import tensorflow as tf

                        # Default initial value of ent_coef when learned
                        init_value = 1.0
                        if '_' in self.ent_coef:
                            init_value = float(self.ent_coef.split('_')[1])
                            assert init_value > 0., "The initial value of ent_coef must be greater than 0"

                        self.log_ent_coef = tf.get_variable('log_ent_coef', dtype=tf.float32,
                                                            initializer=np.log(init_value).astype(np.float32))
                        self.ent_coef = tf.exp(self.log_ent_coef)
                    else:
                        # Force conversion to float
                        # this will throw an error if a malformed string (different from 'auto')
                        # is passed
                        self.ent_coef = float(self.ent_coef)

                with tf.variable_scope("target", reuse=False):
