docstr: Checks whether tqdm can be gracefully used with a dataloader
  1) should have `__len__` property defined
  2) calling len(x) should not throw errors.
docstr_tok: ["Checks","whether","tqdm","can","be","gracefully","used","with","a","dataloader","1",")","should","have","`","__len__","`","property","defined","2",")","calling","len","(","x",")","should","not","throw","errors","."]
code: def _can_use_tqdm(self, dataloader: torch.utils.data.DataLoader):
      """
      Checks whether tqdm can be gracefully used with a dataloader
      1) should have `__len__` property defined
      2) calling len(x) should not throw errors.
      """
      use_tqdm = hasattr(dataloader, "__len__")
  
      try:
          _ = len(dataloader)
      except (AttributeError, TypeError, NotImplementedError):
          use_tqdm = False
      return use_tqdm
  
file_path: mmf/mmf/trainers/core/evaluation_loop.py
imports: import logging
  from abc import ABC
  from typing import Any, Dict, Tuple, Type
  import torch
  import tqdm
  from mmf.common.meter import Meter
  from mmf.common.report import Report
  from mmf.common.sample import to_device
  from mmf.utils.distributed import gather_tensor, is_main, is_xla
label_desc: Use image node_id 3 for calling the TrainerEvaluationLoopMixin obj's underlying member method code with example usage: obj._can_use_tqdm(dataloader) and returns: use_tqdm