Args:
        feature (any shape):
        num_classes(int): num_category + 1
        class_agnostic_regression (bool): if True, regression to N x 1 x 4

    Returns:
        cls_logits: N x num_class classification logits
        reg_logits: N x num_classx4 or Nx2x4 if class agnostic

def fastrcnn_outputs(feature, num_classes, class_agnostic_regression=False):
    """
    Args:
        feature (any shape):
        num_classes(int): num_category + 1
        class_agnostic_regression (bool): if True, regression to N x 1 x 4

    Returns:
        cls_logits: N x num_class classification logits
        reg_logits: N x num_classx4 or Nx2x4 if class agnostic
    """
    classification = FullyConnected(
        'class', feature, num_classes,
        kernel_initializer=tf.random_normal_initializer(stddev=0.01))
    num_classes_for_box = 1 if class_agnostic_regression else num_classes
    box_regression = FullyConnected(
        'box', feature, num_classes_for_box * 4,
        kernel_initializer=tf.random_normal_initializer(stddev=0.001))
    box_regression = tf.reshape(box_regression, (-1, num_classes_for_box, 4), name='output_box')
    return classification, box_regression