Packages

class AssertionDLModel extends AnnotatorModel[AssertionDLModel] with WriteTensorflowModel with HasStorageRef with HasSimpleAnnotate[AssertionDLModel] with ParamsAndFeaturesWritable with HandleExceptionParams with CheckLicense

This is a main class in AssertionDL family. A Deep Learning based approach is used to extract Assertion Status from extracted entities and text. AssertionDLModel requires DOCUMENT, CHUNK and WORD_EMBEDDINGS type annotator inputs, which can be obtained by e.g a DocumentAssembler, NerConverter and WordEmbeddingsModel. The result is an assertion status annotation for each recognized entity. Possible values include “present”, “absent”, “hypothetical”, “conditional”, “associated_with_other_person” etc.

For pretrained models please see the Models Hub for available models.

Example

Define pipeline stages to extract NER chunks first

val data = Seq(
  "Patient with severe fever and sore throat",
  "Patient shows no stomach pain",
  "She was maintained on an epidural and PCA for pain control.").toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("document")
val sentenceDetector = new SentenceDetector().setInputCols("document").setOutputCol("sentence")
val tokenizer = new Tokenizer().setInputCols("sentence").setOutputCol("token")
val embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical", "en", "clinical/models")
  .setOutputCol("embeddings")
val nerModel = MedicalNerModel.pretrained("ner_clinical", "en", "clinical/models")
  .setInputCols("sentence", "token", "embeddings").setOutputCol("ner")
val nerConverter = new NerConverter().setInputCols("sentence", "token", "ner").setOutputCol("ner_chunk")

Then a pretrained AssertionDLModel is used to extract the assertion status

val clinicalAssertion = AssertionDLModel.pretrained("assertion_dl", "en", "clinical/models")
  .setInputCols("sentence", "ner_chunk", "embeddings")
  .setOutputCol("assertion")

val assertionPipeline = new Pipeline().setStages(Array(
  documentAssembler,
  sentenceDetector,
  tokenizer,
  embeddings,
  nerModel,
  nerConverter,
  clinicalAssertion
))

val assertionModel = assertionPipeline.fit(data)

Show results

val result = assertionModel.transform(data)
result.selectExpr("ner_chunk.result", "assertion.result").show(3, truncate=false)
+--------------------------------+--------------------------------+
|result                          |result                          |
+--------------------------------+--------------------------------+
|[severe fever, sore throat]     |[present, present]              |
|[stomach pain]                  |[absent]                        |
|[an epidural, PCA, pain control]|[present, present, hypothetical]|
+--------------------------------+--------------------------------+
See also

AssertionDLApproach for training a custom AssertionDLModel

AssertionLogRegModel for non deep learning based extraction

Linear Supertypes
CheckLicense, HandleExceptionParams, HasSimpleAnnotate[AssertionDLModel], HasStorageRef, WriteTensorflowModel, AnnotatorModel[AssertionDLModel], CanBeLazy, RawAnnotator[AssertionDLModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[AssertionDLModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
AssertionDLModel, AssertionDLModel
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Inherited
  1. AssertionDLModel
  2. CheckLicense
  3. HandleExceptionParams
  4. HasSimpleAnnotate
  5. HasStorageRef
  6. WriteTensorflowModel
  7. AnnotatorModel
  8. CanBeLazy
  9. RawAnnotator
  10. HasOutputAnnotationCol
  11. HasInputAnnotationCols
  12. HasOutputAnnotatorType
  13. ParamsAndFeaturesWritable
  14. HasFeatures
  15. DefaultParamsWritable
  16. MLWritable
  17. Model
  18. Transformer
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AssertionDLModel()
  2. new AssertionDLModel(uid: String)

    uid

    a unique identifier for the instantiated AnnotatorModel

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    This is main point of interest.

    This is main point of interest. It annotates the input dataset applying properties of the class above This method utilises chunk groups, word piece embeddings and conversion to chunk indexes

    annotations

    a sequence of Annotations

    returns

    a sequence of projected Annotations

    Definition Classes
    AssertionDLModel → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. val batchSize: IntParam

    Size of every batch

  14. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]

    This method validates the dataset before annotation

    This method validates the dataset before annotation

    dataset

    a collection of inputs to validate

    returns

    a Dataset after validation

    Attributes
    protected
    Definition Classes
    AssertionDLModel → AnnotatorModel
  15. def checkEntityAssertion(entity: String, assertion: String): Boolean
  16. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  17. def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
    Definition Classes
    CheckLicense
  18. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  19. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  20. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  21. val classes: StringArrayParam

    List of internal copies of classes used to train for Python

  22. final def clear(param: Param[_]): AssertionDLModel.this.type
    Definition Classes
    Params
  23. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  24. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString Example Python code with TF version 2.3: In [1]: import tensorflow as tf In [2]: config = tf.compat.v1.ConfigProto(allow_soft_placement=True, log_device_placement=True) ...: config.gpu_options.allow_growth = True ...: for b in config.SerializeToString(): ...: print(b) ...: 50 2 32 1 56 1 64 1

  25. def copy(extra: ParamMap): AssertionDLModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    AssertionDLModel → RawAnnotator → Model → Transformer → PipelineStage → Params
  26. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  27. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  28. val datasetParams: StructFeature[DatasetEncoderParams]

    Collection of Parameters, which are used by method annotate()

  29. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  30. def dfAnnotate: UserDefinedFunction
    Definition Classes
    HasSimpleAnnotate
  31. val doExceptionHandling: BooleanParam

    If true, exceptions are handled.

    If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

    Definition Classes
    HandleExceptionParams
  32. var entityAssertionCaseSensitive: BooleanParam

    Determines whether entity labels and assertion labels are case sensitive

  33. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  35. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  36. def explainParams(): String
    Definition Classes
    Params
  37. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  38. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  39. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  40. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  41. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  42. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  43. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  44. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  45. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  46. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  47. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  48. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  49. def getClasses: Array[String]

    get the tags used to trained this NerDLModel

  50. def getConfigProtoBytes: Option[Array[Byte]]

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString

  51. def getConfigProtoBytesAsInt: Option[Array[Int]]
  52. def getDatasetParams: DatasetEncoderParams
  53. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  54. def getEntityAssertion: Map[String, Array[String]]

    Get the lists of assertion labels allowed for a given entity

  55. def getEntityAssertionCaseSensitive: Boolean

    Gets the case sensitivity of entities and assertion labels

  56. def getEntityAssertionStr: String

    Get the string representation of the lists of assertion labels allowed for a given entity

  57. def getIncludeConfidence: Boolean

    whether to include confidence scores in annotation metadata

  58. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  59. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  60. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  61. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  62. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  63. def getReplaceLabels: Map[String, String]

    Gets the assertion labels to be replaced for the specified new labels.

  64. def getReplaceLabelsStr: String

    Gets the string presentation of the assertion labels to be replaced for the specified new labels.

  65. def getScopeWindow: (Int, Int)

    Get scope window

  66. def getStorageRef: String
    Definition Classes
    HasStorageRef
  67. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  68. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  69. def hasParent: Boolean
    Definition Classes
    Model
  70. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  71. val includeConfidence: BooleanParam

    whether to include confidence scores in annotation metadata (Default: false)

  72. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  73. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. val inputAnnotatorTypes: Array[String]

    Input annotator types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Input annotator types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Definition Classes
    AssertionDLModel → HasInputAnnotationCols
  75. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  76. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  77. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  78. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  79. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  80. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  81. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  82. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  88. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  89. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  92. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  93. val maxSentLen: IntParam

    Max possible length of a sentence (Default: 256)

  94. def model: TensorflowAssertion

    Tensorflow model for the AssertionDLModel.

    Tensorflow model for the AssertionDLModel. This is used to generate the predictions.

  95. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  96. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  97. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  98. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  99. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    AssertionDLModel → ParamsAndFeaturesWritable
  100. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  101. val outputAnnotatorType: AnnotatorType

    Output annotator types: ASSERTION

    Output annotator types: ASSERTION

    Definition Classes
    AssertionDLModel → HasOutputAnnotatorType
  102. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  103. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  104. var parent: Estimator[AssertionDLModel]
    Definition Classes
    Model
  105. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  106. val scopeWindow: IntArrayParam

    The scope window of the assertion (whole sentence by default)

  107. def set[T](feature: StructFeature[T], value: T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  109. def set[T](feature: SetFeature[T], value: Set[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  110. def set[T](feature: ArrayFeature[T], value: Array[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  111. final def set(paramPair: ParamPair[_]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  112. final def set(param: String, value: Any): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  113. final def set[T](param: Param[T], value: T): AssertionDLModel.this.type
    Definition Classes
    Params
  114. def setBatchSize(size: Int): AssertionDLModel.this.type

    Size of every batch

  115. def setConfigProtoBytes(bytes: Array[Int]): AssertionDLModel

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString

  116. def setDatasetParams(params: DatasetEncoderParams): AssertionDLModel

    Collection of Parameters, which are used by method annotate()

  117. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  118. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  119. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  120. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  121. final def setDefault(paramPairs: ParamPair[_]*): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  122. final def setDefault[T](param: Param[T], value: T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  123. def setDoExceptionHandling(value: Boolean): AssertionDLModel.this.type

    If true, exceptions are handled.

    If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

    Definition Classes
    HandleExceptionParams
  124. def setEntityAssertion(assertionEntities: HashMap[String, List[String]]): AssertionDLModel.this.type

    Set the lists of assertion labels allowed for a given entity.

    Set the lists of assertion labels allowed for a given entity.

    Note

    entityAssertion functionality is processed earlier than replaceLabels

  125. def setEntityAssertion(assertionEntities: Map[String, Array[String]]): AssertionDLModel.this.type

    Set the lists of assertion labels allowed for a given entity.

    Set the lists of assertion labels allowed for a given entity.

    Note

    entityAssertion functionality is processed earlier than replaceLabels

  126. def setEntityAssertionCaseSensitive(value: Boolean): AssertionDLModel

    Sets the case sensitivity of entities and assertion labels

  127. def setIncludeConfidence(value: Boolean): AssertionDLModel.this.type

    whether to include confidence scores in annotation metadata

  128. final def setInputCols(value: String*): AssertionDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  129. def setInputCols(value: Array[String]): AssertionDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  130. def setLazyAnnotator(value: Boolean): AssertionDLModel.this.type
    Definition Classes
    CanBeLazy
  131. def setMaxSentLen(len: Int): AssertionDLModel.this.type

    Max possible length of a sentence.

  132. final def setOutputCol(value: String): AssertionDLModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  133. def setParent(parent: Estimator[AssertionDLModel]): AssertionDLModel
    Definition Classes
    Model
  134. def setReplaceLabels(value: Map[String, String]): AssertionDLModel.this.type

    Sets the replaceLabels to be replaced for the specified new labels.

    Sets the replaceLabels to be replaced for the specified new labels.

    value

    A map containing the replacement labels.

    Note

    replaceLabels functionality runs later than entityAssertion

  135. def setReplaceLabels(value: HashMap[String, String]): AssertionDLModel.this.type

    Sets the replaceLabels to be replaced for the specified new labels.

    Sets the replaceLabels to be replaced for the specified new labels.

    value

    A map containing the replacement labels.

    Note

    replaceLabels functionality is processed later than entityAssertion

  136. def setScopeWindow(window: (Int, Int)): AssertionDLModel.this.type

    Max possible length of a sentence.

  137. def setStorageRef(value: String): AssertionDLModel.this.type
    Definition Classes
    HasStorageRef
  138. def setTensorflow(spark: SparkSession, tf: TensorflowWrapper): AssertionDLModel
  139. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  140. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  141. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  142. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  143. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  144. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  145. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  146. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  147. val uid: String
    Definition Classes
    AssertionDLModel → Identifiable
  148. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  149. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  150. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  151. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  152. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  153. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  154. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  155. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  156. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  157. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from CheckLicense

Inherited from HandleExceptionParams

Inherited from HasSimpleAnnotate[AssertionDLModel]

Inherited from HasStorageRef

Inherited from WriteTensorflowModel

Inherited from AnnotatorModel[AssertionDLModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[AssertionDLModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[AssertionDLModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters