def randomize(self):
tries = 0
while True:
self.type = randomizer.getRandom(self.probabilities)
if tries > 100:
self.force_type = 1
if self.force_type is not None:
self.type = self.force_type
if self.type == 0:
tries += 1
self.value = key_element_list()
self.value.randomize()
elif self.type == 1:
self.value = action_list()
self.value.randomize()
elif self.type == 2:
self.value = entries_list()
self.value.randomize()
elif self.type == 3:
self.opt_annotations = opt_annotations()
self.opt_annotations.randomize()
self.const_initializer = True
self.value = initializer()
self.value.randomize()
elif self.type == 4:
self.opt_annotations = opt_annotations()
self.opt_annotations.randomize()
self.value = initializer()
self.value.randomize()
if not self.filter():
break
def unpack(self, binary_string):
binary_string = ofp_instruction_actions.unpack(self, binary_string)
bytes = self.len - OFP_INSTRUCTION_ACTIONS_BYTES
self.actions = action_list()
binary_string = self.actions.unpack(binary_string, bytes=bytes)
return binary_string
def unpack(self, binary_string):
binary_string = ofp_bucket.unpack(self, binary_string)
self.actions = action_list()
return self.actions.unpack(binary_string)
def __init__(self):
ofp_instruction_actions.__init__(self)
self.type = OFPIT_APPLY_ACTIONS
self.actions = action_list()
self.len = self.__len__()
def __init__(self):
ofp_bucket.__init__(self)
self.actions = action_list()
self.type = None
self.len = self.__len__()
