code: def quantize_np(x, scale, bits):
      return np.clip(
          np.round(x * scale),
          -(2 ** (bits - 1) - 1),
          2 ** (bits - 1) - 1,
      )
  
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 2 for calling a global function with example usage: quantize_np(x, scale, bits) and returns: np