code: def __init__(self, encoder_layer, num_layers, d_model):
      super(LocalformerEncoder, self).__init__()
      self.layers = _get_clones(encoder_layer, num_layers)
      self.conv = _get_clones(
          nn.Conv1d(d_model, d_model, 3, 1, 1), num_layers
      )
      self.num_layers = num_layers
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  import pandas
  from typing import Text, Union
  import copy
  import math
  from ...utils import get_or_create_path
  from ...log import get_module_logger
  import torch
  import torch.nn
  import torch.optim
  from ...model.base import Model
  from ...data.dataset import DatasetH
  from ...data.dataset.handler import DataHandlerLP
  from torch.nn.modules.container import ModuleList
label_desc: Use image node_id 1 to create a new LocalformerEncoder object from inherited base classes: nn with example: obj = LocalformerEncoder(encoder_layer, num_layers, d_model)