code: def compute_pmf(probabilities: Sequence[float]) -> np.ndarray:
      """Computes probability mass function of Poisson binomial distribution."""
      # Compute coefficients of Probability Generating Function (PGF), which
      # equals to
      # PGF(x) = \product_{p\in ps}(1-p + p*x)
      poisson_bin_probs = np.array([1])
      for p in probabilities:
          next_poisson_bin_probs = np.zeros(len(poisson_bin_probs) + 1)
          next_poisson_bin_probs[:-1] = poisson_bin_probs * (1 - p)
          next_poisson_bin_probs[1:] += poisson_bin_probs * p
          poisson_bin_probs = next_poisson_bin_probs
      return PMF(0, poisson_bin_probs)
  
imports: import numpy
  from scipy.stats import norm
  from typing import Sequence, Tuple
  from dataclasses import dataclass
label_desc: Use image node_id 1 for calling a global function with example usage: compute_pmf(probabilities) and returns: PMF