Packages

class AssertionDLApproach extends nlp.annotators.assertion.dl.AssertionDLApproach

Contains all the methods for training an AssertionDLModel. For pretrained models please use AssertionDLModel and see the Models Hub for available models.

Example

First, pipeline stages for pre-processing the dataset (containing columns for text and label) are defined.

val document = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")
val chunk = new Doc2Chunk()
  .setInputCols("document")
  .setOutputCol("chunk")
val token = new Tokenizer()
  .setInputCols("document")
  .setOutputCol("token")
val embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical", "en", "clinical/models")
  .setInputCols("document", "token")
  .setOutputCol("embeddings")

Define AssertionDLApproach with parameters and start training

val assertionStatus = new AssertionDLApproach()
  .setLabelCol("label")
  .setInputCols("document", "chunk", "embeddings")
  .setOutputCol("assertion")
  .setBatchSize(128)
  .setDropout(0.012f)
  .setLearningRate(0.015f)
  .setEpochs(1)
  .setStartCol("start")
  .setEndCol("end")
  .setMaxSentLen(250)

val trainingPipeline = new Pipeline().setStages(Array(
  document,
  chunk,
  token,
  embeddings,
  assertionStatus
))

val assertionModel = trainingPipeline.fit(data)
val assertionResults = assertionModel.transform(data).cache()
See also

AssertionDLModel for using pretrained models

AssertionLogRegModel for non deep learning based extraction

Linear Supertypes
nlp.annotators.assertion.dl.AssertionDLApproach, CheckLicense, HandleExceptionParams, Logging, AnnotatorApproach[nlp.annotators.assertion.dl.AssertionDLModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[nlp.annotators.assertion.dl.AssertionDLModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. AssertionDLApproach
  2. AssertionDLApproach
  3. CheckLicense
  4. HandleExceptionParams
  5. Logging
  6. AnnotatorApproach
  7. CanBeLazy
  8. DefaultParamsWritable
  9. MLWritable
  10. HasOutputAnnotatorType
  11. HasOutputAnnotationCol
  12. HasInputAnnotationCols
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

    uid

    a unique identifier for the instantiated AnnotatorModel

Type Members

  1. 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. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): nlp.annotators.assertion.dl.AssertionDLModel
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. val batchSize: IntParam

    Size for each batch in the optimization process (Default: 64)

    Size for each batch in the optimization process (Default: 64)

    Definition Classes
    AssertionDLApproach
  8. def beforeTraining(spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  9. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  10. def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
    Definition Classes
    CheckLicense
  11. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  12. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  13. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  14. val chunkCol: Param[String]

    Column with extracted NER chunks

    Column with extracted NER chunks

    Definition Classes
    AssertionDLApproach
  15. final def clear(param: Param[_]): AssertionDLApproach.this.type
    Definition Classes
    Params
  16. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  17. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

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

    Definition Classes
    AssertionDLApproach
  18. final def copy(extra: ParamMap): Estimator[nlp.annotators.assertion.dl.AssertionDLModel]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  19. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. val description: String
    Definition Classes
    AssertionDLApproach → AnnotatorApproach
  22. 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
  23. val dropout: FloatParam

    Dropout at the output of each layer (Default: 0.05f)

    Dropout at the output of each layer (Default: 0.05f)

    Definition Classes
    AssertionDLApproach
  24. val enableOutputLogs: BooleanParam

    Whether to output to annotators log folder (Default: false)

    Whether to output to annotators log folder (Default: false)

    Definition Classes
    AssertionDLApproach
  25. val endCol: Param[String]

    Column with token number for last target token

    Column with token number for last target token

    Definition Classes
    AssertionDLApproach
  26. val epochs: IntParam

    Number of epochs for the optimization process (Default: 5)

    Number of epochs for the optimization process (Default: 5)

    Definition Classes
    AssertionDLApproach
  27. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  28. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  29. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  30. def explainParams(): String
    Definition Classes
    Params
  31. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  32. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  33. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  34. final def fit(dataset: Dataset[_]): nlp.annotators.assertion.dl.AssertionDLModel
    Definition Classes
    AnnotatorApproach → Estimator
  35. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[nlp.annotators.assertion.dl.AssertionDLModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  36. def fit(dataset: Dataset[_], paramMap: ParamMap): nlp.annotators.assertion.dl.AssertionDLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  37. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): nlp.annotators.assertion.dl.AssertionDLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  38. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  39. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  40. def getConfigProtoBytes: Option[Array[Byte]]

    ConfigProto from tensorflow, serialized into byte array.

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

    Definition Classes
    AssertionDLApproach
  41. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. def getEnableOutputLogs: Boolean

    Whether to output to annotators log folder

    Whether to output to annotators log folder

    Definition Classes
    AssertionDLApproach
  43. def getIncludeConfidence: Boolean

    whether to include confidence scores in annotation metadata

    whether to include confidence scores in annotation metadata

    Definition Classes
    AssertionDLApproach
  44. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  45. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  46. def getLogName: String
    Definition Classes
    Logging
  47. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  48. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  49. def getOutputLogsPath: String

    Folder path to save training logs

    Folder path to save training logs

    Definition Classes
    AssertionDLApproach
  50. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  51. def getScopeWindow: (Int, Int)

    Get scope window

    Get scope window

    Definition Classes
    AssertionDLApproach
  52. val graphFile: Param[String]

    File path that contain external graph file.

    File path that contain external graph file. When specified, the provided file will be used, and no graph search will happen. The path can be a local file path, a distributed file path (HDFS, DBFS), or a cloud storage (S3).

    Definition Classes
    AssertionDLApproach
  53. val graphFolder: Param[String]

    Folder path that contain external graph files.

    Folder path that contain external graph files.

    Folder path that contain external graph files. The path can a local file path, a distributed file path (HDFS, DBFS), or a cloud storage (S3).

    Definition Classes
    AssertionDLApproach
  54. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  55. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  56. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  57. val includeConfidence: BooleanParam

    Whether to include confidence scores in annotation metadata

    Whether to include confidence scores in annotation metadata

    Definition Classes
    AssertionDLApproach
  58. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  59. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. val inputAnnotatorTypes: Array[String]

    Input Annotator Types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Input Annotator Types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Definition Classes
    AssertionDLApproach → HasInputAnnotationCols
  61. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  62. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  63. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  64. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  65. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  66. val labelCol: Param[String]

    Column with one label per document.

    Column with one label per document. Example of possible values: “present”, “absent”, “hypothetical”, “conditional”, “associated_with_other_person”, etc.

    Definition Classes
    AssertionDLApproach
  67. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  68. val learningRate: FloatParam

    Learning rate for the optimization process (Default: 0.0012f)

    Learning rate for the optimization process (Default: 0.0012f)

    Definition Classes
    AssertionDLApproach
  69. def log(value: ⇒ String, minLevel: Level): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  71. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  78. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. val logger: Logger
    Attributes
    protected
    Definition Classes
    Logging
  83. val maxSentLen: IntParam

    Max possible length of a sentence, must match graph model (Default: 250)

    Max possible length of a sentence, must match graph model (Default: 250)

    Definition Classes
    AssertionDLApproach
  84. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  85. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  86. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  87. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  88. def onTrained(model: nlp.annotators.assertion.dl.AssertionDLModel, spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  89. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  90. val outputAnnotatorType: AnnotatorType

    Output annotator type: ASSERTION

    Output annotator type: ASSERTION

    Definition Classes
    AssertionDLApproach → HasOutputAnnotatorType
  91. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  92. def outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  93. val outputLogsPath: Param[String]

    Folder path to save training logs.

    Folder path to save training logs. If no path is specified, the logs won't be stored in disk. The path can be a local file path, a distributed file path (HDFS, DBFS), or a cloud storage (S3).

    Definition Classes
    AssertionDLApproach
  94. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  95. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  96. val scopeWindow: IntArrayParam

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

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

    Definition Classes
    AssertionDLApproach
  97. final def set(paramPair: ParamPair[_]): AssertionDLApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  98. final def set(param: String, value: Any): AssertionDLApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  99. final def set[T](param: Param[T], value: T): AssertionDLApproach.this.type
    Definition Classes
    Params
  100. def setBatchSize(size: Int): AssertionDLApproach.this.type

    Size for each batch in the optimization process

    Size for each batch in the optimization process

    Definition Classes
    AssertionDLApproach
  101. def setChunkCol(c: String): AssertionDLApproach.this.type

    Column with extracted NER chunks

    Column with extracted NER chunks

    Definition Classes
    AssertionDLApproach
  102. def setConfigProtoBytes(bytes: Array[Int]): AssertionDLApproach.this.type

    ConfigProto from tensorflow, serialized into byte array.

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

    Definition Classes
    AssertionDLApproach
  103. final def setDefault(paramPairs: ParamPair[_]*): AssertionDLApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  104. final def setDefault[T](param: Param[T], value: T): AssertionDLApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. def setDoExceptionHandling(value: Boolean): AssertionDLApproach.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
  106. def setDropout(factor: Float): AssertionDLApproach.this.type

    Dropout at the output of each layer

    Dropout at the output of each layer

    Definition Classes
    AssertionDLApproach
  107. def setEnableOutputLogs(v: Boolean): AssertionDLApproach.this.type

    Whether to output to annotators log folder

    Whether to output to annotators log folder

    Definition Classes
    AssertionDLApproach
  108. def setEndCol(e: String): AssertionDLApproach.this.type

    Column with token number for last target token

    Column with token number for last target token

    Definition Classes
    AssertionDLApproach
  109. def setEpochs(number: Int): AssertionDLApproach.this.type

    Number of epochs for the optimization process

    Number of epochs for the optimization process

    Definition Classes
    AssertionDLApproach
  110. def setGraphFile(path: String): AssertionDLApproach.this.type

    Folder path that contain external graph files

    Folder path that contain external graph files

    Definition Classes
    AssertionDLApproach
  111. def setGraphFolder(path: String): AssertionDLApproach.this.type

    Folder path that contain external graph files

    Folder path that contain external graph files

    Definition Classes
    AssertionDLApproach
  112. def setIncludeConfidence(value: Boolean): AssertionDLApproach.this.type

    Whether to include confidence scores in annotation metadata

    Whether to include confidence scores in annotation metadata

    Definition Classes
    AssertionDLApproach
  113. final def setInputCols(value: String*): AssertionDLApproach.this.type
    Definition Classes
    HasInputAnnotationCols
  114. def setInputCols(value: Array[String]): AssertionDLApproach.this.type
    Definition Classes
    HasInputAnnotationCols
  115. def setLabelCol(label: String): AssertionDLApproach.this.type

    Column with one label per document

    Column with one label per document

    Definition Classes
    AssertionDLApproach
  116. def setLazyAnnotator(value: Boolean): AssertionDLApproach.this.type
    Definition Classes
    CanBeLazy
  117. def setLearningRate(rate: Float): AssertionDLApproach.this.type

    Learning rate for the optimization process

    Learning rate for the optimization process

    Definition Classes
    AssertionDLApproach
  118. def setMaxSentLen(len: Int): AssertionDLApproach.this.type

    Max possible length of a sentence, must match graph model

    Max possible length of a sentence, must match graph model

    Definition Classes
    AssertionDLApproach
  119. final def setOutputCol(value: String): AssertionDLApproach.this.type
    Definition Classes
    HasOutputAnnotationCol
  120. def setOutputLogsPath(v: String): AssertionDLApproach.this.type

    Folder path to save training logs

    Folder path to save training logs

    Definition Classes
    AssertionDLApproach
  121. def setScopeWindow(window: (Int, Int)): AssertionDLApproach.this.type

    Max possible length of a sentence.

    Max possible length of a sentence.

    Definition Classes
    AssertionDLApproach
  122. def setStartCol(s: String): AssertionDLApproach.this.type

    Column with token number for first target token

    Column with token number for first target token

    Definition Classes
    AssertionDLApproach
  123. def setValidationSplit(validationSplit: Float): AssertionDLApproach.this.type

    Choose the proportion of training dataset to be validated against the model on each Epoch.

    Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

    Definition Classes
    AssertionDLApproach
  124. def setVerbose(verbose: Level): AssertionDLApproach.this.type

    Level of verbosity during training

    Level of verbosity during training

    Definition Classes
    AssertionDLApproach
  125. val startCol: Param[String]

    Column with token number for first target token

    Column with token number for first target token

    Definition Classes
    AssertionDLApproach
  126. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  127. val testDataset: ExternalResourceParam

    Path to test dataset.

    Path to test dataset. If set used to calculate statistic on it during training

    Definition Classes
    AssertionDLApproach
  128. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  129. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): AssertionDLModel

    Trains the dataset with recursive pipeline and uses methods trainWithChunk() and trainwithStartEnd() The choice of training happens based on the startCol value of the DL Approach

    Trains the dataset with recursive pipeline and uses methods trainWithChunk() and trainwithStartEnd() The choice of training happens based on the startCol value of the DL Approach

    dataset

    a collection of inputs to train

    recursivePipeline

    an instance of PipelineModel

    returns

    an instance of trained AssertionDLModel

    Definition Classes
    AssertionDLApproach → AssertionDLApproach → AnnotatorApproach
  130. final def transformSchema(schema: StructType): StructType
    Definition Classes
    AnnotatorApproach → PipelineStage
  131. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  132. val uid: String
    Definition Classes
    AssertionDLApproach → AssertionDLApproach → Identifiable
  133. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  134. val validationSplit: FloatParam

    The proportion of training dataset to be used as validation set.

    The proportion of training dataset to be used as validation set.

    The model will be validated against this dataset on each Epoch and will not be used for training. The value should be between 0.0 and 1.0.

    Definition Classes
    AssertionDLApproach
  135. val verbose: IntParam

    Level of verbosity during training

    Level of verbosity during training

    Definition Classes
    AssertionDLApproach
  136. val verboseLevel: Level
    Definition Classes
    AssertionDLApproach → Logging
  137. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  138. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  139. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  140. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from nlp.annotators.assertion.dl.AssertionDLApproach

Inherited from CheckLicense

Inherited from HandleExceptionParams

Inherited from Logging

Inherited from AnnotatorApproach[nlp.annotators.assertion.dl.AssertionDLModel]

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[nlp.annotators.assertion.dl.AssertionDLModel]

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