help="how much batches to validate", default=10) parser.add_argument( "-bs", "--batch_size", type=int, help="GNN require batch sizes close to 1 due to memory constraints", default=10) args = parser.parse_args() ################################ ####### Comet Logging ########## ################################ if args.log_experiment: logger = experiment_logger("comet", "gnn-yeast") logger.add_params(vars(args)) ################################ ####### DATA GENERATION ######## ################################ print("Loading Data...") file_buffer = open('train.pickle', 'rb') train = pickle.load(file_buffer) file_buffer.close() file_buffer = open('test.pickle', 'rb') test = pickle.load(file_buffer) file_buffer.close()
parser.add_argument("-lm", "--log_model", help="wether to save final weights on comet", action="store_true") args = parser.parse_args() ################################ ####### Comet Logging ########## ################################ file_buffer = open('meta.pickle', 'rb') meta = pickle.load(file_buffer) file_buffer.close() if args.log_experiment: logger = experiment_logger("comet", args.experiment_name) logger.add_params(vars(args)) logger.add_params(meta) ################################ ####### SYSTEM SETUP ########### ################################ if useGPU and torch.cuda.is_available(): device = 'cuda:0' torch.cuda.empty_cache() else: device = 'cpu' # Notify: print("Device selected: %s" % device)
parser.add_argument("-e", "--epochs",type=int, help="number of epochs",default=10) parser.add_argument("-lr", "--learning_rate",type=float, help="learning rate",default=0.000935) parser.add_argument("-vi", "--validation_interval",type=int, help="how much batches to validate",default=50) parser.add_argument("-bs", "--batch_size",type=int, help="GNN require batch sizes close to 1 due to memory constraints",default=4) args = parser.parse_args() ################################ ####### Comet Logging ########## ################################ file_buffer = open('meta.pickle', 'rb') meta = pickle.load(file_buffer) file_buffer.close() if args.log_experiment: logger = experiment_logger("neptune", "gnn-optuna") logger.add_params(vars(args)) logger.add_params(meta) neptune_callback = opt_utils.NeptuneCallback(log_study=True, log_charts=True) ################################ ####### SYSTEM SETUP ########### ################################ if useGPU and torch.cuda.is_available(): device = 'cuda:0' torch.cuda.empty_cache() else: device = 'cpu' # Notify: print("Device selected: %s" % device)