def _get_default_variable_store():
store = get_collection(_VARSTORE_KEY)
if store:
return store[0]
# create a new store
store = variable_store()
add_to_collection(_VARSTORE_KEY, store)
return store
def get_variable_scope():
# get_collection returns a list
scope = get_collection(_VARSCOPE_KEY)
if scope:
# only 1 element in the list
return scope[0]
# create a new scope
scope = var_scope(False)
add_to_collection(_VARSCOPE_KEY, scope)
return scope
def get_regularization_loss(scopes):
if scopes is None:
scopes = [None]
if not isinstance(scopes, (tuple, list)):
raise ValueError("parameter: scopes should be either a tuple or list")
print scopes
loss_list = [
loss for scope in scopes
for loss in get_collection(_REGULARIZATION_LOSSES_KEYS, scope)
]
loss_list = list(set(loss_list))
if not loss_list:
return None
return reduce(theano.tensor.add, loss_list)
def trainable_variables(scope=None):
return get_collection(_TRAINABLE_VARIABLES_KEY, scope)
def global_variables():
return get_collection(_GLOBAL_VARIABLES_KEY)
def trainable_variables():
return get_collection(_TRAINABLE_VARIABLES_KEY)
def get_updates(key="training"):
updates_list = get_collection(_SCAN_UPDATES_KEYS + "/" + key)
return reduce(merge_updates, [OrderedDict()] + list(updates_list))