code: def _gamma_from_loc_scale(loc, log_scale):
      return gamma.Gamma(
          concentration=(loc / tf.exp(log_scale)) ** 2,
          rate=loc / (tf.exp(log_scale)) ** 2,
      )
  
file_path: probability/tensorflow_probability/python/experimental/util/deferred_module_test.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.util import deferred_module
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling a global function with example usage: _gamma_from_loc_scale(loc, log_scale) and returns: gamma