code: def make_inverse_temperatures(
      n_replica,
      min_nonzero_value,
      zero_final_value=True,
      dtype=np.float32,
  ):
      beta = 10 ** (
          np.linspace(0.0, np.log10(min_nonzero_value), num=n_replica)
      )
      if zero_final_value:
          beta[-1] = 0.0
      return beta.astype(dtype)
  
file_path: probability/tensorflow_probability/python/experimental/mcmc/thermodynamic_integrals_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.mcmc import thermodynamic_integrals
  from tensorflow_probability.python.internal import broadcast_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import diagnostic
  from tensorflow_probability.python.mcmc import hmc
  from tensorflow_probability.python.mcmc import replica_exchange_mc
  from tensorflow_probability.python.mcmc import sample
label_desc: Use image node_id 1 for calling a global function with example usage: make_inverse_temperatures(n_replica, min_nonzero_value, zero_final_value, dtype) and returns: beta