code: def compute_eps_poisson(
      *,
      steps: int,
      noise_multiplier: float,
      sample_rate: float,
      delta: float,
  ) -> float:
      """
      Compute epsilon given delta from inverse dual of Poisson subsampling
  
      Args:
          steps: Number of steps taken
          noise_multiplier: Noise multiplier (sigma)
          sample_rate: Sample rate
          delta: Target delta
  
      Returns:
          eps
      """
  
      return eps_from_mu(
          mu=compute_mu_poisson(
              steps=steps,
              noise_multiplier=noise_multiplier,
              sample_rate=sample_rate,
          ),
          delta=delta,
      )
  
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 6 for calling a global function with example usage: compute_eps_poisson() and returns: eps_from_mu