code: def test_relu_api(self):
      X = torch.arange(-5, 5, dtype=torch.float)
      scale = 2.0
      zero_point = 1
      qX = torch.quantize_per_tensor(
          X, scale=scale, zero_point=zero_point, dtype=torch.quint8
      )
      qY = torch.relu(qX)
      qY_hat = F.relu(qX)
      self.assertEqual(qY, qY_hat)
  
file_path: pytorch/test/quantization/core/test_quantized_functional.py
imports: import torch
  import torch.ao.nn.quantized.functional
  import torch.nn.functional
  import numpy
  from hypothesis import assume, given
  from hypothesis import strategies
  from torch.testing._internal.common_quantization import QuantizationTestCase, _make_conv_test_input
  from torch.testing._internal.common_quantized import override_quantized_engine
  from torch.testing._internal.common_utils import IS_PPC, TEST_WITH_UBSAN
label_desc: Use image node_id 1 for calling the TestQuantizedFunctionalOps obj's underlying member method code with example usage: obj.test_relu_api() without return types