code: def forward(self, x, lens):
      if self.use_mask:
          # Generally will be called by ConvASREncoder, but kept as single gpu backup.
          if x.size(2) > self.max_len:
              self.update_masked_length(x.size(2), device=lens.device)
          x = self.mask_input(x, lens)
  
      # Update lengths
      lens = self.get_seq_len(lens)
  
      # asymmtric pad if necessary
      if self.pad_layer is not None:
          x = self.pad_layer(x)
  
      sh = x.shape
      if self.heads != -1:
          x = x.view(-1, self.heads, sh[-1])
  
      out = self.conv(x)
  
      if self.heads != -1:
          out = out.view(sh[0], self.real_out_channels, -1)
  
      return out, 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 3 for calling the MaskedConv1d obj's underlying member method code with example usage: obj.forward(x, lens) and returns: out,  lens