def update(self):
if connected_to_internet():
data = self.fetcher.fetch(self.date_from)
# update whole data, because data can be changed after initial release
data.dropna(axis=0, how='any', inplace=True)
self._combine_data(data)
self.save()
self.last_fetched = datetime.datetime.now()
self.check_up_to_date()
np.random.seed(args.seed)
torch.manual_seed(args.seed)
torch.backends.cudnn.deterministic = args.torch_deterministic
env.seed(args.seed)
env.action_space.seed(args.seed)
env.observation_space.seed(args.seed)
#####################################
# book keeping to log stuff
if args.dryrun:
writer = None
weight_save_path = 'model_dryrun.ckpt'
else:
# check internet connection
# for offline wandb. Will load everything on cloud afterwards
if not connected_to_internet():
import json
# save a json file with your wandb api key in your home folder as {'my_wandb_api_key': 'INSERT API HERE'}
# NOTE this is only for running on MIT Supercloud
with open(os.path.expanduser('~')+'/keys.json') as json_file:
key = json.load(json_file)
my_wandb_api_key = key['my_wandb_api_key'] # NOTE change here as well
os.environ["WANDB_API_KEY"] = my_wandb_api_key # my Wandb api key
os.environ["WANDB_MODE"] = "dryrun"
start_time = time.strftime("%H_%M_%S-%d_%m_%Y", time.localtime())
pretty_env_name = get_pretty_env_name(args.env_name)
experiment_name = f"{args.exp_name}_{pretty_env_name}_{args.seed}_{start_time}"
# create only one wandb logger instead of 8/16!!!
if MPI.COMM_WORLD.Get_rank() == 0:
def update(self):
if connected_to_internet():
LOGGER.send_info("Spuštěn update.")
self._update_datasets()
self.app.callback_queue.put(self._update_controllers)