code: def test_quantization_forward(self):
      fake_quantize = FakeLinearQuantizationWithSTE().apply
      x = torch.randn(1, 100)
      scale = (2 ** (8 - 1) - 1) / np.abs(x).max()
      self.assertTrue(
          (
              fake_quantize(x, scale, 8)
              == fake_quantize_np(x, scale, 8)
          ).all()
      )
  
imports: import unittest
  import numpy
  import torch
  from torch import nn
  from torch.nn import functional
  from nlp_architect.nn.torch.quantization import FakeLinearQuantizationWithSTE, QuantizedLinear, get_dynamic_scale, get_scale, QuantizedEmbedding
label_desc: Use image node_id 1 for calling the FakeLinearQuantizationWithSTETester obj's underlying member method code with example usage: obj.test_quantization_forward() without return types