text: import tensorflow as tf
  
  from rllab.core.serializable import Serializable
  
  from sandbox.rocky.tf.core.parameterized import Parameterized
  
  from dac.misc.mlp import MLPFunction
  from dac.misc import tf_utils
  
  class MLPPreprocessor(MLPFunction):
      def __init__(self, env_spec, layer_sizes=(128, 16),
                   output_nonlinearity=None, name='observations_preprocessor'):
  
          Parameterized.__init__(self)
          Serializable.quick_init(self, locals())
  
          self._name = name
  
          self._Do = env_spec.observation_space.flat_dim
  
          obs_ph = tf.placeholder(
              tf.float32,
              shape=(None, self._Do),
              name='observations',
          )
  
          self._input_pls = (obs_ph, )
          self._layer_sizes = layer_sizes
          self._output_nonlinearity = output_nonlinearity
  
          self._output_t = self.get_output_for(obs_ph, reuse=tf.AUTO_REUSE)
  