final case class ModelProto(irVersion: Option[Long] = _root_.scala.None, opsetImport: Seq[OperatorSetIdProto] = _root_.scala.Seq.empty, producerName: Option[String] = _root_.scala.None, producerVersion: Option[String] = _root_.scala.None, domain: Option[String] = _root_.scala.None, modelVersion: Option[Long] = _root_.scala.None, docString: Option[String] = _root_.scala.None, graph: Option[GraphProto] = _root_.scala.None, metadataProps: Seq[StringStringEntryProto] = _root_.scala.Seq.empty, trainingInfo: Seq[TrainingInfoProto] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = _root_.scalapb.UnknownFieldSet.empty) extends GeneratedMessage with Updatable[ModelProto] with Product with Serializable
Models
ModelProto is a top-level file/container format for bundling a ML model and associating its computation graph with metadata.
The semantics of the model are described by the associated GraphProto's.
- irVersion
The version of the IR this model targets. See Version enum above. This field MUST be present.
- opsetImport
The OperatorSets this model relies on. All ModelProtos MUST have at least one entry that specifies which version of the ONNX OperatorSet is being imported. All nodes in the ModelProto's graph will bind against the operator with the same-domain/same-op_type operator with the HIGHEST version in the referenced operator sets.
- producerName
The name of the framework or tool used to generate this model. This field SHOULD be present to indicate which implementation/tool/framework emitted the model.
- producerVersion
The version of the framework or tool used to generate this model. This field SHOULD be present to indicate which implementation/tool/framework emitted the model.
- domain
Domain name of the model. We use reverse domain names as name space indicators. For example:
com.facebook.fair
orcom.microsoft.cognitiveservices
Together withmodel_version
and GraphProto.name, this forms the unique identity of the graph.- modelVersion
The version of the graph encoded. See Version enum below.
- docString
A human-readable documentation for this model. Markdown is allowed.
- graph
The parameterized graph that is evaluated to execute the model.
- metadataProps
Named metadata values; keys should be distinct.
- trainingInfo
Training-specific information. Sequentially executing all stored
TrainingInfoProto.algorithm
s and assigning their outputs following the correspondingTrainingInfoProto.update_binding
s is one training iteration. Similarly, to initialize the model (as if training hasn't happened), the user should sequentially execute all storedTrainingInfoProto.initialization
s and assigns their outputs usingTrainingInfoProto.initialization_binding
s. If this field is empty, the training behavior of the model is undefined.
- Annotations
- @SerialVersionUID()
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- ModelProto
- Updatable
- GeneratedMessage
- Serializable
- Product
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Instance Constructors
- new ModelProto(irVersion: Option[Long] = _root_.scala.None, opsetImport: Seq[OperatorSetIdProto] = _root_.scala.Seq.empty, producerName: Option[String] = _root_.scala.None, producerVersion: Option[String] = _root_.scala.None, domain: Option[String] = _root_.scala.None, modelVersion: Option[Long] = _root_.scala.None, docString: Option[String] = _root_.scala.None, graph: Option[GraphProto] = _root_.scala.None, metadataProps: Seq[StringStringEntryProto] = _root_.scala.Seq.empty, trainingInfo: Seq[TrainingInfoProto] = _root_.scala.Seq.empty, unknownFields: UnknownFieldSet = _root_.scalapb.UnknownFieldSet.empty)
- irVersion
The version of the IR this model targets. See Version enum above. This field MUST be present.
- opsetImport
The OperatorSets this model relies on. All ModelProtos MUST have at least one entry that specifies which version of the ONNX OperatorSet is being imported. All nodes in the ModelProto's graph will bind against the operator with the same-domain/same-op_type operator with the HIGHEST version in the referenced operator sets.
- producerName
The name of the framework or tool used to generate this model. This field SHOULD be present to indicate which implementation/tool/framework emitted the model.
- producerVersion
The version of the framework or tool used to generate this model. This field SHOULD be present to indicate which implementation/tool/framework emitted the model.
- domain
Domain name of the model. We use reverse domain names as name space indicators. For example:
com.facebook.fair
orcom.microsoft.cognitiveservices
Together withmodel_version
and GraphProto.name, this forms the unique identity of the graph.- modelVersion
The version of the graph encoded. See Version enum below.
- docString
A human-readable documentation for this model. Markdown is allowed.
- graph
The parameterized graph that is evaluated to execute the model.
- metadataProps
Named metadata values; keys should be distinct.
- trainingInfo
Training-specific information. Sequentially executing all stored
TrainingInfoProto.algorithm
s and assigning their outputs following the correspondingTrainingInfoProto.update_binding
s is one training iteration. Similarly, to initialize the model (as if training hasn't happened), the user should sequentially execute all storedTrainingInfoProto.initialization
s and assigns their outputs usingTrainingInfoProto.initialization_binding
s. If this field is empty, the training behavior of the model is undefined.
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 addAllMetadataProps(__vs: Iterable[StringStringEntryProto]): ModelProto
- def addAllOpsetImport(__vs: Iterable[OperatorSetIdProto]): ModelProto
- def addAllTrainingInfo(__vs: Iterable[TrainingInfoProto]): ModelProto
- def addMetadataProps(__vs: StringStringEntryProto*): ModelProto
- def addOpsetImport(__vs: OperatorSetIdProto*): ModelProto
- def addTrainingInfo(__vs: TrainingInfoProto*): ModelProto
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clearDocString: ModelProto
- def clearDomain: ModelProto
- def clearGraph: ModelProto
- def clearIrVersion: ModelProto
- def clearMetadataProps: ModelProto
- def clearModelVersion: ModelProto
- def clearOpsetImport: ModelProto
- def clearProducerName: ModelProto
- def clearProducerVersion: ModelProto
- def clearTrainingInfo: ModelProto
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- def companion: ModelProto.type
- Definition Classes
- ModelProto → GeneratedMessage
- def discardUnknownFields: ModelProto
- val docString: Option[String]
- val domain: Option[String]
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- def getDocString: String
- def getDomain: String
- def getField(__field: FieldDescriptor): PValue
- Definition Classes
- ModelProto → GeneratedMessage
- def getFieldByNumber(__fieldNumber: Int): Any
- Definition Classes
- ModelProto → GeneratedMessage
- def getGraph: GraphProto
- def getIrVersion: Long
- def getModelVersion: Long
- def getProducerName: String
- def getProducerVersion: String
- val graph: Option[GraphProto]
- val irVersion: Option[Long]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- val metadataProps: Seq[StringStringEntryProto]
- val modelVersion: Option[Long]
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- val opsetImport: Seq[OperatorSetIdProto]
- val producerName: Option[String]
- val producerVersion: Option[String]
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def serializedSize: Int
- Definition Classes
- ModelProto → GeneratedMessage
- 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
- ModelProto → GeneratedMessage
- val trainingInfo: Seq[TrainingInfoProto]
- val unknownFields: UnknownFieldSet
- def update(ms: (Lens[ModelProto, ModelProto]) => Mutation[ModelProto]*): ModelProto
- Definition Classes
- Updatable
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- def withDocString(__v: String): ModelProto
- def withDomain(__v: String): ModelProto
- def withGraph(__v: GraphProto): ModelProto
- def withIrVersion(__v: Long): ModelProto
- def withMetadataProps(__v: Seq[StringStringEntryProto]): ModelProto
- def withModelVersion(__v: Long): ModelProto
- def withOpsetImport(__v: Seq[OperatorSetIdProto]): ModelProto
- def withProducerName(__v: String): ModelProto
- def withProducerVersion(__v: String): ModelProto
- def withTrainingInfo(__v: Seq[TrainingInfoProto]): ModelProto
- def withUnknownFields(__v: UnknownFieldSet): ModelProto
- final def writeDelimitedTo(output: OutputStream): Unit
- Definition Classes
- GeneratedMessage
- def writeTo(_output__: CodedOutputStream): Unit
- Definition Classes
- ModelProto → 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
(Since version 9)