def main(argv):
"""
Expects command line input:
python generate-traffic.py config_file.txt my_ip pkts_per_min
"""
# Parse command line args
config_file = argv[1]
my_ip = argv[2]
pkts_per_min = int(argv[3])
# Time to wait between sending packets to satisfy pkts_per_min arg
time_to_wait = (1.0/pkts_per_min) * 60.0
# Parse the config file into dictionary
config_dict = util.parse_config(config_file)
# Get a list of destination nodes
dests = config_dict["dests"]
dests.remove(my_ip)
# Make UDP socket
udpPort = 44000
try:
udpSocket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
except socket.error, msg:
print "Failed to create socket with error: " + msg
sys.exit()
def main():
parser = argparse.ArgumentParser()
arguments = [
("preprocess", preprocess_dataset,
"Preprocess samples - cleaning/filtering of invalid data."),
("split", split_dataset,
"Split dataset in separate folds for training/validation/testing."),
("pretrain", prepare_embeddings,
"Precompute input representations from unlabeled/training data."),
("prepare_input", prepare_input,
"Convert raw inputs to numpy compatible data types."),
("train", train, "Train currently selected model."),
("test", test, "Run available model on evaluation data.")
# ("analyse", analyse_dataset), # WIP
# ("extract_embeddings", extract_embeddings), # WIP
]
for arg, _, description in arguments:
parser.add_argument('--{}'.format(arg),
action='store_true',
help=description)
params = parser.parse_args()
args = parse_config("config.json")
setup_logging(args)
set_random_seed(args)
for arg, fun, _ in arguments:
if hasattr(params, arg) and getattr(params, arg):
logging.info("Performing {} operation..".format(arg))
fun(args)
def parse_kiosk_conf():
kiosk_conf=util.parse_config(ini_file, 'UNIBOX')
if type(kiosk_conf) is dict:
extern_conf_file = kiosk_conf['ubkiosk_dir'] + 'Kiosk.conf'
extern_conf = util.parse_config(extern_conf_file, '*')
if type(extern_conf) is dict:
kiosk_conf.update(extern_conf)
else:
kiosk_conf['kioskid']=0
kiosk_conf['ownerid']=0
log.error(kiosk_conf['kiosk_conf_file']+' config file error')
else:
return {}
return kiosk_conf
def reduce_ops(config_path: str,
enable_type_reduction: bool = False,
use_cuda: bool = True):
'''
Reduce op kernel implementations.
:param config_path: Path to configuration file that specifies the ops to include
:param enable_type_reduction: Whether per operator type reduction is enabled
:param use_cuda: Whether to reduce op kernels for the CUDA provider
'''
required_ops, op_type_usage_manager, globally_allowed_types = parse_config(
config_path, enable_type_reduction)
if globally_allowed_types is not None:
globally_allowed_types = _validated_globally_allowed_types(
globally_allowed_types)
_process_provider_registrations(ort_root, use_cuda, required_ops,
op_type_usage_manager,
globally_allowed_types)
if op_type_usage_manager is not None:
type_control_cpp_code = op_type_usage_manager.get_cpp_entries()
elif globally_allowed_types is not None:
type_control_cpp_code = [
"ORT_SPECIFY_OP_KERNEL_GLOBAL_ALLOWED_TYPES({});".format(", ".join(
sorted(globally_allowed_types)))
]
else:
type_control_cpp_code = []
_insert_type_control_cpp_code(ort_root, type_control_cpp_code)
def reduce_ops(config_path: str,
build_dir: str,
enable_type_reduction: bool = False,
use_cuda: bool = True):
'''
Reduce op kernel implementations.
:param config_path: Path to configuration file that specifies the ops to include
:param build_dir: Path to the build directory. The op reduction files will be generated under the build directory.
:param enable_type_reduction: Whether per operator type reduction is enabled
:param use_cuda: Whether to reduce op kernels for the CUDA provider
'''
build_dir = Path(build_dir).resolve()
build_dir.mkdir(parents=True, exist_ok=True)
required_ops, op_type_impl_filter = parse_config(config_path,
enable_type_reduction)
# delete any existing generated files first
op_reduction_root = _get_op_reduction_file_path(ORT_ROOT, build_dir)
if op_reduction_root.is_dir():
log.info(
f"Deleting existing op reduction file root directory: {op_reduction_root}"
)
shutil.rmtree(op_reduction_root)
_generate_provider_registrations(ORT_ROOT, build_dir, use_cuda,
required_ops, op_type_impl_filter)
type_control_cpp_code = op_type_impl_filter.get_cpp_entries(
) if op_type_impl_filter is not None else []
_generate_type_control_overrides(ORT_ROOT, build_dir,
type_control_cpp_code)
def parse_kiosk_conf():
kiosk_conf = util.parse_config(ini_file, 'UNIBOX')
if type(kiosk_conf) is dict:
extern_conf_file = kiosk_conf['ubkiosk_dir'] + 'Kiosk.conf'
extern_conf = util.parse_config(extern_conf_file, '*')
if type(extern_conf) is dict:
kiosk_conf.update(extern_conf)
else:
kiosk_conf['kioskid'] = 0
kiosk_conf['ownerid'] = 0
log.error(kiosk_conf['kiosk_conf_file'] + ' config file error')
else:
return {}
return kiosk_conf
def _load(self):
config_filename = "config.ini"
self.config = util.parse_config(config_filename)
#Set up logging
self.logger = util.logger(self.config['loglevel'], self.config['logfile'])
self.logger.info("Loaded config")
def exclude_unused_ops_and_types(config_path, enable_type_reduction=False, use_cuda=True):
required_ops, op_type_usage_manager = parse_config(config_path, enable_type_reduction)
registration_files = op_registration_utils.get_kernel_registration_files(ort_root, use_cuda)
_exclude_unused_ops_and_types_in_registrations(required_ops, op_type_usage_manager, registration_files)
_generate_required_types_cpp_code(ort_root, op_type_usage_manager)
def __init__(self, target_list):
"""Index builder"""
self.config = util.parse_config('core.cfg')
self.context = self.__update_context(target_list)
tfile = util.view_mapper.get('index')
tlookup = TemplateLookup(directories = ['.'],
output_encoding='utf-8',
encoding_errors='replace')
self.template = Template(filename = os.path.join('design', tfile),
lookup = tlookup)
def main(opt):
opt = parse_config(opt, TEST)
pl_logger = logging.getLogger("lightning")
pl_logger.propagate = False
# passing `valid_ds` will overwrite `ds`
if opt[VALID_DATA][INPUT]:
console.log(
'[[ WARN ]] Found `valid_ds` in arguments. The value of `ds` will be overwrited by `valid_ds`.'
)
opt[DATA] = opt[VALID_DATA]
ModelClass = parse_model_class(opt[RUNTIME][MODELNAME])
ckpt = opt[CHECKPOINT_PATH]
assert ckpt
model = ModelClass.load_from_checkpoint(ckpt, opt=opt)
model.opt[IMG_DIRPATH] = model.build_test_res_dir()
console.log(f'Loading model from: {ckpt}')
transform = parseAugmentation(opt)
if opt[AUGMENTATION][CROP]:
console.log(
f'[yellow]WRAN: You are testing the model but aug.crop is {opt[AUGMENTATION][CROP]}. Ignore the crop? (Y/n) [/yellow]'
)
res = input()
if res == 'n':
console.log('Testing with cropped data...')
else:
console.log('Ignore and set transform=None...')
transform = torchvision.transforms.ToTensor()
ds = ImagesDataset(opt, ds_type=DATA, transform=transform)
dataloader = torch.utils.data.DataLoader(
ds,
batch_size=1,
shuffle=False,
num_workers=opt[DATALOADER_NUM_WORKER])
trainer = Trainer(gpus=opt[GPU],
distributed_backend='dp',
precision=opt[RUNTIME_PRECISION])
# test.
beg = time.time()
trainer.test(model, dataloader)
console.log(
f'[ TIMER ] Total time usage: {time.time() - beg}, #Dataset sample num: {len(ds)}'
)
console.log('[ PATH ] The results are in :')
console.log(model.opt[IMG_DIRPATH])
def reduce_ops(config_path: str, enable_type_reduction: bool = False, use_cuda: bool = True):
'''
Reduce op kernel implementations.
:param config_path: Path to configuration file that specifies the ops to include
:param enable_type_reduction: Whether per operator type reduction is enabled
:param use_cuda: Whether to reduce op kernels for the CUDA provider
'''
required_ops, op_type_impl_filter = parse_config(config_path, enable_type_reduction)
_process_provider_registrations(ort_root, use_cuda, required_ops, op_type_impl_filter)
if enable_type_reduction:
type_control_cpp_code = op_type_impl_filter.get_cpp_entries() if op_type_impl_filter is not None else []
_insert_type_control_cpp_code(ort_root, type_control_cpp_code)
def _load(self):
config_filename = "config.ini"
self.config = util.parse_config(config_filename)
#Set up logging
self.logger = util.logger(self.config['loglevel'], self.config['logfile'])
self.logger.info("Loaded config")
#Read file and store header and content
with open(self.name, 'r') as f:
self.raw_header, self.raw_content = f.read().split('---')
self.logger.info("Read raw header and content")
self.header = util.parse_header(self.raw_header)
self.logger.info("Parsed header into a dict")
def update_tabsint_plugins(input):
""" Updates just the tabsint specific plugins in the project """
ut.log.info("[BUILD]: Updating tabsint plugins")
config = ut.parse_config()
if input.tabsint_plugins_src:
add_tabsint_plugins(config["plugins"], cordova=False, docs=False)
return
# remove the tabsint_plugins folder from www
rm_tabsint_plugins()
rm_tabsint_plugin_dependencies(config["plugins"])
add_tabsint_plugins(config["plugins"])
add_tabsint_plugin_dependencies(config["plugins"])
def _load(self):
config_filename = "config.ini"
self.config = util.parse_config(config_filename)
#Set up logging
self.logger = util.logger(self.config['loglevel'],
self.config['logfile'])
self.logger.info("Loaded config")
#Read file and store header and content
with open(self.name, 'r') as f:
self.raw_header, self.raw_content = f.read().split('---')
self.logger.info("Read raw header and content")
self.header = util.parse_header(self.raw_header)
self.logger.info("Parsed header into a dict")
def __init__(self, name, target_list, rss = False):
"""Index builder"""
self.config = util.parse_config()
self.name = name
self.rss = rss
self.tagprefix = 'tags'
self.context = self.__update_context(target_list)
if not rss:
tfile = util.view_mapper.get('index')
else:
tfile = util.view_mapper.get('rss')
tlookup = TemplateLookup(directories = ['.'],
output_encoding='utf-8',
encoding_errors='replace')
self.template = Template(filename = os.path.join(self.config.get('designdir', 'design'), tfile),
lookup = tlookup)
def get_app_version():
# gen version num automatic
ver=util.parse_config(ini_file, 'UNIBOX')
if ver and ver['version'] != '':
return ver['version']
else:
try:
git_tags=os.popen('git tag').read().strip('\n')
if git_tags:
# get last tag
lastest_ver=git_tags.split('\n')[-1]
# save lastest_ver into extern file
util.update_config(ini_file, {'version': lastest_ver}, 'UNIBOX')
return lastest_ver
except Exception, e:
# fake initial ver
return 'v0.0.1'
def get_app_version():
# gen version num automatic
ver = util.parse_config(ini_file, 'UNIBOX')
if ver and ver['version'] != '':
return ver['version']
else:
try:
git_tags = os.popen('git tag').read().strip('\n')
if git_tags:
# get last tag
lastest_ver = git_tags.split('\n')[-1]
# save lastest_ver into extern file
util.update_config(ini_file, {'version': lastest_ver},
'UNIBOX')
return lastest_ver
except Exception, e:
# fake initial ver
return 'v0.0.1'
def __init__(self, inpath):
"""Read the infile and populate the object"""
# First patse the config and extract data from infile
self.inpath = inpath
self.config = util.parse_config()
with open(inpath) as infh:
raw_header, self.content = infh.read().split('\n' + self.config.get('separator', '---') + '\n', 1)
# Parse the header and populate the context with this
# information
self.context = self.__update_context(util.parse_header(raw_header))
# Get a template ready to write
tfile = util.view_mapper.get(self.context.get('view', 'single'))
tlookup = TemplateLookup(directories = ['.'],
output_encoding='utf-8',
encoding_errors='replace')
self.template = Template(filename = os.path.join(self.config.get('designdir', 'design'), tfile),
lookup = tlookup)
def reduce_ops(
config_path: str,
build_dir: str,
enable_type_reduction: bool,
use_cuda: bool,
is_extended_minimal_build_or_higher: bool,
):
"""
Reduce op kernel implementations.
:param config_path: Path to configuration file that specifies the ops to include
:param build_dir: Path to the build directory. The op reduction files will be generated under the build directory.
:param enable_type_reduction: Whether per operator type reduction is enabled
:param use_cuda: Whether to reduce op kernels for the CUDA provider
:param is_extended_minimal_build_or_higher: Whether this build has at least the features of an extended minimal
build enabled.
"""
build_dir = Path(build_dir).resolve()
build_dir.mkdir(parents=True, exist_ok=True)
required_ops, op_type_impl_filter = parse_config(config_path,
enable_type_reduction)
if is_extended_minimal_build_or_higher:
required_ops, op_type_impl_filter = _adapt_filters_for_extended_minimal_build(
required_ops, op_type_impl_filter)
# delete any existing generated files first
op_reduction_root = _get_op_reduction_root(build_dir)
if op_reduction_root.is_dir():
log.info(
f"Deleting existing op reduction file root directory: {op_reduction_root}"
)
shutil.rmtree(op_reduction_root)
_generate_provider_registrations(ORT_ROOT, build_dir, use_cuda,
required_ops, op_type_impl_filter)
type_control_cpp_code = op_type_impl_filter.get_cpp_entries(
) if op_type_impl_filter is not None else []
_generate_type_control_overrides(ORT_ROOT, build_dir,
type_control_cpp_code)
def main(args):
"""
Expects command line input: python traffic-simulator.py config_file.txt my_ip
"""
config_filename = str(args[1])
my_ip = str(args[2])
# First, parse the config file
config_dict = util.parse_config(config_filename)
# Instantiate this traffic light
traffic_light = TrafficLight(config_dict, my_ip)
dir_to_mac_dict = util.match_MAC_to_direction(traffic_light.router, config_dict)
# Make seperate process to listen for packets
packet_listener = multiprocessing.Process(target=packet_sniff, \
args=(dir_to_mac_dict, traffic_light.north_queue, \
traffic_light.east_queue, traffic_light.south_queue, \
traffic_light.west_queue))
packet_listener.start()
traffic_light.start()
def main(config):
opt = parse_config(config, TRAIN)
# logging
console.log('Running config:', opt, log_locals=False)
pl_logger = logging.getLogger("lightning")
pl_logger.propagate = False
# init model:
ModelClass = parse_model_class(opt[RUNTIME][MODELNAME])
if opt[CHECKPOINT_PATH]:
model = ModelClass.load_from_checkpoint(opt[CHECKPOINT_PATH], opt=opt)
console.log(f'Loading model from: {opt[CHECKPOINT_PATH]}')
else:
model = ModelClass(opt)
# Loading data:
transform = parseAugmentation(opt)
dataset = ImagesDataset(opt, ds_type=DATA, transform=transform)
console.log('Finish loading data.')
sample_input_batch = dataset[0][INPUT].unsqueeze(0)
# only support one input argument in model.forward
dynamic_ax = {'input': {2: 'H', 3: 'W'}, 'output': {2: 'H', 3: 'W'}}
fpath = f"../onnx/{opt[NAME]}.onnx"
model.to_onnx(
fpath,
sample_input_batch,
export_params=True,
verbose=True,
do_constant_folding=True,
input_names=['input'], # the model's input names
output_names=['output'], # the model's output names
opset_version=12,
dynamic_axes=dynamic_ax)
console.log(f'[[ DONE ]] ONNX file {fpath} exported.')
def check_tabsint_plugins(input):
""" Checks locally installed cordova plugins against the required list in plugins.json and tabsintConfig.json"""
ut.log.info("[BUILD]: Checking tabsint plugins")
# if tabsint plugins directory is not there, then run the full update plugins script
if not os.path.isdir("../www/tabsint_plugins"):
ut.log.info("[BUILD]: No tabsint_plugins directory found")
update_tabsint_plugins(input)
else:
config = ut.parse_config()
tp_dir = set(
os.walk("../www/tabsint_plugins").next()[1]
) # list the directory contents of tabsint_plugins, only dirs, not files
tp = set(config["plugins"].keys())
missing_pl = list(tp - tp_dir)
extra_pl = list(tp_dir - tp)
if len(missing_pl) > 0:
ut.log.info("[BUILD]: Missing the following tabsint plugins: {0}".format(missing_pl))
update_tabsint_plugins(input)
elif len(extra_pl) > 0:
ut.log.info("[BUILD]: Installed tabsint plugins not found in config: {0}".format(extra_pl))
update_tabsint_plugins(input)
def test_parse_config(self):
config = util.parse_config('core.cfg')
assert config.get('basedir', None) == "/home/artagnon/dev/rejourn"
def main():
#Parsing level from parameters and parsing main config:
level_name = None
world_index = 0
world = World(WORLDS[world_index])
user_supplied_level = False
parse_config()
getlevel = False
Variables.vdict["devmode"] = False
if len(sys.argv) > 1:
for arg in sys.argv:
if getlevel:
try:
level_name = arg
user_supplied_level = True
end_trigger = END_NEXT_LEVEL
menu_choice = MENU_QUIT
except:
error_message("Incorrect command line parameters")
level_name = None
elif arg == "-l":
getlevel = True
elif arg == "-dev":
Variables.vdict["devmode"] = True
Variables.vdict["verbose"] = True
elif arg == "-v":
Variables.vdict["verbose"] = True
#Initializing pygame and screen
pygame.init()
screen = pygame.display.set_mode((SCREEN_WIDTH,SCREEN_HEIGHT))
caption = "Which way is up?"
if (Variables.vdict["devmode"]):
caption = caption + " - developer mode"
pygame.display.set_caption(caption)
apply_fullscreen_setting(screen)
if (pygame.joystick.get_count() > 0):
joystick = pygame.joystick.Joystick(0)
joystick.init()
else:
joystick = None
score = Score(0)
done = False
if not user_supplied_level:
if (Variables.vdict["unlocked" + WORLDS[0]] == 0): # Nothing unlocked, go straight to the game
end_trigger = END_NEXT_LEVEL
menu_choice = MENU_QUIT
level_name = world.get_level()
else: # Go to the menu first
end_trigger = END_MENU
menu_choice = 0
bgscreen = None
#Menu and level changing loop, actual game code is in game.py:
while not done:
if end_trigger == END_NEXT_LEVEL:
if user_supplied_level:
end_trigger = game.run(screen, level_name, world.index, score, joystick)
if end_trigger == END_NEXT_LEVEL:
user_supplied_level = False
end_trigger = END_WIN
else:
end_trigger = game.run(screen, level_name, world.index, score, joystick)
if end_trigger == END_NEXT_LEVEL:
if world.is_next_level():
level_name = world.get_level()
else:
end_trigger = END_WIN
elif end_trigger == END_QUIT:
display_bg("quit", screen)
end_trigger = END_MENU
bgscreen = screen.copy()
if end_trigger == END_LOSE:
display_bg("lose", screen)
end_trigger = END_MENU
menu_choice = world.index - 1
bgscreen = screen.copy()
elif end_trigger == END_WIN:
display_bg("victory", screen)
end_trigger = END_MENU
menu_choice = 0
bgscreen = screen.copy()
elif end_trigger == END_QUIT or end_trigger == END_HARD_QUIT:
done = True
elif end_trigger == END_MENU:
prev_score = score.score
prev_time = score.time
prev_levels = score.levels
score = Score(0)
if prev_score != 0:
menu = Mainmenu(screen, prev_score, world, bgscreen, prev_time, prev_levels)
else:
menu = Mainmenu(screen, None, world, bgscreen)
menu_choice = menu.run(menu_choice)
if menu_choice == MENU_QUIT:
end_trigger = END_QUIT
elif menu_choice == MENU_SOUND:
Variables.vdict["sound"] = not Variables.vdict["sound"]
end_trigger = END_MENU
elif menu_choice == MENU_DIALOGUE:
Variables.vdict["dialogue"] = not Variables.vdict["dialogue"]
end_trigger = END_MENU
elif menu_choice == MENU_FULLSCREEN:
Variables.vdict["fullscreen"] = not Variables.vdict["fullscreen"]
end_trigger = END_MENU
apply_fullscreen_setting(screen)
elif menu_choice == MENU_WORLD:
world_index += 1
if world_index >= len(WORLDS):
world_index = 0
world = World(WORLDS[world_index])
end_trigger = END_MENU
else:
level_name = world.get_level(menu_choice)
end_trigger = END_NEXT_LEVEL
write_config()
write_log()
return
def test_parse_config(self):
config = util.parse_config()
assert config.get("indir", None)
assert config.get("outdir", None)
def main():
global w_init, w_menu
w_init = sg.Window(title="Modular Macro Menu", layout=gen_layout_init())
while True:
event, val = w_init.Read()
if event == sg.WIN_CLOSED or event == "Cancel":
return 0
elif event == "btn_load":
w_init["fname_error"].Update(visible=False)
if not val["fname"]:
w_init["fname_error"].Update(value="No config selected.")
w_init["fname_error"].Update(visible=True)
else:
try:
config = util.parse_config(val["fname"])
assert config
break
except:
w_init["fname_error"].Update(
value="{} was not loaded correctly.".format(
os.path.basename(val["fname"])))
w_init["fname_error"].Update(visible=True)
menu_params = config.pop("MenuParams")
hotkeys = {}
loaded_macros = []
for k, v in config.items():
try:
x = macro.Macro(**v)
if x.hotkey not in hotkeys.keys():
hotkeys[x.hotkey] = x.run_macro
loaded_macros.append(x)
else:
print(
"Failed to load Macro '{}'. Reason: WARNING::Duplicate Hotkey {} found!"
.format(k, x.hotkey))
except Exception as e:
print("Failed to load Macro '{}'. Reason: {}".format(k, str(e)))
config["MenuParams"] = menu_params
w_menu = sg.Window(title="Modular Macro Menu",
layout=gen_layout_menu(config, loaded_macros),
text_justification="center",
element_justification="center")
t = threading.Thread(target=util.establish_keyboard_hook, args=(hotkeys, ))
t.daemon = True
t.start()
w_init.close()
while True:
event, val = w_menu.Read()
if event == sg.WIN_CLOSED or event == "Cancel":
return 0
elif event == "event_trigger":
macro_name = w_menu["event_trigger"].metadata
try:
status = macro_name.split(":::")[-1]
macro_name = ":::".join(macro_name.split(":::")[:-1])
if status == "running":
w_menu[macro_name +
":::status"].Update(background_color=GREEN)
w_menu[macro_name + ":::status"].Update(value="Active")
else:
w_menu[macro_name +
":::status"].Update(background_color=RED)
w_menu[macro_name + ":::status"].Update(value="Inactive")
except AttributeError as e:
print(e)
pass
elif event == "Exit":
return 0
elif event == "Go Back":
return -1
elif event == "Open Docs":
util.open_help()
elif event == "Toggle Freeze":
macro._FROZEN = not macro._FROZEN
if macro._FROZEN:
w_menu["menu_title"].Update(value="FROZEN")
w_menu["menu_title"].Update(text_color=LIGHT_BLUE)
else:
w_menu["menu_title"].Update(
value=config["MenuParams"]["menu_name"])
w_menu["menu_title"].Update(text_color=BLACK)
else:
elem = event.split(":::")[-1]
macro_name = ":::".join(event.split(":::")[:-1])
if elem and macro_name:
if elem in ["name", "status", "hotkey", "desc", "vs"]:
w_menu[macro_name + ":::hotkey"].Update(visible=True)
w_menu[macro_name + ":::desc"].Update(visible=True)
cur_state = w_menu[macro_name + ":::desc"].metadata
if cur_state:
w_menu[macro_name + ":::hotkey"].hide_row()
w_menu[macro_name + ":::desc"].hide_row()
else:
w_menu[macro_name + ":::hotkey"].unhide_row()
w_menu[macro_name + ":::desc"].unhide_row()
cur_state = not cur_state
w_menu[macro_name + ":::desc"].metadata = cur_state
def main():
#Parsing level from parameters:
level = 0
user_supplied_level = False
parse_config()
if len(sys.argv) > 1:
for arg in sys.argv:
if level == -1:
try:
level = int(arg)
user_supplied_level = True
except:
print "Error: incorrect level number"
level = 0
elif arg == "-l":
level = -1
#Initializing pygame and screen
pygame.init()
print "Which way is up starting up."
screen = pygame.display.set_mode((SCREEN_WIDTH,SCREEN_HEIGHT))
pygame.display.set_caption("Which way is up?")
if (pygame.joystick.get_count() > 0):
joystick = pygame.joystick.Joystick(0)
joystick.init()
else:
joystick = None
score = Score(0)
done = False
if (Variables.vdict["unlocked"] == 0) or user_supplied_level: # Go straight to the game
end_trigger = END_NEXT_LEVEL
menu_choice = -2
else: # Go to the menu first
end_trigger = END_MENU
menu_choice = 0
#Menu and level changing loop, actual game code is in game.py:
while not done:
if end_trigger == END_NEXT_LEVEL:
if level < TOTAL_LEVELS or user_supplied_level:
end_trigger = game.run(screen, level, score, joystick)
level += 1
if end_trigger == END_QUIT:
end_trigger = END_MENU
else:
end_trigger = END_WIN
if end_trigger == END_LOSE:
display_bg("lose", screen)
end_trigger = END_MENU
elif end_trigger == END_WIN:
display_bg("victory", screen)
end_trigger = END_MENU
elif end_trigger == END_QUIT or end_trigger == END_HARD_QUIT:
done = True
elif end_trigger == END_MENU:
prev_score = score.score
score = Score(0)
if prev_score != 0:
menu = Menu(screen, prev_score)
else:
menu = Menu(screen)
menu_choice = menu.run(menu_choice)
if menu_choice == MENU_QUIT:
end_trigger = END_QUIT
elif menu_choice == MENU_SOUND:
Variables.vdict["sound"] = not Variables.vdict["sound"]
end_trigger = END_MENU
elif menu_choice == MENU_DIALOGUE:
Variables.vdict["dialogue"] = not Variables.vdict["dialogue"]
end_trigger = END_MENU
else:
level = menu_choice
end_trigger = END_NEXT_LEVEL
else:
if user_supplied_level:
user_supplied_level = False
end_trigger = END_WIN
else:
if Variables.vdict["unlocked"] < level:
Variables.vdict["unlocked"] = level
print "Unlocked level " + str(Variables.vdict["unlocked"])
write_config()
return
def main(config):
opt = parse_config(config, TRAIN)
# update debug config (if in debug mode)
if opt[DEBUG]:
debug_config = {
DATALOADER_NUM_WORKER: 0,
NAME: DEBUG,
LOG_EVERY: 1,
VALID_EVERY: 1,
NUM_EPOCH: 2
}
opt.update(debug_config)
console.log(
'[red]>>>> [[ WARN ]] You are in debug mode, update configs. <<<<[/red]'
)
console.log(debug_config)
console.log(
'[red]>>>> [[ WARN ]] You are in debug mode, update configs. <<<<[/red]'
)
# logging
console.log('Running config:', opt, log_locals=False)
opt[LOG_DIRPATH], opt[IMG_DIRPATH] = configLogging(TRAIN, opt)
pl_logger = logging.getLogger("lightning")
pl_logger.propagate = False
# init model:
ModelClass = parse_model_class(opt[RUNTIME][MODELNAME])
ckpt = opt[CHECKPOINT_PATH]
if ckpt:
model = ModelClass.load_from_checkpoint(ckpt, opt=opt)
console.log(f'Loading model from: {ckpt}')
else:
model = ModelClass(opt)
# Loading data:
transform = parseAugmentation(opt)
training_dataset = ImagesDataset(opt, ds_type=DATA, transform=transform)
trainloader = torch.utils.data.DataLoader(
training_dataset,
batch_size=opt[BATCHSIZE],
shuffle=True,
num_workers=opt[DATALOADER_NUM_WORKER],
drop_last=True)
valid_loader = None
if opt[VALID_DATA] and opt[VALID_DATA][INPUT]:
valid_dataset = ImagesDataset(opt,
ds_type=VALID_DATA,
transform=transform)
valid_loader = torch.utils.data.DataLoader(
valid_dataset,
batch_size=opt[VALID_BATCHSIZE],
shuffle=False,
num_workers=opt[DATALOADER_NUM_WORKER])
console.log('Finish loading data.')
# callbacks:
checkpoint_callback = ModelCheckpoint(
dirpath=opt[LOG_DIRPATH],
save_last=True,
save_weights_only=True,
filename='{epoch:}-{step}',
save_top_k=10, # save 10 model
monitor=opt[CHECKPOINT_MONITOR],
)
# trainer logger:
mylogger = WandbLogger(name=opt[NAME],
project='vielab',
notes=None if not opt[COMMENT] else opt[COMMENT],
tags=[opt[RUNTIME][MODELNAME], opt[DATA][NAME]],
save_dir=ROOT_PATH)
# init trainer:
trainer = pl.Trainer(
gpus=opt[GPU],
distributed_backend='dp',
# auto_select_gpus=True,
max_epochs=opt[NUM_EPOCH],
logger=mylogger,
callbacks=[checkpoint_callback],
precision=opt[RUNTIME_PRECISION],
check_val_every_n_epoch=opt[VALID_EVERY])
# training loop
global OPT
OPT = copy.deepcopy(opt)
trainer.fit(model, trainloader, val_dataloaders=valid_loader)
attack_vectors = extract_attack_vectors(
attack) # Extract the attack vectors from the attack
summary = compute_summary(
attack_vectors
) # Compute summary statistics of the attack (e.g. average bps / Bpp / pps)
# Generate fingeperint
fingerprint = Fingerprint(target=target,
summary=summary,
attack_vectors=attack_vectors,
show_target=args.show_target)
if args.summary: # If the user wants a preview, show the finerprint in the terminal
LOGGER.info(str(fingerprint))
args.output.mkdir(parents=True, exist_ok=True)
fingerprint.write_to_file(
args.output /
(fingerprint.checksum[:16] + '.json')) # write the fingerprint to disk
if args.ddosdb: # Upload the fingerprint to a specified DDoS-DB instance
fingerprint.upload_to_ddosdb(**parse_config(args.config),
noverify=args.noverify)
if args.misp: # Upload the fingerprint to a specified MISP instance
conf = parse_config(args.config, misp=True)
misp_instance = MispInstance(host=conf['host'],
token=conf['token'],
protocol=conf['protocol'],
verify_tls=not args.noverify)
if misp_instance.misp is not None:
fingerprint.upload_to_misp(misp_instance)