code: def test_load_from_8bit(self):
      exporter = QuantizedEmbedding(10, 5, mode="EMA")
      exporter.eval()
      exporter.mode_8bit = True
      state_dict = exporter.state_dict()
      exporter.mode_8bit = False
      importer = QuantizedEmbedding(10, 5, mode="EMA")
      self.assertTrue((exporter.weight != importer.weight).any())
      importer.eval()
      importer.load_state_dict(state_dict, strict=False)
      indices = torch.tensor(np.arange(10))
      self.assertTrue((exporter(indices) == importer(indices)).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 7 for calling the QuantizedEmbeddingTest obj's underlying member method code with example usage: obj.test_load_from_8bit() without return types