code: def create_mask(
      size: int, lengths: torch.LongTensor, inverse: bool = False
  ) -> torch.BoolTensor:
      """
      Create boolean masks of shape len(lenghts) x size.
  
      An entry at (i, j) is True if lengths[i] > j.
  
      Args:
          size (int): size of second dimension
          lengths (torch.LongTensor): tensor of lengths
          inverse (bool, optional): If true, boolean mask is inverted. Defaults to False.
  
      Returns:
          torch.BoolTensor: mask
      """
  
      if inverse:  # return where values are
          return torch.arange(size, device=lengths.device).unsqueeze(
              0
          ) < lengths.unsqueeze(-1)
      else:  # return where no values are
          return torch.arange(size, device=lengths.device).unsqueeze(
              0
          ) >= lengths.unsqueeze(-1)
  
imports: from collections import namedtuple
  from contextlib import redirect_stdout
  import inspect
  import os
  from typing import Any, Callable, Dict, List, Tuple, Union
  import lightning.pytorch
  import torch
  from torch import nn
  from torch.fft import irfft, rfft
  import torch.nn.functional
  from torch.nn.utils import rnn
label_desc: Use image node_id 5 for calling a global function with example usage: create_mask(size, lengths, inverse) and returns: unknown, unknown