code: def test_parametric_function_1d(
      inshape, kernel, multiplier, outshape
  ):
      base_axis = len(inshape) - 2
      sample_channels = inshape[base_axis]
      outmap_channels = sample_channels * multiplier
      x = nn.Variable(inshape)
      y = PF.depthwise_convolution(x, kernel, multiplier=multiplier)
      p = nn.get_parameters()
      assert y.shape == outshape
      assert p["depthwise_conv/W"].shape == (outmap_channels,) + kernel
      assert p["depthwise_conv/b"].shape == (outmap_channels,)
      nn.clear_parameters()
  
file_path: nnabla/python/test/function/test_depthwise_convolution.py
imports: from __future__ import division
  import pytest
  import numpy
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  import refs
  from nbla_test_utils import list_context
  from nbla_test_utils import function_tester
label_desc: Use image node_id 5 for calling a global function with example usage: test_parametric_function_1d(inshape, kernel, multiplier, outshape) without return types