import tensorflow as tf

    FLAGS.pm= FLAGS.pm.split('-')

  num_layers = len(FLAGS.pm) - 1
  print(num_layers)
  for l in range(num_layers):
    with tf.variable_scope('layer{}'.format(l)):
      with tf.variable_scope('conv'):
        if l == 0:
          bottom = x
          W = weight_variable([1, FLAGS.conv_kernel, FLAGS.conv_kernel, 1, FLAGS.feats_per_layer])
        else:
          if out.get_shape()[2] < FLAGS.conv_kernel:
