def _update_bias_stats():
    'A method to update the bias stats.'
    grads_sum = math_ops.reduce_sum(gradients, 0)
    hess = gradients_impl.gradients(grads_sum, predictions, name='Hessians', colocate_gradients_with_ops=False, gate_gradients=0, aggregation_method=None)[0]
    hess_sum = math_ops.reduce_sum(hess, 0)
    partition_ids = math_ops.range(self._logits_dimension)
    feature_ids = array_ops.zeros([self._logits_dimension, 2], dtype=dtypes.int64)
    add_stats_op = bias_stats_accumulator.add(ensemble_stamp, partition_ids, feature_ids, grads_sum, hess_sum)
    return control_flow_ops.group(*[add_stats_op], name='update_bias_stats')
A method to update the bias stats.
def _update_bias_stats():
    
    grads_sum = math_ops.reduce_sum(gradients, 0)
    hess = gradients_impl.gradients(grads_sum, predictions, name='Hessians', colocate_gradients_with_ops=False, gate_gradients=0, aggregation_method=None)[0]
    hess_sum = math_ops.reduce_sum(hess, 0)
    partition_ids = math_ops.range(self._logits_dimension)
    feature_ids = array_ops.zeros([self._logits_dimension, 2], dtype=dtypes.int64)
    add_stats_op = bias_stats_accumulator.add(ensemble_stamp, partition_ids, feature_ids, grads_sum, hess_sum)
    return control_flow_ops.group(*[add_stats_op], name='update_bias_stats')