class_docstr: Samples a length
class_docstr_tok: ["Samples","a","length"]
code: def __call__(self) -> int:
      return np.random.choice(self.values)
  
imports: import gc
  import random
  import warnings
  from contextlib import contextmanager
  from typing import Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils.rnn import pad_sequence
  from transformers import top_k_top_p_filtering
  from .import_utils import is_npu_available, is_xpu_available
label_desc: Use image node_id 2 for calling the LengthSampler obj's underlying member method code with example usage: obj.__call__() and returns: np