
- Annotations
- @SerialVersionUID()
- Alphabetic
- By Inheritance
- GraphProto
- Updatable
- GeneratedMessage
- Serializable
- Serializable
- Product
- Equals
- AnyRef
- Any
- Hide All
- Show All
- Public
- All
Instance Constructors
-
new
GraphProto(node: Seq[NodeProto] = _root_.scala.Seq.empty, name: Option[String] = _root_.scala.None, initializer: Seq[TensorProto] = _root_.scala.Seq.empty, sparseInitializer: Seq[SparseTensorProto] = _root_.scala.Seq.empty, docString: Option[String] = _root_.scala.None, input: Seq[ValueInfoProto] = _root_.scala.Seq.empty, output: Seq[ValueInfoProto] = _root_.scala.Seq.empty, valueInfo: Seq[ValueInfoProto] = _root_.scala.Seq.empty, quantizationAnnotation: Seq[TensorAnnotation] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = ...)
- node
The nodes in the graph, sorted topologically.
- name
The name of the graph. namespace Graph
- initializer
A list of named tensor values, used to specify constant inputs of the graph. Each initializer (both TensorProto as well SparseTensorProto) MUST have a name. The name MUST be unique across both initializer and sparse_initializer, but the name MAY also appear in the input list.
- sparseInitializer
Initializers (see above) stored in sparse format.
- docString
A human-readable documentation for this graph. Markdown is allowed.
- input
The inputs and outputs of the graph.
- valueInfo
Information for the values in the graph. The ValueInfoProto.name's must be distinct. It is optional for a value to appear in value_info list.
- quantizationAnnotation
This field carries information to indicate the mapping among a tensor and its quantization parameter tensors. For example: For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated, which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def addAllInitializer(__vs: Iterable[TensorProto]): GraphProto
- def addAllInput(__vs: Iterable[ValueInfoProto]): GraphProto
- def addAllNode(__vs: Iterable[NodeProto]): GraphProto
- def addAllOutput(__vs: Iterable[ValueInfoProto]): GraphProto
- def addAllQuantizationAnnotation(__vs: Iterable[TensorAnnotation]): GraphProto
- def addAllSparseInitializer(__vs: Iterable[SparseTensorProto]): GraphProto
- def addAllValueInfo(__vs: Iterable[ValueInfoProto]): GraphProto
- def addInitializer(__vs: TensorProto*): GraphProto
- def addInput(__vs: ValueInfoProto*): GraphProto
- def addNode(__vs: NodeProto*): GraphProto
- def addOutput(__vs: ValueInfoProto*): GraphProto
- def addQuantizationAnnotation(__vs: TensorAnnotation*): GraphProto
- def addSparseInitializer(__vs: SparseTensorProto*): GraphProto
- def addValueInfo(__vs: ValueInfoProto*): GraphProto
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clearDocString: GraphProto
- def clearInitializer: GraphProto
- def clearInput: GraphProto
- def clearName: GraphProto
- def clearNode: GraphProto
- def clearOutput: GraphProto
- def clearQuantizationAnnotation: GraphProto
- def clearSparseInitializer: GraphProto
- def clearValueInfo: GraphProto
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native() @HotSpotIntrinsicCandidate()
-
def
companion: GraphProto.type
- Definition Classes
- GraphProto → GeneratedMessage
- def discardUnknownFields: GraphProto
- val docString: Option[String]
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def getDocString: String
-
def
getField(__field: FieldDescriptor): PValue
- Definition Classes
- GraphProto → GeneratedMessage
-
def
getFieldByNumber(__fieldNumber: Int): Any
- Definition Classes
- GraphProto → GeneratedMessage
- def getName: String
- val initializer: Seq[TensorProto]
- val input: Seq[ValueInfoProto]
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- val name: Option[String]
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- val node: Seq[NodeProto]
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- val output: Seq[ValueInfoProto]
- val quantizationAnnotation: Seq[TensorAnnotation]
-
def
serializedSize: Int
- Definition Classes
- GraphProto → GeneratedMessage
- val sparseInitializer: Seq[SparseTensorProto]
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
final
def
toByteArray: Array[Byte]
- Definition Classes
- GeneratedMessage
-
final
def
toByteString: ByteString
- Definition Classes
- GeneratedMessage
-
final
def
toPMessage: PMessage
- Definition Classes
- GeneratedMessage
-
def
toProtoString: String
- Definition Classes
- GraphProto → GeneratedMessage
- val unknownFields: UnknownFieldSet
-
def
update(ms: (Lens[GraphProto, GraphProto]) ⇒ Mutation[GraphProto]*): GraphProto
- Definition Classes
- Updatable
- val valueInfo: Seq[ValueInfoProto]
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
- def withDocString(__v: String): GraphProto
- def withInitializer(__v: Seq[TensorProto]): GraphProto
- def withInput(__v: Seq[ValueInfoProto]): GraphProto
- def withName(__v: String): GraphProto
- def withNode(__v: Seq[NodeProto]): GraphProto
- def withOutput(__v: Seq[ValueInfoProto]): GraphProto
- def withQuantizationAnnotation(__v: Seq[TensorAnnotation]): GraphProto
- def withSparseInitializer(__v: Seq[SparseTensorProto]): GraphProto
- def withUnknownFields(__v: UnknownFieldSet): GraphProto
- def withValueInfo(__v: Seq[ValueInfoProto]): GraphProto
-
final
def
writeDelimitedTo(output: OutputStream): Unit
- Definition Classes
- GeneratedMessage
-
def
writeTo(_output__: CodedOutputStream): Unit
- Definition Classes
- GraphProto → GeneratedMessage
-
final
def
writeTo(output: OutputStream): Unit
- Definition Classes
- GeneratedMessage
Deprecated Value Members
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] ) @Deprecated
- Deprecated