BOREP
- class lightautoml.text.dl_transformers.BOREP(embed_size=300, proj_size=300, pooling='mean', max_length=200, init='orthogonal', pos_encoding=False, **kwargs)[source]
Bases:
Module
Class to compute Bag of Random Embedding Projections sentence embeddings from words embeddings.
Bag of Random Embedding Projections sentence embeddings.
- Parameters:
Note
There are several pooling types:
‘max’: Maximum on seq_len dimension for non masked inputs.
‘mean’: Mean on seq_len dimension for non masked inputs.
‘sum’: Sum on seq_len dimension for non masked inputs.
For init parameter there are several options:
‘orthogonal’: Orthogonal init.
‘normal’: Normal with std 0.1.
‘uniform’: Uniform from -0.1 to 0.1.
‘kaiming’: Uniform kaiming init.
‘xavier’: Uniform xavier init.