code: def compute_mu_poisson(
      *, steps: int, noise_multiplier: float, sample_rate: float
  ) -> float:
      """
      Compute mu from uniform subsampling.
  
      Args:
          steps: Number of steps taken
          noise_multiplier: Noise multiplier (sigma)
          sample_rate: Sample rate
  
      Returns:
          mu
      """
  
      return (
          np.sqrt(np.exp(noise_multiplier ** (-2)) - 1)
          * np.sqrt(steps)
          * sample_rate
      )
  
file_path: opacus/opacus/accountants/analysis/gdp.py
imports: import numpy
  from scipy import optimize
  from scipy.stats import norm
label_desc: Use image node_id 2 for calling a global function with example usage: compute_mu_poisson() and returns: unknown