import tensorflow as tf

        else:
          out = tf.nn.max_pool3d(bottom, ksize=[1,1, FLAGS.pool_kernel, FLAGS.pool_kernel,1], strides=[1,1,FLAGS.pool_stride,FLAGS.pool_stride,1], padding='VALID')
        shape = out.get_shape()
        print('pool{}'.format(l + 1))
        print('\t{} --> {}'.format(bottom.name, out.name))
        print('\t{} --> {}'.format(bottom.get_shape(), out.get_shape()))
      with tf.variable_scope('scale'):
        bottom = out
        if FLAGS.pm[l + 1]  == FLAGS.pm[l]:
          kernel_size = 1 # useless 1x1 pooling
        elif int(FLAGS.pm[l + 1]) < int(FLAGS.pm[l]):
          num_scales_prev = int(FLAGS.pm[l])
