code: def __init__(self, nf, rf, nx):
      super(Conv1D, self).__init__()
      self.rf = rf
      self.nf = nf
      if rf == 1:
          w = torch.empty(nx, nf)
          torch.nn.init.normal_(w, std=0.02)
          self.w = Parameter(w)
          self.b = Parameter(torch.zeros(nf))
      else:
          raise NotImplementedError
  
imports: from __future__ import with_statement
  from __future__ import division
  from __future__ import absolute_import
  import copy
  import io
  import json
  import logging
  import math
  import re
  import tarfile
  import numpy
  import torch
  from torch.nn import Parameter
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.file_utils import cached_path
  from allennlp.common.from_params import FromParams
  from io import open
label_desc: Use image node_id 1 to create a new Conv1D object from inherited base classes: torch.nn with example: obj = Conv1D(nf, rf, nx)