c

com.johnsnowlabs.ml.tensorflow

NerDatasetEncoder

class NerDatasetEncoder extends Serializable

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Instance Constructors

  1. new NerDatasetEncoder(params: DatasetEncoderParams)

Value Members

  1. val char2Id: Map[Char, Int]
  2. val chars: Array[Char]
  3. def convertBatchTags(predictedTags: Array[String], allTags: Array[String], sentenceLength: Array[Int], prob: Option[Seq[Array[Float]]], includeAllConfidenceScores: Boolean): Array[Array[(String, Option[Array[Map[String, String]]])]]

    Converts Tensorflow tags output to 2-dimensional Array with shape: (Batch, Sentence Length).

    Converts Tensorflow tags output to 2-dimensional Array with shape: (Batch, Sentence Length).

    predictedTags

    2-dimensional tensor in plain array

    allTags

    All original tags

    sentenceLength

    Every sentence length (number of words).

    returns

    List of tags for each sentence

  4. def decodeOutputData(tagIds: Array[Int]): Array[String]

    Converts Tag Identifiers to Source Names

    Converts Tag Identifiers to Source Names

    tagIds

    Tag Ids encoded for Tensorflow Model.

    returns

    Tag names

  5. def encodeInputData(sentences: Array[WordpieceEmbeddingsSentence]): NerBatch
  6. def encodeTags(tags: Array[Array[String]]): Array[Array[Int]]

    Converts Tag names to Identifiers

    Converts Tag names to Identifiers

    tags

    batches of labels/classes for each sentence/document

    returns

    batches of tag ids for each sentence/document

  7. def getOrElse[T](source: Array[T], i: Int, value: ⇒ T): T
  8. val params: DatasetEncoderParams
  9. val tag2Id: Map[String, Int]
  10. val tags: Array[String]