text: import os
  import copy
  
  import numpy as np
  import tensorflow as tf
  import sys
  import json
  
  
  sys.path.append('curiosity')
  
  # import curiosity.utils.base as base
  from curiosity.models import future_pred_symmetric_coupled_with_below
  import curiosity.models.future_pred_symmetric_coupled_with_below as modelsource
  # import curiosity.datasources.images_futures_and_actions as datasource
  CODE_ROOT = os.environ['CODE_ROOT']
  cfgfile = os.path.join(CODE_ROOT, 
                         'curiosity/curiosity/configs/future_test_config_b.cfg')
  
  
  from curiosity.utils.loadsave import (get_checkpoint_path,
                                        preprocess_config,
                                        postprocess_config)
  
  
  
  cfg0 = postprocess_config(json.load(open(cfgfile)))
  # print cfg0
  # cfg0 = {}
  seed = 0
  rng = np.random.RandomState(seed=seed)
  
  
  batch_size = 64
  IMAGE_SIZE = 360
  NUM_CHANNELS = 3
  ACTION_LENGTH = 10
  current_node = tf.placeholder(
    tf.float32,
    shape=(batch_size, IMAGE_SIZE, IMAGE_SIZE, NUM_CHANNELS))
  
  future_node = tf.placeholder(
      tf.float32,
    shape=(batch_size, IMAGE_SIZE, IMAGE_SIZE, NUM_CHANNELS))
  
  actions_node = tf.placeholder(tf.float32,
                              shape=(batch_size,
                                     ACTION_LENGTH))
  
  time_node = tf.placeholder(tf.float32,
                           shape=(batch_size, 1))
  
  inputs = {'current' : current_node, 'future' : future_node, 'actions' : actions_node, 'time' : time_node}
  
  
  outputs, params = modelsource.model_tfutils(inputs, rng, cfg = cfg0, train = True, slippage = .5)
  
  all_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
  
  for var in all_vars:
  	print var.name
  
  real_encode_depth = len([k for k in params.keys() if 'enc' in k])
  
  for i in range(real_encode_depth + 1):
  	print(outputs['pred']['pred' + str(i)])
  	print(outputs['future']['future' + str(i)])
  