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)