code: def _common(m, s, alpha, c):
      m, s, alpha, c = _prepare_args(m, s, alpha, c)
      m_ = m[..., tf.newaxis]
      s_ = s[..., tf.newaxis]
      one_over_rho = tf.math.rsqrt(c**2 + s_**2)
      m_over_rho = m_ * one_over_rho
      cdf, pdf = _get_cdf_pdf(c)
      return alpha, m_over_rho, cdf, pdf, one_over_rho, m_, s_, c
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 4 for calling a global function with example usage: _common(m, s, alpha, c) and returns: alpha,  m_over_rho,  cdf,  pdf,  one_over_rho,  m_,  s_,  c