class_docstr: A unit dropout layer that's designed for input of sequence units (e.g., word sequence, char sequence, etc.).
  Given a sequence of unit indices, this layer randomly set some of them to be a replacement id (usually set to be <UNK>).
class_docstr_tok: ["A","unit","dropout","layer","that","'s","designed","for","input","of","sequence","units","(","e.g.",",","word","sequence",",","char","sequence",",","etc.",")",".","Given","a","sequence","of","unit","indices",",","this","layer","randomly","set","some","of","them","to","be","a","replacement","id","(","usually","set","to","be","<","UNK",">",")","."]
code: def __init__(self, dropprob, replacement_id):
      super().__init__()
      self.dropprob = dropprob
      self.replacement_id = replacement_id
  
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 SequenceUnitDropout object from inherited base classes: nn with example: obj = SequenceUnitDropout(dropprob, replacement_id)