code: def _skip_encoder_out(encoder, encoder_out, mask):
      if not mask.any():
          return encoder_out
      else:
          return encoder.reorder_encoder_out(
              encoder_out, mask.nonzero(as_tuple=False).squeeze()
          )
  
file_path: fairseq/fairseq/models/nat/levenshtein_utils.py
imports: import torch
  from fairseq.utils import new_arange
label_desc: Use image node_id 8 for calling a global function with example usage: _skip_encoder_out(encoder, encoder_out, mask) and returns: encoder_out, encoder