code: def forward(self, x, inplace: bool = False):
      if self.p > 0 and (self.training or self.apply_during_inference):
          return F.dropout(x, p=self.p, training=True, inplace=inplace)
      else:
          return x
  
file_path: fairseq/fairseq/modules/fairseq_dropout.py
imports: import logging
  from typing import List, Optional
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the FairseqDropout obj's underlying member method code with example usage: obj.forward(x, inplace) and returns: F, x