code: def _masked_conv_init_lens(
      lens: torch.Tensor,
      current_maxlen: int,
      original_maxlen: torch.Tensor,
  ):
      if current_maxlen > original_maxlen:
          new_lens = torch.arange(current_maxlen)
          new_max_lens = torch.tensor(current_maxlen)
      else:
          new_lens = lens
          new_max_lens = original_maxlen
      return new_lens, new_max_lens
  
imports: import math
  from typing import Callable, Iterable, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.nn.init import _calculate_correct_fan
  from torch.nn.modules.utils import _single
  from nemo.collections.common.parts.utils import activation_registry
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.classes.mixins.adapter_mixins import AdapterModuleMixin
  from nemo.utils import logging
label_desc: Use image node_id 9 for calling a global function with example usage: _masked_conv_init_lens(lens, current_maxlen, original_maxlen) and returns: new_lens,  new_max_lens