code: def test_start_quantization_delay(self):
      quantization_delay = 2
      qlinear = QuantizedLinear(
          10, 5, start_step=quantization_delay, mode="DYNAMIC"
      )
      linear = nn.Linear(10, 5)
      linear.weight.data = qlinear.weight
      linear.bias.data = qlinear.bias
      for _ in range(quantization_delay):
          x = torch.randn(3, 10)
          qy = qlinear(x)
          y = linear(x)
          self.assertTrue((y == qy).all())
      qy = qlinear(x)
      self.assertFalse((y == qy).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 5 for calling the QuantizedLinearTest obj's underlying member method code with example usage: obj.test_start_quantization_delay() without return types