class_docstr: Hubert Pretrain model
class_docstr_tok: ["Hubert","Pretrain","model"]
code: def compute_correct(
      self,
      logits,
  ):
      if logits.numel() == 0:
          corr, count = 0, 0
      else:
          assert logits.dim() > 1, logits.shape
          max = logits.argmax(-1) == 0
          min = logits.argmin(-1) == 0
          both = max & min
          corr = max.long().sum().item() - both.long().sum().item()
          count = max.numel()
      return corr, count
  
imports: import logging
  from contextlib import contextmanager
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  from packaging.version import parse
  from typeguard import check_argument_types
  from espnet2.asr.encoder.abs_encoder import AbsEncoder
  from espnet2.asr.frontend.abs_frontend import AbsFrontend
  from espnet2.asr.preencoder.abs_preencoder import AbsPreEncoder
  from espnet2.asr.specaug.abs_specaug import AbsSpecAug
  from espnet2.hubert.hubert_loss import HubertPretrainLoss
  from espnet2.layers.abs_normalize import AbsNormalize
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet2.train.abs_espnet_model import AbsESPnetModel
  from espnet.nets.e2e_asr_common import ErrorCalculator
label_desc: Use image node_id 6 for calling the HubertPretrainModel obj's underlying member method code with example usage: obj.compute_correct(logits) and returns: corr,  count