#===============================================================================
# Copyright (c) 2015, Max Zwiessele
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#===============================================================================
[docs]class Pickleable(object):
"""
Make an object pickleable (See python doc 'pickling').
This class allows for pickling support by Memento pattern.
_getstate returns a memento of the class, which gets pickled.
_setstate(<memento>) (re-)sets the state of the class to the memento
"""
def __init__(self, *a, **kw):
super(Pickleable, self).__init__()
#===========================================================================
# Pickling operations
#===========================================================================
[docs] def pickle(self, f, protocol=-1):
"""
:param f: either filename or open file object to write to.
if it is an open buffer, you have to make sure to close
it properly.
:param protocol: pickling protocol to use, python-pickle for details.
"""
try: #Py2
import cPickle as pickle
if isinstance(f, basestring):
with open(f, 'wb') as f:
pickle.dump(self, f, protocol)
else:
pickle.dump(self, f, protocol)
except ImportError: #python3
import pickle
if isinstance(f, str):
with open(f, 'wb') as f:
pickle.dump(self, f, protocol)
else:
pickle.dump(self, f, protocol)
#===========================================================================
# copy and pickling
#===========================================================================
[docs] def copy(self, memo=None, which=None):
"""
Returns a (deep) copy of the current parameter handle.
All connections to parents of the copy will be cut.
:param dict memo: memo for deepcopy
:param Parameterized which: parameterized object which started the copy process [default: self]
"""
#raise NotImplementedError, "Copy is not yet implemented, TODO: Observable hierarchy"
if memo is None:
memo = {}
import copy
# the next part makes sure that we do not include parents in any form:
parents = []
if which is None:
which = self
which.traverse_parents(parents.append) # collect parents
for p in parents:
if not id(p) in memo :memo[id(p)] = None # set all parents to be None, so they will not be copied
if not id(self.gradient) in memo:memo[id(self.gradient)] = None # reset the gradient
if not id(self._fixes_) in memo :memo[id(self._fixes_)] = None # fixes have to be reset, as this is now highest parent
copy = copy.deepcopy(self, memo) # and start the copy
copy._parent_index_ = None
copy._trigger_params_changed()
return copy
def __deepcopy__(self, memo):
s = self.__new__(self.__class__) # fresh instance
memo[id(self)] = s # be sure to break all cycles --> self is already done
import copy
s.__setstate__(copy.deepcopy(self.__getstate__(), memo)) # standard copy
return s
def __getstate__(self):
ignore_list = ['_param_array_', # parameters get set from bottom to top
'_gradient_array_', # as well as gradients
'_optimizer_copy_',
'logger',
'observers',
'_fixes_', # and fixes
'cache', # never pickle the cache
]
dc = dict()
#py3 fix
#for k,v in self.__dict__.iteritems():
for k,v in self.__dict__.items():
if k not in ignore_list:
dc[k] = v
return dc
def __setstate__(self, state):
self.__dict__.update(state)
from .lists_and_dicts import ObserverList
from ..caching import FunctionCache
self.observers = ObserverList()
self.cache = FunctionCache()
self._setup_observers()
self._optimizer_copy_transformed = False