Unit-level magnitude pruning.

def unit_targeting(w, k):
  """Unit-level magnitude pruning."""
  k = tf.to_int32(k)
  w_shape = shape_list(w)
  size = tf.to_int32(tf.reduce_prod(w_shape[:-1]))
  w = tf.reshape(w, [size, w_shape[-1]])

  norm = tf.norm(w, axis=0)
  thres = tf.contrib.framework.sort(norm, axis=0)[k]
  mask = to_float(thres >= norm)[None, :]
  mask = tf.tile(mask, [size, 1])

  return tf.reshape(mask, w_shape)