code: def _prepare_args(m, s, alpha, c):
      dtype = dtype_util.common_dtype([m, s], dtype_hint=tf.float32)
      m = tf.convert_to_tensor(m, dtype, name="m")
      s = tf.convert_to_tensor(s, dtype, name="s")
      c = tf.cast(c, dtype=dtype, name="c")
      alpha = tf.cast(alpha, dtype=dtype, name="alpha")
      return m, s, alpha, 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 2 for calling a global function with example usage: _prepare_args(m, s, alpha, c) and returns: m,  s,  alpha,  c