code: def convolution_1d(
      x, W, b=None, stride=1, pad=0, cover_all=False, dilate=1, groups=1
  ):
      """1-dimensional convolution function.
  
      .. note::
  
          This function calls :func:`~chainer.functions.convolution_nd`
          internally, so see the details of the behavior in
          the documentation of :func:`~chainer.functions.convolution_nd`.
  
      """
      if len(x.shape[2:]) != 1:
          raise ValueError(
              "The number of dimensions under channel dimension of the input "
              "'x' should be 1. But the actual ndim was {}.".format(
                  len(x.shape[2:])
              )
          )
      return convolution_nd(
          x, W, b, stride, pad, cover_all, dilate, groups
      )
  
imports: import numpy
  from six import moves
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import configuration
  from chainer import function_node
  from chainer.functions.connection import convolution_2d
  from chainer import utils
  from chainer.utils import conv
  from chainer.utils import conv_nd
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 2 for calling a global function with example usage: convolution_1d(x, W, b, stride, pad, cover_all, dilate, groups) and returns: convolution_nd