object BertEncoder extends Serializable
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- def apply[S](maxLength: Int, vocabularySize: Int, segmentVocabularySize: Int, numBlocks: Int, embeddingDim: Int, attentionHiddenPerHeadDim: Int, attentionNumHeads: Int, mlpHiddenDim: Int, dropout: Double, padToken: Long, tOpt: STenOptions, linearized: Boolean)(implicit arg0: Sc[S]): BertEncoder
Factory for the encoder module of Bert
Factory for the encoder module of Bert
Input is
(tokens, segments)
wheretokens
andsegments
are both (batch,num tokens) long tensor.- maxLength
maximum num token length
- vocabularySize
vocabulary size
- numBlocks
number of transformer blocks to create
- embeddingDim
input embedding dimension
- attentionHiddenPerHeadDim
size of hidden attention dimension of each attention head
- attentionNumHeads
number of attention heads
- mlpHiddenDim
size of hidden dimension of the two layer perceptron
- dropout
dropout rate
- padToken
pad token, (batch, seq) positions where
tokens
==padToken
are ignored, padding is not the same as masking- tOpt
tensor options
- returns
a module
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- implicit val load: Load[BertEncoder]
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- implicit val trainingMode: TrainingMode[BertEncoder]
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