code: def test_1d_convolution(
      self,
      input_channels,
      output_channels,
      batch_size,
      stride,
      size,
      kernel,
      dilation,
      pad,
      group,
      order,
      use_bias,
      engine,
      force_algo_fwd,
      force_algo_dgrad,
      force_algo_wgrad,
      gc,
      dc,
  ):
      if hiputl.run_in_hip(gc, dc):
          # currently miopen only supports 2d conv
          assume(
              engine != "CUDNN"
          )  # CUDNN is aliased to MIOPEN for HIP
      # TODO: 1D conv in NHWC not implemented for GPU yet.
      assume(order == "NCHW" or gc.device_type == caffe2_pb2.CPU)
      if order == "NHWC":
          dc = [d for d in dc if d.device_type == caffe2_pb2.CPU]
  
      self._nd_convolution(
          1,
          input_channels,
          output_channels,
          batch_size,
          stride,
          size,
          kernel,
          dilation,
          pad,
          group,
          order,
          use_bias,
          engine,
          force_algo_fwd,
          force_algo_dgrad,
          force_algo_wgrad,
          gc,
          dc,
      )
  
imports: import collections
  import functools
  import unittest
  import caffe2.python._import_c_extension
  import caffe2.python.hip_test_util
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import hypothesis.strategies
  import numpy
  from caffe2.proto import caffe2_pb2
  from caffe2.python import brew, core, utils, workspace
  from caffe2.python.model_helper import ModelHelper
  from hypothesis import assume, given, settings
label_desc: Use image node_id 5 for calling the TestConvolution obj's underlying member method code with example usage: obj.test_1d_convolution(input_channels, output_channels, batch_size, stride, size, kernel, dilation, pad, group, order, use_bias, engine, force_algo_fwd, force_algo_dgrad, force_algo_wgrad, gc, dc) without return types