code: def _get_bsize_nsteps(self, m, x):
      if isinstance(x[0], PackedSequence):
          batch_size = torch.max(x[0].batch_sizes)
          num_steps = x[0].batch_sizes.size(0)
      else:
          if m.batch_first:
              batch_size = x[0].size(0)
              num_steps = x[0].size(1)
          else:
              batch_size = x[0].size(1)
              num_steps = x[0].size(0)
  
      return batch_size, num_steps
  
imports: import functools
  from collections import Counter
  from prettytable import PrettyTable
  import torch
  import torch.nn
  from torch.nn.utils.rnn import PackedSequence
  from nni.compression.base.wrapper import ModuleWrapper
label_desc: Use image node_id 15 for calling the ModelProfiler obj's underlying member method code with example usage: obj._get_bsize_nsteps(m, x) and returns: batch_size,  num_steps