# Path: ldif/util/file_util.py
# def readlines(p):
# def readbin(p):
# def writebin(p, s):
# def writetxt(p, s):
# def write_np(path, arr):
# def read_grd(path):
# def read_sif_v1(path, verbose=False):
# def read_lines(p):
# def read_image(p):
# def read_npz(p):
# def read_np(p):
# def read_txt_to_np(p):
# def read_py2_pkl(p):
# def write_mesh(path, mesh):
# def read_mesh(path):
# def read_csv(path):
# def read_normals(path_to_dir, im_count=20, leading='_depth'):
# def write_points(path_ext_optional, points):
# def write_grd(path, volume, world2grid=None):
# def write_depth_image(path, depth_image):
# 
# Path: ldif/util/file_util.py
# def readlines(p):
# def readbin(p):
# def writebin(p, s):
# def writetxt(p, s):
# def write_np(path, arr):
# def read_grd(path):
# def read_sif_v1(path, verbose=False):
# def read_lines(p):
# def read_image(p):
# def read_npz(p):
# def read_np(p):
# def read_txt_to_np(p):
# def read_py2_pkl(p):
# def write_mesh(path, mesh):
# def read_mesh(path):
# def read_csv(path):
# def read_normals(path_to_dir, im_count=20, leading='_depth'):
# def write_points(path_ext_optional, points):
# def write_grd(path, volume, world2grid=None):
# def write_depth_image(path, depth_image):


import pickle
import tensorflow as tf
from ldif.util import file_util
from ldif.util.file_util import log
  d = tf_hparams_to_dict(autoencoder_hparams)
  d['h'] = 224
  d['w'] = 224
  d['cnna'] = 's50'
  d['samp'] = 'im1xyzpn'
  d['didx'] = 0
  d['ia'] = 'p'
  d['sc'] = 32
  d['lyr'] = 16
  return tf.contrib.training.HParams(**d)


def write_hparams(hparams, path):
  d = tf_hparams_to_dict(hparams)
  file_util.writebin(path, pickle.dumps(d))
  return


def read_hparams_with_new_backwards_compatible_additions(path):
  """Reads hparams from a file and adds in any new backwards compatible ones."""
  kvs = pickle.loads(file_util.readbin(path))
  log.verbose('Loaded %s' % repr(kvs))
  if 'ident' not in kvs:
    ident = 'sif'  #  A default identifier for old checkpoints.
    log.info('Default ident!')
  else:
    ident = kvs['ident']
  new_additions = backwards_compatible_hparam_defaults(ident)
  for k, v in new_additions.items():
    if k not in kvs:

# Path: ldif/util/file_util.py
# def readlines(p):
# def readbin(p):
# def writebin(p, s):
# def writetxt(p, s):
# def write_np(path, arr):
# def read_grd(path):
# def read_sif_v1(path, verbose=False):
# def read_lines(p):
# def read_image(p):
# def read_npz(p):
# def read_np(p):
# def read_txt_to_np(p):
# def read_py2_pkl(p):
# def write_mesh(path, mesh):
# def read_mesh(path):
# def read_csv(path):
# def read_normals(path_to_dir, im_count=20, leading='_depth'):
# def write_points(path_ext_optional, points):
# def write_grd(path, volume, world2grid=None):
# def write_depth_image(path, depth_image):
# 
# Path: ldif/util/file_util.py
# def readlines(p):
# def readbin(p):
# def writebin(p, s):
# def writetxt(p, s):
# def write_np(path, arr):
# def read_grd(path):
# def read_sif_v1(path, verbose=False):
# def read_lines(p):
# def read_image(p):
# def read_npz(p):
# def read_np(p):
# def read_txt_to_np(p):
# def read_py2_pkl(p):
# def write_mesh(path, mesh):
# def read_mesh(path):
# def read_csv(path):
# def read_normals(path_to_dir, im_count=20, leading='_depth'):
# def write_points(path_ext_optional, points):
# def write_grd(path, volume, world2grid=None):
# def write_depth_image(path, depth_image):


# Path: ldif/model/hparams.py
import pickle
import tensorflow as tf
from ldif.util import file_util
from ldif.util.file_util import log

  d = tf_hparams_to_dict(autoencoder_hparams)
  d['h'] = 224
  d['w'] = 224
  d['cnna'] = 's50'
  d['samp'] = 'im1xyzpn'
  d['didx'] = 0
  d['ia'] = 'p'
  d['sc'] = 32
  d['lyr'] = 16
  return tf.contrib.training.HParams(**d)


def write_hparams(hparams, path):
  d = tf_hparams_to_dict(hparams)
  file_util.writebin(path, pickle.dumps(d))
  return


def read_hparams_with_new_backwards_compatible_additions(path):
  """Reads hparams from a file and adds in any new backwards compatible ones."""
  kvs = pickle.loads(file_util.readbin(path))
  log.verbose('Loaded %s' % repr(kvs))
  if 'ident' not in kvs:
    ident = 'sif'  #  A default identifier for old checkpoints.
    log.info('Default ident!')
  else:
    ident = kvs['ident']
  new_additions = backwards_compatible_hparam_defaults(ident)
  for k, v in new_additions.items():
    if k not in kvs:

      log.verbose('Adding hparam %s:%s since it postdates the checkpoint.' %