class TensorflowBertTokenClassification extends Serializable
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new
TensorflowBertTokenClassification(tensorflowWrapper: TensorflowWrapper, sentenceStartTokenId: Int, sentenceEndTokenId: Int, configProtoBytes: Option[Array[Byte]] = None, tags: Map[String, Int], signatures: Option[Map[String, String]] = None)
- tensorflowWrapper
Bert Model wrapper with TensorFlow Wrapper
- sentenceStartTokenId
Id of sentence start Token
- sentenceEndTokenId
Id of sentence end Token.
- configProtoBytes
Configuration for TensorFlow session
- tags
labels which model was trained with in order
- signatures
TF v2 signatures in Spark NLP
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def
##(): Int
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- val _tfBertSignatures: Map[String, String]
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def
encode(sentences: Seq[(WordpieceTokenizedSentence, Int)], maxSequenceLength: Int): Seq[Array[Int]]
Encode the input sequence to indexes IDs adding padding where necessary
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- def predict(sentences: Seq[WordpieceTokenizedSentence], originalTokenSentences: Seq[TokenizedSentence], batchSize: Int, maxSentenceLength: Int): Seq[Annotation]
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- def tag(batch: Seq[Array[Int]]): Seq[Array[Array[Float]]]
- val tensorflowWrapper: TensorflowWrapper
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