class_docstr: A variant of dropout layer that consistently drops out the same parameters over time. Also known as the variational dropout. 
  This implementation was modified from the LockedDropout implementation in the flair library (https://github.com/zalandoresearch/flair).
class_docstr_tok: ["A","variant","of","dropout","layer","that","consistently","drops","out","the","same","parameters","over","time",".","Also","known","as","the","variational","dropout",".","This","implementation","was","modified","from","the","LockedDropout","implementation","in","the","flair","library","(","https",":","\/\/github.com\/zalandoresearch\/flair",")","."]
code: def __init__(self, dropprob, batch_first=True):
      super().__init__()
      self.dropprob = dropprob
      self.batch_first = batch_first
  
file_path: stanza/stanza/models/common/dropout.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new LockedDropout object from inherited base classes: nn with example: obj = LockedDropout(dropprob, batch_first)