text: import numpy as np
  import torch
  import torch.nn as nn
  from torch.autograd import Variable
  from onnx2keras import onnx_to_keras, check_torch_keras_error
  import onnx
  import pytest
  
  from test.utils import convert_and_test
  
  
  class FDiv(nn.Module):
      def __init__(self):
          super(FDiv, self).__init__()
  
      def forward(self, x, y):
          x = x / 2
          y = y / 2
  
          x = x / y
          return x
  
  
  @pytest.mark.repeat(10)
  @pytest.mark.parametrize('change_ordering', [True, False])
  def test_div(change_ordering):
      model = FDiv()
      model.eval()
  
      input_np1 = np.random.uniform(0, 1, (1, 3, 224, 224))
      input_np2 = np.random.uniform(0, 1, (1, 3, 224, 224))
      error = convert_and_test(model, (input_np1, input_np2), verbose=False, change_ordering=change_ordering)
  
  