code: def normal(low, high, q):
      """Samples values from a clipped normal (Gaussian) distribution quantized to q."""
      # mu/sigma are computed from low/high such that ~99.7% of samples are in range
      f, mu, sigma = np.inf, (low + high) / 2, (high - low) / 6
      while not low <= f <= high:
          f = np.random.normal(mu, sigma)
      return quantize(f, q, np.round)
  
file_path: pycls/pycls/sweep/random.py
imports: from decimal import Decimal
  import matplotlib.pyplot
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: normal(low, high, q) and returns: quantize