code: def forward(self, x):
      if self.rf == 1:
          size_out = x.size()[:-1] + (self.nf,)
          x = torch.addmm(self.b, x.view(-1, x.size(-1)), self.w)
          x = x.view(*size_out)
      else:
          raise NotImplementedError
      return x
  
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 2 for calling the Conv1D obj's underlying member method code with example usage: obj.forward(x) and returns: x