code: def maybe_cat(tensors, dim, nullable=None):
      """Like torch.cat, but skips elements in `tensors` which are None.
  
      Args:
          tensors: List of tensors (compare torch.cat())
          dim: Dimension along which to concatenate (compare to torch.cat())
          nullable: List of the same length as `tensors`. If specified, throw
              a RuntimeError if the i-th element in `tensors` is None and the
              i-th element in nullable is False.
  
      Returns:
          Concatenation of all tensors in `tensors` along `dim` which are not
          None.
  
      Throws:
          RuntimeError is `nullable` constraint is violated or all alements in
          `tensors` are None.
      """
      if nullable is not None and any(
          (t is None) and not n for t, n in zip(tensors, nullable)
      ):
          raise RuntimeError("Unexpected element in tensors is None.")
      filtered = [t for t in tensors if t is not None]
      if len(filtered) == 1:
          return filtered[0]
      return torch.cat(filtered, dim=dim)
  
imports: import argparse
  import ast
  import os
  import signal
  import threading
  import time
  from typing import Dict, List, Optional, Union
  import torch
  from fairseq import distributed_utils, tasks, utils
  from pytorch_translate.file_io import PathManager
label_desc: Use image node_id 4 for calling a global function with example usage: maybe_cat(tensors, dim, nullable) and returns: torch, filtered