code: def test_int_gelu(self):
      gelu_q = IntGELU(quant_mode=True)
      gelu_dq = nn.GELU()
  
      x_int = torch.arange(-10000, 10001, 1)
      x_scaling_factor = torch.tensor(0.001)
      x = x_int * x_scaling_factor
  
      q, q_scaling_factor = gelu_q(x, x_scaling_factor)
      q_int = q / q_scaling_factor
      dq = gelu_dq(x)
  
      # output of the normal GELU and the quantized GELU should be similar
      self.assertTrue(torch.allclose(q, dq, atol=0.5))
  
      # output of the quantized GELU layer should be integer
      self.assertTrue(torch.allclose(q_int, q_int.round(), atol=1e-4))
  
imports: import copy
  import unittest
  from transformers import IBertConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the IBertModelIntegrationTest obj's underlying member method code with example usage: obj.test_int_gelu() without return types