class TensorflowSpell extends Logging with Serializable
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Instance Constructors
- new TensorflowSpell(tensorflow: TensorflowWrapper, verboseLevel: nlp.annotators.ner.Verbose.Value)
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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- val checkPointStep: Int
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def
clone(): AnyRef
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- protected[lang]
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- val contextIds: String
- val contextWordIds: String
- val dropoutRate: String
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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- val finalLearningRateKey: String
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def
finalize(): Unit
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- @throws( classOf[java.lang.Throwable] )
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final
def
getClass(): Class[_]
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- @native()
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def
getLogName: String
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- Logging
- val globalStepKey: String
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def
hashCode(): Int
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- @native()
- val initKey: String
- val initialLearningRateKey: String
- val inputLens: String
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final
def
isInstanceOf[T0]: Boolean
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- val learningRate: String
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def
log(value: ⇒ String, minLevel: Level): Unit
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- Logging
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val
logger: Logger
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- protected
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- Logging
- val lossKey: String
- val losses: String
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def pplEachWord(dataset: Array[Array[Int]], cids: Array[Array[Int]], cwids: Array[Array[Int]], configProtoBytes: Option[Array[Byte]] = None): Array[Float]
- def predict(dataset: Array[Array[Int]], cids: Array[Array[Int]], cwids: Array[Array[Int]], configProtoBytes: Option[Array[Byte]] = None): Iterator[Float]
- def predict_(dataset: Array[Array[Int]], cids: Array[Array[Int]], cwids: Array[Array[Int]], candCids: Array[Int], candWids: Array[Int], configProtoBytes: Option[Array[Byte]] = None): List[Float]
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
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- val tensorflow: TensorflowWrapper
- val testCids: String
- val testWids: String
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def
toString(): String
- Definition Classes
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- def train(train: ⇒ Iterator[Array[LangModelSentence]], valid: ⇒ Iterator[Array[LangModelSentence]], epochs: Int, batchSize: Int, initialRate: Float, finalRate: Float): Unit
- val updatesKey: String
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val
verboseLevel: nlp.annotators.ner.Verbose.Value
- Definition Classes
- TensorflowSpell → Logging
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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- val wordIds: String