tensorflow

Type Members

1. case class DatasetEncoderParams(tags: List[String], chars: List[Char], emptyVector: List[Float], embeddingsDim: Int, defaultTag: String = "O") extends Product with Serializable

   

2. trait Logging extends AnyRef

   

3. class NerBatch extends AnyRef

   

   Batch that contains data in Tensorflow input format.

4. class NerDatasetEncoder extends Serializable

   

5. trait ReadTensorflowModel extends AnyRef

   

6. case class SentenceGrouper[T](getLength: (T) ⇒ Int, sizes: Array[Int] = Array(5, 10, 20, 50))(implicit evidence$1: ClassTag[T]) extends Product with Serializable

   

7. class TensorResources extends AnyRef

   

8. class TensorflowBert extends Serializable

   

9. class TensorflowElmo extends Serializable

   

   This class is used to calculate ELMO embeddings for For Sequence Batches of TokenizedSentences.

   This class is used to calculate ELMO embeddings for For Sequence Batches of TokenizedSentences.

   https://tfhub.dev/google/elmo/3 * word_emb: the character-based word representations with shape [batch_size, max_length, 512]. == word_emb * lstm_outputs1: the first LSTM hidden state with shape [batch_size, max_length, 1024]. === lstm_outputs1 * lstm_outputs2: the second LSTM hidden state with shape [batch_size, max_length, 1024]. === lstm_outputs2 * elmo: the weighted sum of the 3 layers, where the weights are trainable. This tensor has shape [batch_size, max_length, 1024] == elmo

10. class TensorflowNer extends Serializable with Logging

    

11. class TensorflowUSE extends Serializable

    

12. class TensorflowWrapper extends Serializable

    

13. case class Variables(variables: Array[Byte], index: Array[Byte]) extends Product with Serializable

    

14. trait WriteTensorflowModel extends AnyRef