class_docstr: A word dropout layer that's designed for embedded inputs (e.g., any inputs to an LSTM layer).
  Given a batch of embedded inputs, this layer randomly set some of them to be a replacement state.
  Note that this layer assumes the last dimension of the input to be the hidden dimension of a unit.
class_docstr_tok: ["A","word","dropout","layer","that","'s","designed","for","embedded","inputs","(","e.g.",",","any","inputs","to","an","LSTM","layer",")",".","Given","a","batch","of","embedded","inputs",",","this","layer","randomly","set","some","of","them","to","be","a","replacement","state",".","Note","that","this","layer","assumes","the","last","dimension","of","the","input","to","be","the","hidden","dimension","of","a","unit","."]
code: def extra_repr(self):
      return "p={}".format(self.dropprob)
  
file_path: stanza/stanza/models/common/dropout.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the WordDropout obj's underlying member method code with example usage: obj.extra_repr() and returns: str