code: def _relaxed_binomial(total_count, probs):
      """
      Returns a moment-matched :class:`~pyro.distributions.Normal` approximating
      a :class:`~pyro.distributions.Binomial` but allowing arbitrary real
      ``total_count`` and lower-bounding variance.
      """
      total_count, probs = broadcast_all(total_count, probs)
  
      mean = probs * total_count
      variance = total_count * probs * (1 - probs)
  
      scale = variance.clamp(min=_RELAX_MIN_VARIANCE).sqrt()
      return dist.Normal(mean, scale)
  
file_path: pyro/pyro/contrib/epidemiology/distributions.py
imports: import math
  from contextlib import contextmanager
  import torch
  from torch.distributions.utils import broadcast_all
  import pyro.distributions
  from pyro.distributions.util import is_validation_enabled
label_desc: Use image node_id 7 for calling a global function with example usage: _relaxed_binomial(total_count, probs) and returns: dist