code: def get_seq_len(self, lens):
      if self.same_padding or self.same_padding_asymmetric:
          return lens
  
      if self.pad_layer is None:
          return (
              torch.div(
                  lens
                  + 2 * self.conv.padding[0]
                  - self.conv.dilation[0]
                  * (self.conv.kernel_size[0] - 1)
                  - 1,
                  self.conv.stride[0],
                  rounding_mode="trunc",
              )
              + 1
          )
      else:
          return (
              torch.div(
                  lens
                  + sum(self._padding)
                  - self.conv.dilation[0]
                  * (self.conv.kernel_size[0] - 1)
                  - 1,
                  self.conv.stride[0],
                  rounding_mode="trunc",
              )
              + 1
          )
  
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 2 for calling the MaskedConv1d obj's underlying member method code with example usage: obj.get_seq_len(lens) and returns: lens, unknown, unknown