evaluation.py 文件源码

def __init__(self, log_prior, log_joint, prior_sampler,
                 hmc, observed, latent, n_chains=25, n_temperatures=1000,
                 verbose=False):
        # Shape of latent: [chain_axis, num_data, data dims]
        # Construct the tempered objective
        self.n_chains = n_chains
        self.n_temperatures = n_temperatures
        self.verbose = verbose

        with tf.name_scope("AIS"):
            self.temperature = tf.placeholder(tf.float32, shape=[],
                                              name="temperature")

            def log_fn(observed):
                return log_prior(observed) * (1 - self.temperature) + \
                    log_joint(observed) * self.temperature

            self.log_fn = log_fn
            self.log_fn_val = log_fn(merge_dicts(observed, latent))
            self.sample_op, self.hmc_info = hmc.sample(
                log_fn, observed, latent)
            self.init_latent = [tf.assign(z, z_s)
                                for z, z_s in zip(latent.values(),
                                                  prior_sampler.values())]