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1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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3.  final def ==(arg0: Any): Boolean

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4.  final def asInstanceOf[T0]: T0

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5.  def clone(): AnyRef

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6.  def convertWord(str: String, lowercase: Boolean = false): String
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8.  def equals(arg0: Any): Boolean

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9.  def finalize(): Unit

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10.  final def getClass(): Class[_]

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12.  val hyphenPattern: Pattern
13.  final def isInstanceOf[T0]: Boolean

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14.  def loadBansalVectorsForVocabulary(word2vecPath: String, voc: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]
15.  def loadVectorsForVocabulary(word2vecPath: String, voc: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

    Loads vectors for a vocabulary from word2vec, with OOV words having random vectors generated for them.

16.  def makeRandomVectorsForVocabulary(voc: Set[String], dim: Int, inputVectorBias: Boolean): HashMap[String, Array[Float]]
17.  final def ne(arg0: AnyRef): Boolean

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18.  final def notify(): Unit

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19.  final def notifyAll(): Unit

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20.  def readBansalEmbeddings(embeddingsPath: String, words: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]
21.  def readWord2Vec(word2VecPath: String, words: Set[String], inputVectorBias: Boolean): HashMap[String, Array[Float]]

    Reads the vectors in words from the given word2vec path and augments with a bias feature if necessary.

    Reads the vectors in words from the given word2vec path and augments with a bias feature if necessary. The returned map does not include entries for words that are not in the w2v file.

22.  def smartLoadVectorsForVocabulary(word2vecPaths: Seq[String], voc: Set[String], vocCounts: Counter[String, Double] = Counter[String,Double], maxVectorLen: Int = Int.MaxValue, inputVectorBias: Boolean, randomizeUnks: Boolean = true): HashMap[String, Array[Float]]

    Loads vectors from one or more sources in word2vecPaths; these might be in word2vec format (should end in .bin) or C+W/Bansal format (should end in .txt).

    Loads vectors from one or more sources in word2vecPaths; these might be in word2vec format (should end in .bin) or C+W/Bansal format (should end in .txt).

    For each word, vectors are appended from each source. If at least one source is present, others are zeroes. Otherwise, it gets a random vector.

23.  final def synchronized[T0](arg0: ⇒ T0): T0

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24.  def toString(): String

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25.  final def wait(): Unit

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26.  final def wait(arg0: Long, arg1: Int): Unit

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27.  final def wait(arg0: Long): Unit

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